Master of Science Thesis
KTH School of Industrial Engineering and Management TRITA-ITM-EX 2019:378
Division of Applied Thermodynamics and Refrigeration SE-10044 Stockholm (Sweden)
Techno-economic comparative analysis
on the renewable energy use potential
in multi-family houses in Belgium
This master’s thesis was created for academic purposes at KTH, Royal Institute of Technology, Stockholm (Sweden).
ã KTH Royal Institute of Technology June 2019
Master of Science Thesis TRITA-ITM-EX 2019:378
Techno-economic comparative analysis on the renewable energy use potential in multi-family houses in Belgium
Benjamin van Dam
Approved Examiner
Hatef Madani
Supervisor Hatef Madani Commissioner
Hendrik-Jan Steeman (Arcadis)
Contact person
Abstract
The buildings sector is growing rapidly, and this trend is expected to be maintained. Globally, buildings and construction combined represent roughly 39% of energy-related CO2 emissions.
It is therefore crucial that the widespread implementation of low-carbon solutions for buildings and the use of renewable energy is accelerated rapidly. This study investigated the extent to which the energy system of a residential multi-family house in Belgium can be designed to maximise the share of renewable energy in its heating and household electricity demand, and in this way reduce its operational CO2 emissions. The technologies that were focused on in the
different energy systems that were modelled are ground and air source heat pumps, rooftop photovoltaics, solar thermal collectors, battery electric storage and hot water thermal storage. In a first phase, the technical and environmental performance is assessed, while the second phase consisted of a thorough economic analysis. The results show that a primary renewable energy share of roughly 30% to 34%, and a reduction in the operational CO2 emissions
Contents
PROJECT FEATURES 1
1 INTRODUCTION 2
2 LITERATURE SURVEY 6
3 MODELLING METHODOLOGY AND LIMITATIONS 14
Acknowledgements
List of Figures
FIGURE 1: BUSINESS-AS-USUAL (BAU) SYSTEM DIAGRAM 18 FIGURE 2: ELECTRICITY (ELEC) SYSTEM DIAGRAM 19 FIGURE 3: E&H-A1 SYSTEM DIAGRAM 20 FIGURE 4: E&H-G SYSTEM DIAGRAM 21 FIGURE 5: RESULTS PRIMARY RENEWABLE ENERGY SHARE AND CO2 EMISSIONS ELEC SCENARIO 22 FIGURE 6: RESULTS PRIMARY RENEWABLE ENERGY SHARE AND CO2 EMISSIONS E&H-A SCENARIO 23 FIGURE 7: RESULTS PRIMARY RENEWABLE ENERGY SHARE AND CO2 EMISSIONS E&H-G SCENARIO 24 FIGURE 8: RESULTS PRIMARY RENEWABLE ENERGY SHARE AND CO2 EMISSIONS FROM ALL SCENARIOS 25 FIGURE 9: RESULTS CAPITAL COST FOR PHASE TWO SCENARIOS 26 FIGURE 10: RESULTS TOTAL CAPITAL FOR PHASE TWO SCENARIOS (APPROX. VALUES FOR BAU) 27 FIGURE 11: RESULTS OPERATIONAL COST FOR PHASE TWO SCENARIOS 28 FIGURE 12: RESULTS NET PRESENT VALUE FOR PHASE TWO SCENARIOS 29 FIGURE 13: RESULTS SENSITIVITY ANALYSIS ON NPV FOR CAPITAL COST OF HEAT PUMP AND BOREHOLES
(APPROX. VALUES FOR BAU) 30
FIGURE 14: RESULTS SENSITIVITY ANALYSIS ON NPV FOR COST OF ENERGY (APPROX. VALUES FOR BAU) 31 FIGURE 15: RESULTS SENSITIVITY ANALYSIS ON NPV FOR PRICE-RATIO ELECTRICITY TO GAS (APPROX. VALUES
FOR BAU) 32
FIGURE 16: RESULTS SENSITIVITY ANALYSIS ON NPV FOR DECREASE IN COST FOR PV AND BES (APPROX. VALUES
List of Tables
TABLE 1: OVERVIEW OF PROJECT KPIS AND RELATED TARGETS 15 TABLE 2: MAIN BUILDING ENERGY CHARACTERISTICS POLYSUN MODEL 45 TABLE 3: GAS AND ELECTRICITY PRICES 47 TABLE 4: CAPITAL COSTS MAIN COMPONENTS BAU SCENARIO 47 TABLE 5: CAPITAL COSTS MAIN COMPONENTS ELEC SCENARIO 47 TABLE 6: CAPITAL COSTS MAIN COMPONENTS E&H-A3 SCENARIO 47 TABLE 4: DETAILED RESULTS OF THE SENSITIVITY ANALYSIS ON THE NPV FOR THE CAPITAL COST OF HP AND
BOREHOLES 48
TABLE 5: DETAILED RESULTS OF THE SENSITIVITY ANALYSIS ON THE NPV FOR THE COST OF ENERGY 48 TABLE 6: DETAILED RESULTS OF THE SENSITIVITY ANALYSIS ON THE NPV FOR THE COST-RATIO OF ELEC. TO GAS (DECREASING ENERGY PRICES) 48 TABLE 7: DETAILED RESULTS OF THE SENSITIVITY ANALYSIS ON THE NPV FOR THE COST-RATIO OF ELEC. TO GAS (INCREASING ENERGY PRICES) 48 TABLE 8: DETAILED RESULTS OF THE SENSITIVITY ANALYSIS ON THE NPV FOR THE DECREASE IN COST FOR PV
Nomenclature
ASHP Air source heat pump BES Battery electric storage BEV Battery electric vehicle
BIPV Building integrated photovoltaics BTES Borehole thermal energy storage CES Community energy storage DHW Domestic hot water
DX-SAHP Direct expansion solar assisted heat pump system EV Electric vehicle
GSHP Ground source heat pump G2V Grid-to-vehicle
kWh Kilowatt hour
nZEB Nearly zero-energy building PCM Phase change material
PHEV Plug-in hybrid electric vehicle PV Solar photovoltaic
PV/T Solar photovoltaic and thermal SFP Seasonal performance factor SAHP Solar assisted heat pump system ST Solar thermal
TES Thermal energy storage V2B Vehicle-to-building V2G Vehicle-to-grid
Wp Watt peak
Project Features
This master’s thesis represents the last phase of the Sustainable Energy Engineering Master of Science at KTH Royal Institute of Technology in Stockholm, Sweden. It is carried out in collaboration with Arcadis (Belgium) and with the support of KTH’s Department of Energy Technology.
Arcadis (Belgium)
Arcadis is a leading global Design & Consultancy firm for natural and built assets, with its global headquarters in The Netherlands. Besides being one of the highest ranked companies in ENR’s Top International Design Firms ranking, Arcadis also puts sustainability at the forefront of its business [1]. Being active in over seventy countries, Arcadis operates in various fields such as engineering, environmental solutions, digital innovation, sustainable urban development and architecture, to name a few. For this master’s thesis, a collaboration was established with the Arcadis office in Ghent (Belgium).
Supporting Staff
As this master’s thesis is a collaboration between Arcadis and KTH Royal Institute of Technology, support from both parties was available during the work, and from each party one supervisor was delegated.
KTH Royal Institute of Technology
Hatef Madani Larijani Associate Professor (Docent) in Energy Technology (supervisor)
Arcadis (Belgium)
Hendrik-Jan Steeman Team Leader Green Buildings (supervisor)
Software
1 Introduction
This first chapter will present some key aspects concerning the master’s thesis that was carried out. Context will be given to why addressing the topic is of major importance. Furthermore, the specific research question will be presented, and the major objectives, as well as the general research methodology of this master’s thesis will be addressed.
1.1 Topic Motivation
It is clear that we are currently facing many challenges worldwide. Challenges such as poverty, natural resource depletion, increasing inequality, hunger, water scarcity, preserving the natural environment and climate change, to name a few. The topic of climate change has attained more and more global attention over the recent years and the way we think about energy and development has started to shift. A recent report from the Intergovernmental Panel on Climate
Change (IPCC) has indicated that we only have approximately twelve years left to reduce the
pace at which climate change is increasing, if the goal of limiting global warming to 1.5 °C is to be kept within reach [3]. This task will require extensive worldwide collaboration and might be the biggest global challenge humanity has ever faced.
The energy use of the buildings sector has increased drastically during the last decades as a result of population growth, an increasing demand for thermal comfort and indoor environmental quality, and simply because people spend more time indoors [4, 5]. Nowadays, people spend around 90% of their life inside buildings, where heating and cooling systems are constantly providing the desired conditions, turning buildings into the largest consumers of energy worldwide [4]. Globally, buildings and construction combined represented approximately 36% of the final energy use and 39% of energy-related CO2 emissions1 in 2017,
with fossil fuels (natural gas, oil and coal) accounting for more than 80% of building energy consumption [6]. The buildings sector is growing rapidly, and this trend is expected to be maintained. During the next four decades, “the world is expected to build 230 billion square metres in new construction – adding the equivalent of Paris to the planet every single week” [6]. It is clear to say that the buildings and construction sector will play a pivotal role in facing the major global challenge of limiting climate change.
So, why hasn’t more been done yet? Certainly not due to a shortage of possible solutions. The
IPCC report on Climate Change – Implications for Buildings concluded that “there is major
1This value includes upstream power generation in the calculations and “covers buildings and construction,
potential for energy savings of up to 50-90% in existing and new buildings [and] many mitigation options are immediately available and highly cost-effective” [7]. However, although many effective and clearly documented solutions exist, there is a strong need for strategic policy instruments, market incentives and support for innovative business models to radically drive change, increasingly attract investments and scale up actions around the world to truly make a difference within this sector [6, 7].
A concept that was introduced roughly two decades ago, and became more mainstream in 2006, is that of a zero-energy building (ZEB) [8]. ZEBs, or even net-positive energy buildings, are the next generation of building design, combining renewable energy generation technologies with the concept of green building design. Different definitions exist regarding the actual meaning of ZEBs, and, similarly, there are different calculation methods that focus on different features of the building such as the balancing period, the accepted renewable energy supply options and the requirements for energy efficiency, to name a few [9]. A rather simple definition of the concept, given by the Directive on Energy Performance of Buildings (EPBD), states “a nearly zero-energy building means a building that has a very high energy performance. The nearly zero or very low amount of energy required should be covered to a very significant extent by energy from renewable sources, including energy from renewable sources produced on-site or nearby” [10]. Noting the word “nearly” in this definition, these buildings are usually referred to as nZEBs, or nearly zero-energy buildings. nZEBs and ZEBs are seen as a major solution to limit the increasing pressure the buildings sector puts on our planet, and, in Europe, the EPBD has set the nZEB as the goal for all newly constructed buildings by 2020 [10].
1.2 Research Question
There are many approaches to reduce the energy use and related environmental impact of the buildings sector. Two of the protagonists in this story are energy efficiency and low-carbon solutions. In the UN’s simulations of what will be required to limit global warming to 2°C, known as the 2°C Scenario (2DS), total CO2 emissions related to the buildings sector will need
to decrease by 85% compared to current levels by 2060, with roughly half of this reduction coming from low-carbon power generation [6]. Low-carbon power refers to technologies that can generate power with carbon emissions that are significantly lower than the emissions from conventional fossil fuel power plants. These low-carbon power technologies include solar power, wind power, hydropower, geothermal power – the main renewable energy sources – and nuclear power.
Most of this power generation will occur in large power plants at a significant distance from the buildings where it will be put to use – at least for now. However, mainly solar and shallow geothermal heat technologies are perfectly capable of being integrated in the energy systems of buildings, which can then consume the power that is generated locally. This together with energy storage systems, both referring to electricity and heat (or cold), creates the perfect holding space for innovative energy system configurations that can transform buildings from merely consuming energy from the grid to actively taking part in supplying their energy demand in a smart and sustainable way. This is what this master’s thesis will focus on and the central research question can be stated as:
To what extent, using currently available technologies, can the energy system of a residential multi-family house be designed to maximise the share of renewable energy in its space heating, domestic hot water and household electricity2 demand, and in this way reduce its operational
CO2 emissions?
1.3 Objectives
The goal of this master’s thesis is to think about what the building energy systems of the future are, or, better, what they have to be to put the ambition of the Paris Agreement into action. Different systems or solutions to supply a building’s energy demand will be modelled, incorporating various fossil free (or low-carbon) energy technologies such as photovoltaics (PV), solar thermal (ST) collectors, photovoltaic-thermal hybrid (PV/T) collectors, heat pumps, thermal energy storage (TES) and battery electric storage (BES). These different solutions will then be scored regarding the share of renewable energy they can provide in the building’s space
2 The household electricity demand that will be used represents the energy demand for elements such as lighting,
heating, domestic hot water and household electricity demand. Furthermore, since the cost aspect remains of major importance, an economic analysis will be performed, including the capital cost, operational cost and the net present value (NPV) of the different solutions. Similarly, a comparison of the different solution can then be made regarding these parameters.
1.4 General Research Methodology
2 Literature Survey
In this literature survey, focus will be put on different technologies that can be integrated towards a more sustainable design for the energy systems of residential buildings. The survey will include solar heat pump systems, battery electric storage, hydrogen technology, and EV applications. State-of-the-art practices will be discussed, as well as the future possibilities surrounding these technologies. Furthermore, closer attention will be given to what the current state of affairs is in Belgium. This includes the needed background information, ambitions and policies that are in place, and current as well as future legislation regarding the energy use in the buildings sector.
2.1 Key Technologies for Sustainable Building Energy Systems
2.1.1 Solar Assisted Heat Pump SystemsSolar heat pump systems (SAHPs) are combined systems, often called hybrid systems, that combine electrical heat pumps with solar technologies, such as PV, ST or PV/T. PV and building integrated photovoltaics (BIPV) are now the most established technologies used in the buildings sector to convert solar energy into electricity, using the principle of the photoelectric effect [11]. During the last two decades the PV market has grown quasi exponentially [12], mainly due to decreasing costs and the implementation of attractive government policies [13]. One drawback of PV consists in the fact that a significant share of the incident solar energy is converted into thermal energy, which has a negative impact on the conversion efficiency of the PV cells [4]. PV/T systems, offering a combination of electricity generation through PV and thermal collection, represent an innovative solution to this technical drawback [14]. PV/T can facilitate higher total efficiencies and possibly space saving compared to the separate systems, however, there are still challenges in increasing the performance of these systems [15, 16]. Good et al. [16] carried out a comparative simulation study on the performance of PV, ST and PV/T systems for residential building concepts in Norway with the ambition of reaching the ZEB target. The results of their study showed that a system with only highly efficient PV modules was closest to reaching the zero-energy balance, while a system with uncovered PV/T modules is able to provide a decent electricity output, but a rather small and only low-temperature thermal output.
electricity need from the grid [17]. Ground source heat pump systems (GSHPs) are highly efficient for space heating and cooling in buildings [18]. Especially in colder climates, where the heating demand dominates, hybrid GSHP systems using solar collectors can offer the additional benefit of avoiding the heat depletion of the ground [4]. With a system as such, the heat captured by the solar collectors can produce domestic hot water (DHW) in summer and recharge the ground during winter. Emmi et al. [19] carried out a study on the performance of this type of solar-assisted GSHP in a cold climate. The results of their simulations showed that for the reference system without solar collectors, the seasonal energy performance of the heat pump decreased by approximately 10% over the ten-year simulation period. For the system with solar collectors integrated in the design, the seasonal energy performance remained constant over time. Sommerfeldt and Madani [20] reviewed the state-of-the-art on PV/T plus GSHP systems, including the PV/T collectors, borehole thermal energy storage (BTES) and control strategies. Based on this review, they presented four system concepts with the objective of balancing the system’s performance, practicality and cost. It was emphasized that system optimisation remains challenging due to the variety of configuration possibilities, options in component design and the large design flexibility concerning system control. However, Sommerfeldt and Madani state the potential of hybrid PV/T and GSHP systems to increase renewable fractions of heating, cooling and power generation in buildings, since the combination of these two technologies benefits the performance of each component in the new hybrid system. The efficiency of the solar collector increases, surplus heat can be stored in the ground using the boreholes for short-term as well as long-term and the increased borehole temperatures enhances the efficiency of the heat pump.
2.1.2 Thermal Energy Storage
Since the cooling and heating demand in buildings is often unbalanced over a year, GSHP systems could experience a positive impact from being integrated with a supplementary energy storage system [18]. The possible TES systems that can be used include both heating and cooling storage technologies. Zhu et al. [18] performed a thorough review on the research and applications of TES assisted GSHP systems. In their work, five different categories were defined: GSHP integrated with ice storage tanks, GSHP integrated with solar collectors, GSHP integrated with soil, GSHP integrated with water tanks, and lastly GSHP integrated with phase change materials (PCMs). During the last decade, a lot of studies have focused on increasing the performance of such systems. Zhang et al. [24] carried out a study on the operation modes of a GSHP integrated with an ice storage system based on an air-conditioning project for a commercial building in Beijing. By using ice storage technology in a system, cooling can be produced and stored in a storage tank during night-time, when the cooling demand is typically low or equal to zero, and this cold storage can then be used for cooling during daytime. Zang et al. concluded that the needed investment cost for the integrated system was more than double the cost for the conventional reference air-conditioning system. However, the average annual operation fee decreased by roughly 38%, resulting in a payback period of 4.7 years. Han et al. [25] studied a solar assisted GSHP heating system integrated with a latent heat energy storage tank. Through numerical simulations, the integrated system was analysed during the heating period in Harbin, China. It was shown that by using the charge and discharge heat of the latent heat energy storage tank, the system operated more effectively, and both the flexibility as well as the stability of the system increased. Another study analysed the performance of a solar-earth source heat pump for heating, which allowed heat to be stored in the earth or a water tank [26]. Results showed an energy saving rate of 14.5% compared to the reference conventional GSHP system. An important conclusion regarding the use of water tanks as TES in a system was stated by Wang et al. [27], who studied the performance of underground thermal storage in a solar-ground coupled heat pump system for residential buildings. Their results showed that the performance of the thermal storage in the system was not only strongly depending on the intensity of solar radiation, but it was also greatly affected by the matching between the water tank volume and the area of solar collectors.
materials is an efficient way to improve the thermal energy storage capacity of a building [30]. Schossig et al. [31] studied the thermal performance of lightweight buildings integrated with microencapsulated PCM in Germany for a period of one year. Results showed that the integration of the microencapsulated PCM caused a reduced cooling demand and an increase of thermal comfort in the building. This increase of thermal comfort due to the use of PCMs was also shown by Chan [32], who investigated the energy and environmental performance of a typical residential flat with PCM integrated in the external wall in Hong Kong.
PCM technology can also be integrated in the design of GSHP or SAHP systems. Bonamente et al. [33] analysed two possible upgrades for the optimisation of the energy performance of a conventional reference GSHP system. The first upgrade included a water tank as TES, while for the second upgrade a completely new and more compact TES using PCMs was designed. The systems were used to satisfy the heating and cooling demand of the building for a period of two years and results have shown significant improvements in the system performance. For the first upgrade, the COP increased from 3.4 to 4.1 in heating mode and from 2.9 to 5.7 in cooling mode, compared to the reference system. Similarly, for the second upgrade using PCMs, the COP reached 4.1 and 5.9, respectively. Furthermore, the total volume needed for the PCM heat storage was about ten times smaller than the volume needed for the water tank.
2.1.3 Battery Electric Storage (BES)
sufficiency of a building, making it less dependent on the available electric grid. In most countries, consumers are charged for electricity depending on the time of use, currently often including two tariffs: the “low” tariff during night and the “high” tariff during daytime [38]. However, it is certainly possible that this rather simple high/low tariff will be replaced with a more complex system of fluctuating tariffs spanning a broad range of electricity prices depending on the exact moment when then electricity is taken from the grid. In this case, which is already the reality in Sweden, it would of course be very interesting that your battery would be charged using electricity from the grid during a period when this electricity is fairly cheap, to then use the electricity to meet the demand of the building during a period in which grid prices are high. Or, similarly, since the energy mix of the grid is constantly changing, a battery could be programmed to take electricity from the grid when the share of renewable (low-carbon) energy is large. Batteries can also offer opportunities as community energy storage (CES) systems. Parra et al. [39] analysed the optimal performance of a CES system designed for a 100-home community in the UK. The methodology included three reference years (2012, 2020 and a zero-carbon year) to show the evolution of the business case during the low carbon transition. Results of their community approach for battery energy storage showed a cost reduction of 37% and 66% regarding a single home, in 2020 and the zero-carbon year, respectively.
2.1.4 Electric Vehicles (EVs)
potential to store energy when it is cheap to use in peak priced periods, but can also transport energy from one place to another as dispatchable energy sources [43]. If we then fast-forward to a time in which autonomous vehicles dominate the market, the possibilities seem endless. In recent years many studies have analysed the potential of EVs in building energy management systems. Mesaric and Krajcar [44] studied home demand side energy management integrated with EVs and renewable energy sources and developed a program to maximize the share of renewable energy in the energy consumption of residential buildings in Zagreb. Pang et al. [45] reviewed the potential benefits of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) as dynamically configurable dispersed energy storage in V2B operating mode. They emphasize that with enough available EVs the aggregated batteries could play an important role in the electricity demand of a typical building and create revenue for vehicle owners. The idea of making money as an EV owner – besides the money you save on fuel – from services your vehicle can provide when it is not being used certainly sounds interesting and hopefully this can provide an additional boost in the future to the penetration of EVs in the global vehicle market.
2.1.5 Hydrogen & Fuel Cells
One of the central debates regarding the future of transportation is the one of batteries versus
hydrogen, with experts around the world voicing very different opinions. While Tesla is
claims that the construction costs for this building is only 10% higher than those of a regular building, while the building itself is able to cover all the energy requirements of its tenants [48]. A research team at the University of Leuven in Belgium approached the use of hydrogen technology from a different perspective. After roughly ten years of research, the team led by Professor Johan Martens succeeded in developing a new kind of solar panel that generates hydrogen by using solar irradiation and the water vapor available in the air [49]. With a size of 1.6 square meter, this innovative solar panel is similar in size as many conventional solar panels and, although the technology is yet to face extensive field testing, it certainly shows potential. According to Jan Rongé, one of the engineers on the team, twenty of these panels could meet the entire energy demand, regarding heat as well as electricity, of a well-insulated house, even in winter, while another twenty panels could provide enough hydrogen to fuel a hydrogen car for the full year [49].
2.2 Belgium: Current State, Policy and Legislation
Like the rest of the European Union, Belgium took part in signing the Paris Agreement in December 2015 at the conclusion of COP21, agreeing to limit global warming “to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C” [50]. Approaching the five-year mark of this commitment and with the year 2020 being an important milestone in many ongoing national and international projects, it is a good moment to take a step back and look at what has happened so far. A recent study carried out by Robiou du Pont and Meinshausen in 2018 [51] gave birth to the so-called Pledged Warming Map. This colourful map of the world indicates for each country the level of global warming the world would reach by the year 2100, if all other countries would follow the ambition of the country in question [52]. It can be seen on the map that if all would follow the ambition of Belgium to limit global warming, the world would reach 3.2°C of global warming by 2100, more than double the level of what should truly be aimed for. What is maybe even more disturbing is the fact that only a handful of European countries perform better than Belgium, with Sweden – praised for being one of the most innovative, environmentally friendly and sustainable countries around the world – showing a value of 2.7°C.
used in Belgium comes from fossil fuels. Looking at the country’s electricity production, it can be seen that 50% is coming from nuclear energy [54]. Knowing that the government so far has decided to completely phase out nuclear and close all seven reactors by 2025, the energy sector is certainly up for a challenge to fill this void. As for the rest of Europe, the role of renewables in Belgium will become increasingly important. The EU has set a target of 20% renewable energy share in the final energy consumption by 2020, with the target for Belgium being 13% [55]. The latest results show that the EU and Belgium have reached, respectively, 17.5% and 9.1 % in 2017 [56].
ZEBRA2020, or Europe’s Nearly Zero-Energy Building Strategy 2020 to accelerate the market uptake of nZEBs, is obviously also binding in Belgium. One complication regarding these nZEBs or nearly ZEBs, is the meaning of the word “nearly”. Every country is allowed to give its own definition to this word and this definition usually differs for new buildings or existing buildings [57]. Furthermore, with Belgium consisting of three fairly autonomous regions (Flanders, Brussels, Wallonia), all three regions can – and have – stated different definitions [57]. In Flanders, besides the specified nZEB regulation, all new buildings (from 2014), and significant renovations (from 2017), also need to get a certain minimum amount of energy from renewable energy sources [58]. Available measures to do so include the integration of solar PV or a heat pump in the energy system, installing a solar or biofuel boiler, or the participation in a renewable energy production project, to name a few. This minimum amount of renewable energy currently equals 15 kWh/m2 per year for residential buildings and 20 kWh/m2 per year
3 Modelling Methodology and Limitations
This chapter will put a focus on the research intentions of this master’s thesis, clearly indicating what is considered to be part of the scope and what is not, while also elaborating on some elements that were described already earlier in the General Research Methodology in Chapter 1. Some minor additional details might be added or reasoned for further in the report, however, the main points of interest will be presented here.
3.1 Comparative Study
The objective of this study is to present different scenarios for the energy system of a multi-family house in Belgium and compare their performance. These scenarios represent possible alternatives, consisting of distinct combinations of energy technologies. The different scenarios will not only be compared to one another, but also to a reference system that can be seen as the
business-as-usual (BAU) scenario concerning meeting the energy demand of a multi-family
house in Belgium. The emphasis throughout the study will remain on its comparative nature. Although the operation of the different scenarios will be optimised and thoroughly analysed, a detailed study on the impact of all the elements of the different model configuration on the overall performance, followed by an extensive parametric optimisation is not considered to be part of the scope of this master’s thesis.
The geometry of the building that will be modelled in Polysun will be based on a recent residential development in Belgium from Arcadis. The building geometry will be the same for the different scenarios, while every scenario will represent a specific solution to supply the building’s space heating, domestic hot water and household electricity demand. The building dimensions and the design of the different scenarios will be discussed further in Chapter 4.
3.2 Key Performance Indicators
Table 1: Overview of project KPIs and related targets
KPI TARGET
Primary renewable energy share 75%
CO2 emissions Net-zero3
Capital cost Not significantly higher than BAU
Operational cost -50% compared to BAU
Net present value Higher than BAU
Achieving a primary renewable energy share in the building’s space heating, domestic hot water and household electricity demand of 75% might seem an excessively bold target, knowing that the electric grid in Belgium only offers roughly a yearly primary renewable energy share of 15%. However, this is the kind of ambition needed from the “developed world” to keep our planet within the 2°C scenario (2DS), or even better, to stay as close as possible to the 1.5°C scenario. As mentioned before, to stay within the 2DS, total CO2 emissions related to the
buildings sector will need to decrease by 85% compared to current levels by 2060 [6], while the World Green Building Council urges businesses and governments to reach net-zero operating emissions for all new buildings and existing buildings from 2030 and 2050, respectively [60]. For the three economic KPIs, it is slightly more difficult to define a specific absolute target. A major benefit of a well-designed building energy system incorporating renewable energy technologies is the often-large reduction in operational cost that can be achieved. Therefore, this is obviously what is expected from the different solutions that will be modelled. However, the capital cost of such systems is often significantly higher than the conventional system. It is clear that both the capital cost as well as the operational cost play their part in the overall cost analysis, with, for example, a large increase in capital cost being justified by a sharp reduction in operational cost. Of course, as was shown by the Swiss “house of the future”, the ideal case would consist of a system with lower operational costs and a capital cost that is, at least, not significantly higher than the reference system. By using these two cost elements to assess the net present value of the different scenarios, a more conclusive economic result can then be obtained, which can be used to make clear and more decisive comparison.
3.3 Limitations in the Modelling Setup
In Chapter 2, some possible opportunities were mentioned concerning specific interactions between a building’s energy system and the grid, depending on the energy mix of the latter at a specific moment, or more specifically the share of renewable energy. However, incorporating
this dynamic energy mix of the grid into the energy model is a complex task and will not be part of the scope of this study. This implies that any electricity from the grid that will be supplied to the building will be considered to come from a mix of sources equal to the annual average.
Furthermore, as was mentioned by Sommerfeldt and Madani [20], the optimisation of an energy system comprised of multiple elements remains very challenging due to the vast amount of possible system configurations, the multitude of options in component design and system control, and the interdependency of performance between the different components. The objective of this study is to compare several interesting alternatives regarding the stated KPIs. And although the different alternatives will represent high-performing solutions to a building’s energy demand, a full optimisation of each individual alternative is not considered to be within the scope of this study. Therefore, the results of this study should be interpreted accordingly, i.e. as a comparative analysis between different effective combinations of technologies, not an extensive system optimisation.
A final remark regards the KPI of reducing CO2 emissions. When talking about the emissions
from the buildings sector, there are two components: operational emissions and embodied emissions. The main focus is often put on reducing the operational CO2 emissions of a building,
4 Different Scenarios
In this chapter the different scenarios that are developed in Polysun will be presented4. The
business-as-usual (BAU) scenario will serve as the reference system for comparison.
Additionally, two other scenarios were developed, with one of them consisting of more than one variant. As was emphasised before, the objective of this study is to compare different combinations of energy technologies and concepts. Therefore, the three scenarios focus on very different central concepts, i.e. mainly relying on natural gas, the use of solely electricity and combining the efficient use of both electricity and heat.
As stated before, the building geometry that is used is based one of Arcadis’ recent residential developments in Belgium. The building is a five-floor multi-family apartment building with a rectangular floorplan with dimensions of approximately 13 by 38 metres, and a basement level consisting of technical rooms. In the original design, the first two floors are intended for commercial purposes, however for this study all floors will be considered to fulfil a residential purpose. Every floor consists of three large apartments: two three-bedroom apartments intended for four people and one two-bedroom apartment intended for three people, resulting in a total of 15 apartments inhabiting about 55 people. Since the focus of this study is not on obtaining specific results for residential development in particular, but more on the possibilities in general regarding multi-family houses in Belgium, the space heating demand of the building is simulated using the built-in building characteristics related to the “multifamily house,
low-energy building” template of Polysun’s database.
4.1 Business-as-Usual
The Business-as-Usual (BAU) scenario in this study is seen as the reference scenario for the others and is designed to reflect the current common practice in Belgium regarding multi-family houses. The system relies on a central collective gas boiler for the heating demand, consisting of space heating and domestic hot water, while the entire electricity demand is provided by the electric grid. The BAU system diagram is shown in Figure 1.
The space heating demand of the building is governed by the desired thermal comfort level for which standard heating setpoints were chosen, i.e. 21°C and 18°C for day and night, respectively. The domestic hot water demand was set to 50 litres per person per day, following
4 In order to keep the main report concise and still give a thorough enough description where needed, more
Polysun’s suggestion. This estimation for a multi-family house’s hot water consumption was
also checked and confirmed with the Brussels Institute of Environment [62]. Similarly, using average consumption data estimates [63], the total annual household electricity consumption was set to 59,000 kWh per year – 4200 kWh and 3400 kWh per year for, respectively, the four and three bedroom apartments. Both the domestic hot water demand as well as the household electricity consumption are identical for all the different scenarios that are developed, including any variant to a specific scenario. However, the radiator system that is used for space heating in the BAU scenario is replaced by floor heating in all other scenarios.
Figure 1: Business-as-Usual (BAU) system diagram
4.2 Focus on Electricity
The second scenario is called the Electricity (ELEC) scenario. In this scenario the focus is put on generating clean electricity on-site through rooftop PV and putting this electricity to good use. Therefore, the central gas boiler, which was responsible for the entire heating demand in
BAU, is replaced by a central ground source heat pump (GSHP) system. The generated
electricity coming from the rooftop PV can in this case be used to meet the household electricity demand as well as to power the heat pump, while any additionally needed electricity is provided by the electric grid and excess electricity can be stored using batteries. The ELEC system diagram is shown in Figure 2.
that needs to be produced is small. Furthermore, using floor heating typically results in a higher mean radiant temperature of the room in question, at which perceived thermal comfort levels are reached at lower air temperatures [64]. Therefore, the heating setpoint can be set to 20°C and 17°C for day and night, respectively, without jeopardising thermal comfort, for this scenario as well as for the third scenario.
Figure 2: Electricity (ELEC) system diagram
The building, with a roof area of 494 m2, offers a significant amount of space that can be used
for the implementation of PV. The PV system that is used in this scenario consists of four 8x5 arrays of mono-crystalline 300-Wp modules, resulting in a system with a total of 160 PV
4.3 Combining Electricity & Heat
The third scenario is the Electricity and Heat (E&H) scenario. Whereas in the previous scenario (ELEC) the available rooftop area was solely used for PV, E&H also includes heat collection through introducing solar thermal (ST) collectors to the system or the use of PV/T panels. Since the amount of options in system configuration and component selection becomes increasingly large in this case, three different possibilities will be analysed for this scenario, with two of them being very close variants of each other.
The first system (E&H-A1) integrates both PV and ST collectors with a central air source heat pump (ASHP), a hot water storage tank and battery storage. For the ST system, glazed, flat-plate, premium quality collectors were chosen from the Polysun database. Furthermore, different PV to ST collector ratios led to different designs of the PV arrays. According to the design, inverters with suitable current and voltage ranges were selected from the Polysun database. The E&H-A1 system diagram is shown in Figure 3. As was stated before, the domestic hot water demand and household electricity consumption remain unchanged, while the same comment made for ELEC concerning the use of floor heating is valid for this scenario. As a small sidestep to this first system, the second system is a variant to the first, only differing from it in one aspect. In the second system (E&H-A2) the PV and ST collectors from E&H-A1 are replaced with PV/T panels. In Chapter 2, some advantages but also some remaining challenges of PV/T technology were reviewed, however it is interesting to put this option next to the conventional option of combining PV and ST and analyse how it impacts the system.
The third system, referred to as E&H-G, makes use of a central borehole-type GSHP, similar to ELEC, and is shown in Figure 4. As the previous system, E&H-G furthermore combines PV, ST collectors, batteries and a hot water storage tank in its operation. The heat collected through the ST collectors can be used to heat the water in the storage tank, which in its turn can be used to meet the space heating or domestic hot water demand. However, this system also offers the possibility to use the ST collectors for a different purpose. When the heating demand is relatively low, typically during the summer months, and the storage tank is sufficiently charged, the heat pump will not be running and the collected heat from the ST collectors can be used to recharge the borehole field. After the winter and autumn months, where heat has continuously been extracted from the ground by the borehole ground loop, the ground tends to cool down. This has a negative effect on the efficiency of the heat pump. Therefore, by recharging the ground during summer, not only can a stable performance of the heat pump be established throughout the year, but the loss of efficiency over a longer period of time due to low-pace but incremental ground cooling can be limited as well.
5 Results
The results of the different scenarios, that were modelled and simulated in Polysun, were obtained in two phases and will be presented accordingly. In the first phase, several possible variants of the systems presented in Chapter 4 were created by combining different design choices such as, for example, the amount of batteries, the size of the hot water storage tank and the PV to ST collector ratio. This resulted in many different system configurations, for which the first two KPIs were assessed, i.e. the primary renewable energy share in the building’s space heating, domestic hot water and household electricity demand and the operational CO2
emissions. Based on the conclusions from this assessment, a selection was then made of the most promising systems, for which an economic analysis was then performed in phase two.
5.1 Primary Renewable Energy Share & CO
2Emissions
In the Electricity (ELEC) scenario, 25 different variants were modelled, representing different combinations of design choices. The parameters that were experimented with to optimise the performance of the model regarding the first two KPIs were the amount of batteries, the size of the hot water storage tank, the depth of the boreholes and the size of the heat pump. The results of the simulations were plotted and can be seen in Figure 5.
Figure 5: Results Primary Renewable Energy Share and CO2 Emissions ELEC scenario
The primary renewable energy share is shown on the horizontal axis in Figure 5 and shows a range between, roughly, 25% and 33%. This is a significant improvement compared to BAU
for which a primary renewable energy share of 7.1% was found. Regarding the operational CO2
emissions of the system, it can be seen that ELEC, compared to the BAU scenario, achieves a reduction in CO2 emissions of approximately 70% to 76%.
For the Electricity & Heat (E&H) scenario, a distinction was made between using an air source heat pump (E&H-A) or using a ground source heat pump (E&H-G). Starting with E&H-A, in total 31 variants were modelled and simulated in Polysun. As was stated before, one main design choice in this system consisted of how the rooftop area would be used, i.e. for a combination of PV and ST collectors (E&H-A1) or entirely for PV/T panels (E&H-A2). However, despite the name of this scenario, a third option was tested, namely combining the air source heat pump from the E&H-A system with a rooftop area that is solely used for PV. This variant is referred to as E&H-A3. Furthermore, other parameters that were altered in the different variants were the amount of batteries, the ratio of PV to ST collectors (where applicable) and the size of the hot water storage tank. The results are shown in Figure 6.
Figure 6: Results Primary Renewable Energy Share and CO2 Emissions E&H-A scenario
Two main groups can be seen in the plotted results in Figure 6, depending on the way the rooftop area is put to use. The E&H-A1 variants more towards the lower right corner of the graph, meaning a higher primary renewable energy share but lower reduction in CO2 emissions,
and the E&H-A2 and E&H-A3 variants quite close together and more towards the top left corner, meaning a lower primary renewable energy share but greater reduction in CO2
emissions. Furthermore, the results in Figure 6 present a good opportunity to reflect on the relative importance of these two first KPIs. As both are certainly important KPIs to work with
when designing buildings and their energy systems, one of them has a more practically meaningful nature. While the primary renewable energy share is perhaps more related to a visualisation of how well renewables are integrated in the building’s overall design, the actual reduction in operational CO2 emissions is certainly more touching upon the final objective for
the buildings sector in the coming decades. Or in other words, the KPI of reducing operational CO2 emissions can be seen as the result of the increasing integration of renewables in the
building’s design, amongst other aspects. With this in mind, the choice of using only PV
(E&H-A3) in the E&H-A scenario, seems to be the best option. Although E&H-A3 variants show lower
values for the primary renewable energy share than E&H-A1 variants, a slightly higher reduction in CO2 emissions can be achieved. Furthermore, choosing to use only PV makes the
system less complex and thus cheaper, besides the fact the PV is also the least expensive of the three technologies that were considered. Therefore, from the three options analysed in E&H-A, only E&H-A3 will be analysed further in phase two, representing the most promising option from the E&H-A scenario (although not doing justice to the scenario’s name).
The E&H-G scenario then looked at the option of using a GSHP in combination with PV and ST collectors. Being the most complex system of the ones that were analysed in this study, it allowed for less variability in possible configurations. Eight variants were simulated, from which the results are shown in Figure 7.
Figure 7: Results Primary Renewable Energy Share and CO2 Emissions E&H-G scenario
To put these results better into perspective, Figure 8 shows the results of all the variants from the different scenarios that were simulated, together. In Figure 8 it can be seen that the performance of variants of the E&H-G scenario is very similar to those of the ELEC scenario,
both regarding the primary renewable energy share as well as the reduction in operational CO2
emissions compared to BAU. Furthermore, the results in Figure 8 show the difference in the CO2 reduction that can be achieved between systems using an air source heat pump and those
using a ground source heat pump, with the latter clearly performing better in this aspect.
Figure 8: Results Primary Renewable Energy Share and CO2 Emissions from all scenarios
A similar remark to what was said about the best option in the E&H-A scenario can be made when comparing the ELEC and the E&H-G scenarios, which both are using a ground source heat pump. As was said before, both options show very similar performance, with the ELEC scenario reaching only slightly higher values regarding the reduction in CO2 emissions.
However, again, integrating ST collectors into the system’s design, and thus reducing the available space for PV, makes the E&H-G variants significantly more complex than the ELEC alternatives, causing the system to be more expensive without any gain in performance. As one of the advantages of combining ST collectors (or PV/T) with a GSHP to recharge the ground being that it limits the long-term degradation of the heat pump’s efficiency, the latter statement deserves a small side note. For both the ELEC and E&H-G scenario, one variant was simulated with a pre-run time of twenty years to study this aspect of the system. Results showed that in both cases the efficiency of the heat pump decreased, leading to a higher electricity consumption of the heat pump. For the ELEC and the E&H-G variant, an increase in consumption of, respectively, 5% and 2.3% could be seen, resulting in a decrease of the reduction of CO2 emissions of, respectively, 1.2 and 0.5 percentage point. These results confirm
that the integration of ST collectors does pose an advantage to the system, however the scope
of this study does not include extensive conclusions regarding this aspect, with other studies far more suitable to discuss this topic. Therefore, following the results shown in Figure 8, from the
ELEC and E&H-G scenarios, only ELEC will be analysed further in phase two, representing
the most promising option that makes use of a ground source heat pump.
5.2 Capital and Operational Cost
In this second phase, the three remaining KPIs are assessed. The capital cost related to the energy system of a multi-family house typically exists of many components, such as the cost of various types of equipment, labour and project management, to name a few. However, many of these capital costs can be seen as more or less fixed, in a sense that they do not depend entirely on the type of energy system that is chosen for the building. Therefore, when assessing the capital cost of the three scenarios, focus will be put on the relative differences, e.g. what components are needed in ELEC or E&H-A3, but not in the BAU scenario.
The results regarding the capital cost of the three scenarios, as described above, are shown in Figure 9. It can be seen that BAU represents a significantly lower capital cost than the two other scenarios, with the capital cost for ELEC and E&H-A3 being roughly ten and eight times higher than that for BAU, respectively. This is caused by the large investment needed for elements such as a high amount of rooftop PV, battery electric storage, floor heating and the heat pump system, as is indicated in Figure 9. Although these results seem to put the ELEC and E&H-A3 scenarios in a quite unfavourable economic position regarding the investment required, Figure 9 does not quite show the full picture and should be put into perspective.
Figure 9: Results Capital Cost for phase two scenarios 0 50000 100000 150000 200000 250000 300000 EU RO CAPITAL COST
BAU ELEC E&H-A3
As mentioned before, the results in Figure 9 have to be interpreted as relative added cost on the level of the energy system of the building and thus not represent the total cost related to the energy system. Furthermore, the cost of construction of a large multi-family house – from the moment the first groundworks start until the apartments are ready for people to move in – holds many more components. Following estimated values for the “all inclusive” cost per square metre for the construction of a multi-family house in Belgium, the total capital cost for the building in question was calculated. Since it is quite clear that any value estimating the total construction cost per square meter can only be a rough approximation, depending on a vast amount of aspects, the calculations include a sensitivity analysis, with a range of 20% on the reference cost. The results are shown in Figure 10.
Figure 10: Results Total Capital for phase two scenarios (approx. values for BAU)
As intended, the results in Figure 10 certainly put things in perspective, showing a more meaningful capital cost comparison, namely the total capital cost of the building that is to be constructed, for the different scenarios. Looking at this total capital cost, it can be seen that
ELEC and E&H-A3 would be, respectively, 6.2% to 9.4% and 4.6% to 7.0% more expensive
than BAU. Keeping in mind that for ELEC and E&H-A3 the operational CO2 emissions would
be lowered by more than 70% compared to BAU, the assessment whether the additional investment that is required can be justified to the client, might thus include some environmental considerations. 0 1000 2000 3000 4000 5000 1000 EU RO
TOTAL CAPITAL COST
For the fourth KPI that is assessed, being the yearly operational cost, results can be seen in Figure 11. The operational cost for the different scenarios consists of the energy costs and maintenance cost related to the system. As indicated in Figure 11, both ELEC and E&H-A3 show a large decrease in operational cost of 47% and 42%, respectively. This sharp decrease in cost is mainly caused by opting for a heat pump instead of a gas boiler and by the locally generated electricity through PV, and the storage of this electricity through batteries, which reduces the amount of electricity that needs to be bought from the grid.
Figure 11: Results Operational Cost for phase two scenarios
5.3 Net Present Value (NPV)
Comparing the capital cost and operational cost of different options certainly has its value, however, it can be argued that these two elements are also not much more than quite isolated parameters that still need to be processed to reach a more final or conclusive economic result, ready to weigh in on decision-making. Reaching this point can be done by using these two parameters to assess the net present value of the different options. This was done for a period of 30 years and the results are shown in Figure 12. First of all, the net present value for every scenario has a negative value, so in fact actually representing a net present cost, since no revenue is expected in all cases. The major benefit of looking at the net present value instead of at capital cost and operational cost separately, is that the impact of the relative savings made in regards of the operational cost for ELEC and E&H-A3 compared to BAU, now becomes clearly visible. Whereas the results in Figure 9 showed the capital cost of ELEC and E&H-A3
0 5000 10000 15000 20000 25000 30000 35000 EU RO / YEA R OPERATIONAL COST
BAU ELEC E&H-A3
29300
15600 17000
being approximately ten and eight times higher than BAU, the difference regarding net present value over a period of 30 years is just 12.3% and 5.9%, respectively.
Figure 12: Results Net Present Value for phase two scenarios
5.4 Sensitivity Analysis on the Net Present Value
As was already touched upon when analysing the capital cost, a major challenge in doing an economic analysis is the limited quality data available, resulting in a significant uncertainty regarding some aspects of the analysis. Especially when dealing with future costs, such as in this case, for example, future energy or equipment costs, this becomes even more tricky, since making predictions about the future is not easy and always uncertain. Then applying this initial uncertainty to a long-term simulation will increase the uncertainty on the final results even more. Therefore, this section focuses on multiple sensitivity analyses on the net present value that were performed concerning elements of the analysis which were identified as having a significant level of uncertainty and a potentially large impact on the results.
The first element for which a sensitivity analysis is performed, is the capital cost of the heat pump, and borehole ground loop in the case of ELEC. The reason for doing a sensitivity analysis on this cost is mainly due to the difficulty of finding a quality source for the cost of large heat pumps and borehole installations. Furthermore, these costs are generally not fixed, but depend on various project-specific variables. The results are shown in Figure 13. Since the capital cost of the heat pump and boreholes represent significant share in the total capital cost, as was shown
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NET PRESENT VALUE
BAU ELEC E&H-A3
in Figure 9, it is only normal that any changes to this cost affects the net present value. However, looking at the relative differences in Figure 13, the applied uncertainty of 20% on the cost of these elements does not impact the NPV results in any drastic way. A lower cost for the heat pump and borehole ground loop quite simply leads to an NPV for ELEC and E&H-A3 which differs less than that for BAU and vice versa, however to a limited extent.
Figure 13: Results Sensitivity Analysis on NPV for capital cost of heat pump and boreholes (approx. values for BAU)
A second element that has a high level of uncertainty and possibly a large impact on the NPV of the different options is the cost of energy. This is typically a parameter that is increasingly hard to forecast, depending on many aspects such as import prices, government regulation and the decreasing cost of technology, amongst many others. For this analysis, the gas and electricity price are varied from a decrease of 15% up to an increase of 30%, compared to the reference cost. The results are shown in Figure 14. With a decreasing energy price, the cost benefit of using less energy obviously becomes relatively smaller. This is also what is shown in the left side of Figure 14. Whereas, for the reference case, ELEC and E&H-A3 have an NPV that is, respectively 12.3% and 5.9% lower than that for BAU, in the case of a decrease in energy cost by 15%, these relative differences rise to, respectively, 22.8% and 14.4%. On the other hand, in the case of increasing energy prices, options using less energy become more attractive. For an increase of the energy prices by 15%, the results show that E&H-A3 has a higher NPV than BAU. Furthermore, in the case of an increase of the energy prices of 30%, both ELEC and
E&H-A3 exceed the NPV for BAU, respectively, by 1.7% and 5.5%. Now, how much these
energy prices are going to change in the coming years is difficult to predict. However, looking
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NPV SENSITIVITY - CAPITAL COST HP & BOREHOLES
at recent years, a trend of increasing gas and electricity prices can be seen for Belgium [65]. In this case, scenarios offering significant reductions in the energy demand would thus become increasing attractive from a cost point of view.
Figure 14: Results Sensitivity Analysis on NPV for cost of energy (approx. values for BAU)
Zooming in further on the cost of energy, another important aspect is the relative price of electricity compared to gas. Various energy roadmaps have emphasised the benefits of electricity becoming the major energy carrier regarding the goal of reducing global CO2
emissions, and an electricity cost that would become more favourable compared to the cost of fossil fuels could help achieving this [66]. The ratio of the reference price per kWh of electricity to that of gas is 4.2, indicating that one kWh of electricity is four times more expensive than one kWh of gas. The performed sensitivity analysis looked at the impact on the NPV when this ratio changes. However, changing the price-ratio of electricity to gas from one value to another can be done by applying changes to these prices in many different ways. Therefore, two possibilities were looked at, i.e. achieving a certain price-ratio change by keeping one price constant while increasing the other or by keeping one price constant while decreasing the other. In the latter case, the NPV for ELEC and E&H-A3 became increasingly unfavourable compared to BAU for the entire sensitivity range. This is also what could be concluded from Figure 14, namely that a decrease of the cost of energy relatively benefits the NPV for BAU. However, since gas prices in Belgium are expected to rise, the former of the two mentioned possibilities was assumed more likely.
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NPV SENSITIVITY - COST OF ENERGY
The sensitivity range of the price-ratio of electricity to gas that is considered is +25% tot -50%, or a ratio range of, respectively, 5.25 to 2.1. In the case of an increasing price-ratio (+25%), the gas price is thus kept constant while the electricity price increases and for a decreasing price-ratio (-25% and -50%) the electricity price is kept constant while the gas price increases. The results are shown in Figure 15. It can be seen that for all changes to the price-ratio, ELEC and
E&H-A3 perform relatively better compared to BAU than they do in the reference case.
However, the biggest relative impact on the NPV can be seen for a decreasing price-ratio, or in other words, when electricity becomes relatively less expensive compared to gas. With a reduction of 25%, bringing the price-ratio of electricity to gas to 3.15, ELEC and E&H-A3 represent an NPV of, respectively, +5.5% and -0.3% compared to BAU. If the price-ratio decreases even further to 2.1 (-50%), the NPV for ELEC and E&H-A3 reaches a value of, respectively, +17.6% and +22.3% compared to BAU, making them both clearly the more attractive alternatives regarding long-term cost.
Figure 15: Results Sensitivity Analysis on NPV for price-ratio electricity to gas (approx. values for BAU)
Finally, the decrease in cost of certain energy technologies could play a major role regarding the NPV for the different scenarios as well. As already indicated in Figure 9, PV and battery electric storage (BES) represent a large share of the capital cost – roughly 48% for ELEC and 59% for E&H-A3. However, the cost of these elements is falling rapidly. By 2025, PV module prices could fall roughly another 40%, compared to 2019, after already a decade of sharp decreases [67, 68]. And, by 2030, the cost per kWh for BES is projected to decline by up to 61%, compared to 2016 [69]. It is clear that the heavy weight of these elements on the capital
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NPV SENSITIVITY - PRICE RATIO ELECTRICITY/GAS
cost, together with the predicted large cost reductions, certainly has the potential to impact the NPV. A sensitivity analyses is performed for a cost reduction up to 40%5 and results are shown
in Figure 16.
Looking at E&H-A3 compared to BAU, a 20% decrease in the cost of PV and BES, which could already be the new reality within three years, would result in a marginally higher NPV for
E&H-A3. With the cost of these technologies decreasing even further to 40%, the difference grows to
7%. A similar trend can be seen for ELEC, with a 20% and 40% cost reduction of PV and BES leading to an NPV of, respectively, -5.3% and +1.7% compared to BAU.
Figure 16: Results Sensitivity Analysis on NPV for decrease in cost for PV and BES (approx. values for BAU)
5 For these values, the year 2025 was used as the reference year. Since the source on BES gave a cost reduction -800000 -700000 -600000 -500000 -400000 -300000 -200000 -100000 0 EU RO
NPV SENSITIVITY - DECREASE IN COST FOR PV AND BES
6 Discussion
Although many variants were modelled and simulated, combining different design choices in the different scenarios, it is emphasized once more that the focus throughout the analysis is put on the comparative nature of this study. In phase one, the technical and environmental KPI were analysed, i.e. the primary share of renewable energy and the operational CO2 emissions. It was
concluded that the ELEC and E&H-A3 scenarios appeared to be the most promising options regarding these two first KPIs. With both these systems using only PV on the rooftop, this follows the conclusion reached by Good et al. [16], stating that in their comparative study on PV, ST and PV/T systems, a system with only highly efficient PV modules was closest to reaching the zero-energy balance.
The results in Figure 8 showed that ELEC and E&H-A3 were able to reach a primary renewable energy share of roughly 30% to 34%. One reason why these values are not higher than they are is the fact the in both cases the systems are still taking a significant amount of electricity from the electric grid, which only has a yearly primary renewable energy share of roughly 15%. However, this share of renewable energy is varying strongly from day to day and hour to hour, and by matching the demand with moments in which the electric grid has a high renewable energy share, the performance regarding this first KPI could probably be improved. Furthermore, increasing the amount of electricity that could be produced locally through, for example, building-integrated PV, would probably enable ELEC and E&H-A3 to reach higher percentages in the share of renewable energy as well.
Looking at the potential of ELEC and E&H-A3 to reduce the operational CO2 emissions
compared to BAU, values of roughly 69% to 76% were shown by Figure 8. Despite falling short of the target of net-zero, this represents a very significant improvement. The main reason why both systems perform better for this second KPI, compared to the first one, has to do with the energy mix of Belgium’s electric grid. Although the yearly primary renewable energy share in the grid is only roughly 15%, about half of the grid’s electricity is supplied through Belgium’s nuclear power reactors. Therefore, although having a low share of renewable energy, the electric grid is quite clean, since nuclear energy is a low-carbon technology.
