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Market policies play a crucial role in facilitating the transition to a low-carbon society by restructuring the electricity market and influencing stakeholder behavior. Policymakers are concerned with how to implement these policies in terms of their intensity, combination, and timing. However, existing research lacks effective simulation tools that can accurately capture the impact of market policies on individual decision-making in the electricity sector, which is essential to represent the complex impacts of the policy mix. To address this gap, we present an agent-based model for analyzing the Low Carbon Transition (LCT) in the electricity sector. Using the Japanese electricity sector as a case study, we design various subsidies, incentives, and liberalization policy scenarios to evaluate the role of market policies in facilitating LCT. We observed that, within the Feed-in Premium (FIP) system, above a subsidy threshold of 2 JPY/kWh or 20% of the electricity cost leads to overcompensation, resulting in a stagnation of LCT promotion. To address this stagnation, it is imperative to not only enhance demand-side incentives, such as carbon taxes but also expedite the advancement of the free trade market to prevent market-induced stagnation. A synergistic implementation of these three policies is crucial for the most efficient progression of LCT., QC 20240503

Buildings consume significant energy worldwide and account for a substantial proportion of greenhouse gas emissions. Therefore, building energy management has become critical with the increasing demand for sustainable buildings and energy-efficient systems. Simulation tools have become crucial in assessing the effectiveness of buildings and their energy systems, and they are widely used in building energy management. These simulation tools can be categorized into white-box and black-box models based on the level of detail and transparency of the model’s inputs and outputs. This review publication comprehensively analyzes the white-box, black-box, and web tool models for building energy simulation tools. We also examine the different simulation scales, ranging from single-family homes to districts and cities, and the various modelling approaches, such as steady-state, quasi-steady-state, and dynamic. This review aims to pinpoint the advantages and drawbacks of various simulation tools, offering guidance for upcoming research in the field of building energy management. We aim to help researchers, building designers, and engineers better understand the available simulation tools and make informed decisions when selecting and using them., QC 20240208

Modern heat pump systems often come equipped with sensors, enabling the collection of substantial operational data. However, many residential heat pumps installed in preceding decades lack pressure sensors, energy meters, or mass flow meters, primarily due to financial limitations. As a result of these incomplete measurements, the direct analysis of the heat pump system’s performance or the leveraging of the amassed data for inventive applications like prognosticating energy consumption, detecting and diagnosing faults, and implementing intelligent control becomes challenging.In existing literature, the focus of soft sensors in heat pump systems has been on estimating a single parameter. This approach, however, overlooks the reality that multiple parameters are often missing due to the lack of all-encompassing physical meters and sensors. Furthermore, current soft sensor models are typically developed using inputs such as compressor power consumption, pressures, evaporation, and condensation temperatures. These inputs, unfortunately, tend to be inaccessible within existing heat pump monitoring installations.In practice, it is a challenge to compensate for several critical measurements, encompassing mass flow rate, pressures, power consumption, and heating capacity, by using only commonly available sensors such as secondary loop temperatures and compressor frequency are available. Currently, there is a notable gap in research concerning this practical issue.To address the problems associated with inadequate measurements, this study presents the development and validation of soft sensors based on a data-driven approach, which can compensate for the parameters often unavailable with data collected from a limited number of commonly used sensors. Each component model employs a multivariate polynomial regression that calculates the evaporation temperature, condensation temperature, mass flow rate, and compressor power consumption, respectively. Subsequently, we present an, QC 20240906

As the transition away from fluorinated refrigerants occurs due to F-gas and PFAS regulations, heat pumps face the challenge of adapting to new non-fluorinated refrigerants. Evaluating heat pump performance during this transition is challenging due to limited operational data on the new refrigerants. Conducting long-term tests to fully understand a heat pump’s performance with all possible refrigerants is labor-intensive and economically burdensome. This study introduces two complementary reduced-parameter models to assess heat pump performance across multiple new natural refrigerants despite limited data. A transfer learning model, leveraging knowledge from existing data-rich refrigerants, has been developed to evaluate the performance of heat pumps using new, data-scarce natural refrigerants. However, due to the lack of transparency in transfer learning models, semi-empirical models are being developed in parallel. The semi-empirical models, across multiple natural refrigerants, are capable of analyzing the thermodynamics and heat transfer processes within the heat pump system by utilizing only limited easy-to-measure variables as inputs. The transfer learning model demonstrates high accuracy for all outputs across seven refrigerants with RRMSE all below 7%. In comparison, the semi-empirical models are less accurate, with RRMSE results under 25% for all parameters except compressor power. By integrating these two models, a comprehensive framework is established for assessing heat pump performance with both high accuracy and a deeper understanding of the system., QC 20240906

Social sustainability requires both technological innovations and societal changes within energy systems, with decentralization playing a critical role. This shift emphasizes the increasing importance of individual user decision-making, posing significant management challenges. An individual’s environmental awareness has a key influence on their energy decisions. However, the relationship between individual environmental awareness and social sustainability, particularly from a systemic perspective, remains underexplored. Our study uses agent-based modeling to examine this relationship within Japan’s electricity market, focusing on social learning and consumer heterogeneity. We find that social learning leads to the formation of consumer clusters with specific electricity preferences, affecting environmental awareness differently across high- and low-carbon groups. This process reveals the nuanced role of social learning in promoting low-carbon technology adoption, which varies according to the market share of low-carbon energy. Additionally, our results suggest that initial heterogeneity in environmental awareness among consumers has a limited and varied effect on sustainable transition pathways. However, the diversity resulting from social learning significantly shapes these trajectories. These insights highlight the complex interplay between individual behaviors, societal dynamics, and technological advancements in steering the sustainable transition, providing valuable considerations for future energy system management., QC 20240925

The study investigated the characteristics of different natural refrigerants and their mixtures in a residential heat pump with low refrigerant charge. Three main evaluation criteria were utilized for comparing different mixtures: Coefficient of Performance (COP), Volumetric Heating Capacity (VHC), and a newly proposed indicator, the heating capacity at charge limit. Propane was used as a reference refrigerant. It was found that some mixtures significantly improved both COP and the heating capacity at charge limit while maintaining similar volumetric heating capacity and operating conditions. Alternative multi-criteria decision-making techniques were adopted to rank the best refrigerant mixtures. Mixtures rich in Dimethyl Ether (DME), such as DME-CO2 [0.96-0.04] and DME-Propylene [0.75-0.25] were found consistently among the best options. Those were followed by Propylene-rich mixtures such as Propylene-CO2, Propylene-Isobutane and Propylene-Butane. The levelized cost of heat (LCOH) could be improved by up to 12 %. To accelerate the transition to natural refrigerants, without compromises on efficiency and costs, further research and certification activities on non-fluorinated refrigerants based on Dimethyl Ether (R-E170), CO2 (R-744) and Propylene (R-1270) are recommended., QC 20240620

This study empirically investigates the optimal design features of photovoltaic-thermal (PVT) collectors for integration with ground source heat pump (GSHP) systems, considering technical and economic factors. Outdoor experiments are conducted in Stockholm, Sweden, comparing five unglazed and uninsulated PVT collector designs a) Reference Sheet & Tube b) Sheet & Tube with a narrow air gap between PV and absorber plate c) Box-channel polypropylene d) Finned tube and e) Box-channel aluminum with fins at operating temperatures below ambient. The findings indicate that the box-channel aluminum design with fins, characterized by a superior combination of high zero-loss efficiency and a high U-value, emerges as the ideal PVT design for integration with ground source heat pumps, taking into account both technical and economic considerations. Despite having a relative specific thermal cost 9% higher than the reference collector, this design demonstrates the capability to generate 2,096 kWh/(m2a) of thermal energy, marking an 83.3% increase compared to the reference, with a 136% higher energy-to-mass ratio., QC 20240617

International Energy Agency predicts that the global number of installed heat pumps (HP) will increase from 180 million in 2020 to approximately 600 million by 2030, covering 20% of buildings heating needs. Electric power consumption is one of the main key performance indicators for the heat pump systems from techno-economic perspective. However a common issue prevalent in many existing heat pumps is the lack of electric power measurement. The modern installations might be equipped with electric power measurement sensors but this comes at a higher system cost for the manufacturers and end-users. The primary objective of this work is to propose a virtual measurement for estimating power consumption, thereby eliminating the need for field measurement of power for heat pumps. To achieve the objective, a data-driven approach is proposed. Firstly, the in-situ data is preprocessed through data merging, cleaning, and normalization. Then, input features are pre-selected using Spearman correlation coefficients, and further refined by addressing multicollinearity problem. Following this, Extreme Gradient Boosting (XGBoost) models and polynomial models are developed by considering different features as inputs. All models are finally validated against the in-situ data from multi-units of ground source heat pump (GSHP) and air source heat pump (ASHP) installations. The results showed that the electric power consumption of GSHP can be estimated with high accuracy (99% for R2, 10 W for MAE, and 1% for MAPE) through generic data-driven models using only four easy-to-measure input features. Taking three input features as inputs for ASHP generic model, the accuracy can be reached to 83% for R2, 125 W for MAE, and 9% for MAPE. The method presented in this paper can be applied to estimate power consumption of millions of heat pumps and consequently add a significant value as well as provide different types of services, such as cost-saving benefits for manufacturers and end-users, flexi, QC 20231115

The development of smart sensors, low cost communication, and computation technologies enables continuous monitoring and accumulation of tremendous amounts of data for heat pump systems. But the measurements, especially for domestic heat pump, usually suffer from incompleteness given technical and/or economic barriers, which prevents database of measurements from being exploited to its full potential. To this end, this work proposes a data-driven soft sensor approach for compensating multiple missing information. The soft sensors are developed based on an ANN model, an integrated multivariate polynomial regression model and empirical model by considering different constrains like data and information availability during model establishing process. All the three models have been validated against the data from a field test installation, and showed good performance for all the compensated variables. Of the three models, the ANN model shows the best performance for all soft sensors, but it has the highest requirement for additional resources to collect training data. While the integrated multivariate polynomial regression model demonstrates excellent accuracy for the majority of soft sensors with manufacturers' subcomponent data which needs no extra cost. Even though empirical model is not as accurate as the other two models, it still performs good accuracy with limited information from performance map. The methods developed in the present study paves the way for available measured data in thousands of installations to be fully utilized for innovative services including but not limited to: improved heat pump control strategies, fault detection and diagnosis, and communication with local energy grids., QC 20230309

The evolution of a society is inextricably linked to technological transition, which is based on both innovation and dissemination of technologies. To protect the vulnerable new generation of technology, government subsidies are one of the most common and effective tools. However, not all subsidy policies can lead to a healthy development of market shares. Subsidy fraud is one of the most problematic issues that can arise under an imperfect system. This paper identifies an interesting subsidy fraud like phenomenon via a validated agent-based model. After analysing the mechanism of the transition of technology in the model, we drive the condition upon which subsidy fraud could occur., QC 20220420Part of proceedings ISBN 978-989-758-547-0

Buildings provide an ideal platform for solar photovoltaics (PV) towards sustainable development goals, and the decision to invest in PV lies predominantly with building owners. Information delivery is critical for the diffusion of innovations, and this study aims to improve the quality of information for household PV investors in Sweden. A User Journey Mapping approach is applied with a combination of semi-structured interviews and a review of online solar calculators. The results show that despite a rapid growth in the quantity of information there is still a gap between demand and supply due to the lack of clarity and trustworthiness of information. This is clearly demonstrated in the review of online calculators, which show a high variance in results. Payback time, for example, ranged from 7 to 18 years for a single test case. The information gap can be closed by creating neutral, non-commercial online information sources that focus on transparency and education where household investors can validate supplier offers and analyses. The PV industry risks eroding trust in the market, which will likely slow adoption by the early majority and hinder sustainability goals., QC 20220301

Heat pumps and water tanks can be used to increase PV self-consumption in buildings without any additional equipment, but there is sometimes a lack of economic incentives to maximize it that limits economic gains. Therefore, pricing conditions need to change in order to make self-consumption strategies more interesting for prosumers. This study aims at determining what, if any, unsubsidized market conditions could lead to economically motivated self-consumption control strategies with solar heat pumps. A sensitivity analysis is used on multiple pricing models based on current market conditions for a solar PV and ground source heat pump system for a single-family house in Norrköping, Sweden. The results show that control strategies aimed at maximizing self-consumption have very little impact on net costs, regardless of pricing model or variation in price. Feed-in-bonus is the most important aspect when comparing different pricing schemes, and no other sensitivity comes close., QC 20230802

With the increasing amount of building renovations in Austria, the potential increases for replacing conventional national gas heating systems with heat pumps (HP) and thereby reduce CO2 emissions particularly when combined with solar photovoltaics (PV). The Austrian subsidization scheme for HP and PV systems are different for every state, creating confusion and inconstancy for potential adopters. This study provides a parametric technoeconomic analysis of PV + HP systems to identify the critical economic parameters on profitability and make policy recommendations. A case study in Vienna is modelled using demand from the Building Model Generator and black box efficiency models for the HP and PV simulated with hourly time steps. The results show that both air-source and ground source heat pumps are currently profitable with PV under current subsidy schemes. The benefit-to-cost ratio (BCR) is highly influenced by capital costs and subsidies, however natural gas prices have the greatest influence. Increasing natural gas prices by 0.01 euro/kWh, or 17%, is enough to replace all other complicated subsidies for both HP and PV. This is equivalent to a carbon emissions price of 33 euro/ton and could result in a reduction of CO2 emissions in multi-family houses by approximately 45%-60%., QC 20210818

What commonalities are there in sustainable or unsustainable heating practices in five high-income, high-emitting western European countries? What preferences do a nationally representative sample of the public in these countries hold towards low-carbon options? It is imperative that climate policy researchers and practitioners grapple with the difficulty of decarbonizing heat, which remains the largest single end-use service worldwide and which accounts about half of total final energy consumption. Based on a comparative assessment of five representative national surveys in Germany (N = 2009), Italy (N = 2039), Spain (N = 2038), Sweden (N = 2023), and the United Kingdom (N = 2000), this study explores the demographics and geography of household heat decarbonisation in Europe. By analyzing our country level data as well as our combined sample of 10,109 respondents, it investigates how people conceive of the purposes of low-carbon heat, their preferences for particular forms of heat supply, and their (at times odd) practices of heat consumption and temperature settings. Grounded in its original data, the study organizes its findings inductively across the five themes of literacy (heating knowledge, awareness and control), sustainability (heating practices, dynamics and conflicts), temperature (heating satisfaction and preferences), desirability of change (low-carbon heating priorities, business models and trust), and culture (country and national variation). The study also explores intersections between these dimensions, using multivariate analysis, as well as how preferences differ according to varying types of actors as well as geography and space., QC 20210329

Low-carbon transitions are long-term complex processes that are driven by multiple factors. To provide a theoretical and practical framework of this process, we argue that the combination of the multi-level perspective (MLP) and agent-based modeling (ABM) enables us to reach a deeper and detailed analysis of low-carbon transitions. As an extensively applied theoretical form, MLP conceptualizes low-carbon transitions as a nonlinear process and allows a system to be analyzed and organized into multiple dimensions (landscape, regime, and niche). However, MLP cannot explain the many details of complex transitions, whereas ABM can estimate the influence of interacting behaviors in a complex system. Therefore, the main advantages of the combined approach for the analysis of low-carbon transition are verified: the MLP can contribute to the overall design of ABM, and ABM can provide a dynamic, continuous, and quantitative description of the MLP. To construct this combination framework, this paper offers a guiding principle that combines the two perspectives under a low-carbon transitional background to create an integrated strategy using three procedures: defining the common concepts, their interaction, and their combination. Through the proposed framework, the goal of this work was to reach a better understanding of social system evolution from the present high-carbon state to a low-carbon state under the pressure of ambitious climate goals, providing specific policy recommendations., QC 20201127

This paper aims to contribute by presenting calculated and measured electricity usage in two single-family case studies during the heating season of 2019-2020 located in Stockholm, Sweden. The electricity usage included consumption by heat pumps’ compressor to cover space heating and domestic hot water, auxiliary energy for fans and pumps, and ventilation system. The first case study was built in 1936 with an oil burner, which was renovated to a ground-source heat pump (GSHP) in 2015, and the second case study was a new building built in 2013 with a GSHP. The application of photovoltaic/thermal (PVT) systems in combination with GSHP was theoretically investigated for both case studies. Buildings were modelled using the energy simulation tool IDA Indoor Climate and Energy (ICE), and the model was validated against the measured electrical energy usage. PVT was designed to balance the maximum heat production with domestic hot water consumption during the summer months. Simulation results revealed that combining GSHP with 5 m2 grid-connected PVT gave 21% and 22% energy savings in case study 1 and case study 2, respectively. Employing a battery storage to store extra electricity production by PVT increased the energy savings to 24 % and 32 % for case study 1 and case study 2, respectively. Moreover, in both cases approximately half of the total annual domestic hot water need was prepared by 5 m2 PVT., QC 20200821

Fossil fuel based building space heating and cooling contribute to more than 10% total final energy consumption in China. Consequent carbon dioxide and air pollutants emissions bring about atmospheric pressure and associated respiratory diseases. Seawater heat pumps as a candidate sustainable building space heating and cooling solution can alleviate such environmental pressure since China has a long coastline and many coastal cities have the possibility for seawater heat pump implementation. However, stakeholders are still suffering from insufficient understanding of seawater heat pumps feasibility in different coastal cities of China from techno-economic, environmental and geographical perspectives. This paper proposes a systematic method to evaluate seawater heat pump potential in different locations of China considering various local spatial parameters in the source and sink side of the energy system. A key performance indicator system is introduced to quantitatively analyze the relative advantages and disadvantages of applying seawater heat pumps compared with status-quo systems. Quantitative evaluation results show that seawater heat pumps have a higher potential in north Chinese coastal cities from techno-economic point of view when compared with existing heating and cooling systems. Environmentally, seawater heat pumps have to reach a critical seasonal coefficient of performance value to guarantee its potential in carbon emissions saving. In south Chinese coastal cities, seawater heat pumps have to reach a more satisfactory system efficiency and a more competitive system cost in order to exploit its full advantages over status-quo systems from techno-economic perspectives. Environmentally, seawater heat pumps are more attractive than competing technologies in south cities. Also, north Chinese cities are geographically more feasible for seawater heat pumps applications compared with south cities., QC 20200103, STINT - NSFC

Within the heat pump sector, there are applications where photovoltaic/thermal (PVT) collectors can offer greater value with lower investment costs than the current alternatives. The first is ground source heat pumps (GSHP) with under dimensioned boreholes. The second is a solar source heat pump (SSHP) where the PVT collectors are a replacement for the traditional air heat exchanger in an air source heat pump (ASHP). Complete systems models for a multi-family house are simulated in TRNSYS to determine seasonal performance factors (SPF), which are then compared technically and economically to each respective alternative. A 156 m(2) PVT array is capable of improving the SPF of a degraded GSHP by 30%, the same gains as drilling additional boreholes but at a lower cost. The SSHP with a 235 m(2) PVT array can reach an SPF of 2.6, comparable to the performance of an ASHP, but has the cost of a GSHP. Already today, PVT can economically compete with borehole drilling for GSHP and the SSHP concept shows enough market potential to warrant investment and development towards broader adoption., Part of ISBN 978-3-9820408-2-0QC 20230921

The electrification of buildings is a promising pathway to the decarbonization of cities. This is a parametric study of the technical and economic performance of ground source heat pump (GSHP) systems with series connected solar PV/thermal (PVT) collectors. The focus is on multi-family houses (MFH) in the heating dominated climate of Sweden, where land restrictions for boreholes or noise restrictions on air heat exchangers limit the heat pump market. System efficiency and lifecycle cost results are generated using a holistic and detailed systems model in TRNSYS with 20 year simulations. The results show that PVT can reduce borehole length by 18% or spacing by 50% while maintaining an equivalent seasonal performance factor to systems without PVT. The cost for PVT + GSHP systems is higher than a traditionally designed PV + GSHP, however this does not take into account the value of the land area saved by PVT, which can be up to 89%. The reduction in land enabled by PVT has the potential to increase penetration of GSHP in MFH and promote solar energy diffusion in high latitude markets., QC 20191118

Fast urbanization process and promotion of life standard in China requires a great amount of energy input in building heating sector. North China now faces challenges of upgrading existing fossil fuel based high emission district heating systems into more environmental friendly heating systems. South China is discussing to choose proper building heating solutions for new and existing buildings which lack proper heating facilities. Renewable heating technologies such as ground source heat pump and air source heat pump are candidates to upgrade traditional heating solutions such as fossil fuel boilers and electric heaters. In order to find the most feasible building heating solution for different geolocations of China, this paper proposes a spatial data based techno-economic and environmental analysis methodology to fulfill such research gap. Case studies are carried out in two selected cities by using proposed methodology. Evaluation model shows that, heat pumps is quite competitive in south China compared with electric heaters, whereas in north China heat pumps have to reach several preconditions to be competitive with coal boiler district heating system under current techno-economic and environmental situations. In north China, a heat pump should reach a minimum seasonal coefficient of performance of 2.5-3.7 (for ground source heat pump) or 2.7-3.0 (for air source heat pump) to become CO2 and PM2.5 emission neutral as well as economically competitive compared with coal boiler district heating system. The advantage of proposed methodology is its simplicity in execution and could be repeated to other areas as the data required are available., QC 20181217

As the demand for sustainable energy technologies grows, solar photovoltaics (PV) and heat pumps are increasingly being used in buildings. Hybrid PV-thermal (PVT) collectors have been researched for decades, but have not yet had success in the market. This study combines PVT and ground source heat pumps (GSHP) in a series connection for a multi-family house, and compares the technical and economic performance to GSHP and PV+GSHP systems. A complete systems model in TRNSYS is used for the solar heat pump system, and climate and economic boundary conditions come from the Swedish market. The results show that reducing the borehole length and/or spacing with no or a limited loss of efficiency is the greatest benefit of adding PVT, however a fully sized borehole field with PV is found to be the lowest cost design option. In systems with poor efficiency and high auxiliary boiler use, the addition of PVT can be the lowest cost option but is not preferable to the PV+GSHP when space is not a limitation. The reduction in borehole field area for a given heat pump efficiency is notable since many multi-family homes cannot install GSHP due to a lack of drilling space. PVT+GSHP systems could offer a new, low-carbon heating alternative for buildings previously outside of the heat pump market., QC 20190812

Photovoltaic-thermal (PVT) collectors are commonly designed for use in domestic hot water systems, however it can be interesting to incorporate them into ground source heat pump (GSTIP) systems. Because of the historically narrow use case, many PVT models are created with a collection of assumptions which may not apply to novel collectors designed for use in PVT+GSHP systems. The aims of this study are to review existing PVT collector models for use in TRNSYS, identify any potential error sources, and test for possible improvements. Type 560 is found to be the most promising theoretical model, however two potentially limiting features are identified; the radiation absorption model and the confinement to sheet-and-tube configurations. The absorption is tested using a recreation of Type 560 in Matlab where two alternative models developed specifically for PV modules are compared. The results show a marked increase in power during low angle, low light hours, and a 14.36% increase in electrical energy and a 10.91% for the thermal energy over the course of a day with one of the models. Collector geometry is tested by creating a ID model in EES and comparing it to several geometries in Type 560. A method of packing as many tubes as possible together is shown to give comparable results as the ID model. The results of these simulations will be compared with empirical data from currently ongoing testing., QC 20190208

The market for solar photovoltaic systems is growing rapidly into a mature industry, while at the same time policies which have spurred the growth (e.g. feed-in tariffs or net metering) are beginning to fade away. These policies made techno-economic studies relatively simple for engineers, analysts, and owners, however investing in a deregulated market requires more advanced tools than the traditional engineering economics which dominate the literature. The objective of part one in this paper is to catalogue and critique the range of methods and models relevant to techno-economic analysis for PV systems in the context of distributed, grid-connected buildings. This is accomplished by; developing a system modeling framework for prosumer PV investment analysis, reviewing relevant energy, economics, and finance literature to identify mathematical models which can be applied, and cataloging the use of the reviewed techniques in the relevant literature. Also included is a qualitative discussion of the benefits and practicality of the review techniques, where Monte Carlo analysis is highlighted as an exemplary method. This review is useful as a reference for analysts, researchers, and engineers developing PV integration solutions for building energy systems in a post early adopter PV market., QC 2017-06-12

Part One in this two part paper identified Monte Carlo analysis as an improved approach over traditional deterministic techno-economic methods for solar PV prosumers in deregulated markets. In this paper a novel Monte Carlo methodology is described and demonstrated through a case study for the Swedish residential sector, which includes a review of relevant market, climate, and policy conditions, their use in determining inputs, and the probabilistic results. The probability of profitability (PoP) is introduced as an indicator in conjunction with result distributions. The results show that under current policy conditions, Swedish PV investors with well positioned buildings have a 71% chance of making a 3% real return on investment, and virtually no chance of losing their original investment. Without subsidies the PoP drops to 8%. In none of the simulated cases was any of the original investment lost. The PoP is most sensitive to the capital subsidy and the uncertainty of market based, long-term support is less critical to the chances of a successful investment. Given the current market conditions, Swedish PV prosumers can expect a return on investment. The decision to install will also depend on the probability of achieving their desired profitability, which Monte Carlo analysis quantifies well., QC 2017-06-12

This paper presents and demonstrates a methodology to explore the flexibility of a heat pump pool. Three points are in the focus of this work: First the procedure to model a pool of residential heat pump systems. Second the study of the response of a large number of heat pumps when the Smart-Grid-Ready interface is used for direct load control. Third a general assessment of flexibility of a pool of heat pump systems. The presented pool model accounts for the diversity in space heating and domestic hot water demands, the types of heat source and heat distribution systems used and system sizing procedures. The model is validated using field test data. Flexibility is identified by sending trigger signals to a pool of 284 SG-Ready heat pumps and evaluating the response. Flexibility is characterized by maximum power, shiftable energy and regeneration time. Results show that flexibility is highly dependent on the ambient temperature and the use of an electric back-up heater. It is found that using SG-Ready-like signals offers significantly higher flexibility than just switching off heat pumps, as it is mostly done today., QC 20170308

In the last five years the costs of photovoltaic systems have decreased considerably making it economically attractive to generate electricity locally. In many countries, self-consumption is the most attractive option to make use of the generated electricity. Variable speed heat pumps - if controlled properly - can take a share of the PV electricity to decrease costs and CO2 emissions for heat generation and increase PV self-consumption. This paper discusses a control strategy that uses real-time smart meter readings and adjusts the compressor speed to adapt heat pump electricity consumption depending on the available PV power. The approach is tested in a detailed building simulation. Self-consumption can be increased by 6% compared to a heat driven control. For the chosen PV size of 10kWp in a German multi-family house, an increase of storage size shows only little possibility for a further increase in self-consumption., QC 20200910

The present paper, as the first part of two, suggests a method to approach the challenge of capacity control in Ground Source Heat Pumps (GSHP). The paper describes the development of a model of the system which includes several sub-models such as the heat pump unit, building, ground source, thermal storage tank, auxiliary heater, and climate. The developed computer model can be used for comparative analysis of different control methods and strategies aiming at the improvement of the system seasonal performance. With this model, on/off controlled and variable capacity GSHPs, with a single speed or variable speed pumps in the systems, can be evaluated in a wide range of operating conditions and more energy efficient methods of the system control can be found. The computer model is developed in the two environments EES and TRNSYS utilizing so-called co-solving technique., QC 20110927

QC 20240906

QC 20240906

QC 20240906

QC 20240906