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Data analysis and estimation of the conversion efficiency of bidirectional EV chargers using home energy management systems data 利用家庭能源管理系统数据分析和估算双向电动汽车充电器的转换效率

Smart Energy Pub Date : 2024-06-11 DOI: 10.1016/j.segy.2024.100145

Yumiko Iwafune, Toshiaki Kawai

{"title":"Data analysis and estimation of the conversion efficiency of bidirectional EV chargers using home energy management systems data","authors":"Yumiko Iwafune, Toshiaki Kawai","doi":"10.1016/j.segy.2024.100145","DOIUrl":"https://doi.org/10.1016/j.segy.2024.100145","url":null,"abstract":"<div><p>This study elucidates the authentic utilization of Vehicle-to-Home (V2H) system, a bi-directional DC charger for residential use and appraises power conversion losses incurred during V2H charging and discharging, utilizing data from commercial Home Energy Management Systems (HEMS). This approach offers the advantage of ascertaining operational efficiency within practical scenarios at a reduced cost relative to empirical data acquisition.</p><p>The empirical examination of results revealed that V2H households exhibited more frequent connections to the charger and engaged in more substantial charging activities compared to Charging-only households.</p><p>When estimating the power conversion efficiency in the context of V2H charging and discharging, a partial load efficiency curve was constructed for the input power of the V2H charger, thereby confirming that the peak efficiency closely approximated the nominal rated efficiency. These identified characteristics hold value for V2H system simulations. Furthermore, it was confirmed that a substantial standby power, ranging from 92 to 142 kWh per year, was generated when the V2H charger remained inactive in the sampled households. Additionally, the lack of reverse power flow to the external grid from the V2H system led to an observed increase in V2H partial load operation, resulting in a situation characterized by diminished conversion efficiency.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"15 ","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000157/pdfft?md5=82390c0545c91423a33d9116d8757b7c&pid=1-s2.0-S2666955224000157-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141325959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combining techno-economic modeling and spatial analysis for heat planning in rural regions: A case study of the Holbæk municipality in Denmark 将技术经济建模和空间分析相结合，促进农村地区的供热规划：丹麦霍尔拜克市案例研究

Smart Energy Pub Date : 2024-05-01 DOI: 10.1016/j.segy.2024.100144

Hyunkyo Yu , Claire Bergaentzlé , Stefan Petrović , Erik O. Ahlgren , Filip Johnsson

{"title":"Combining techno-economic modeling and spatial analysis for heat planning in rural regions: A case study of the Holbæk municipality in Denmark","authors":"Hyunkyo Yu , Claire Bergaentzlé , Stefan Petrović , Erik O. Ahlgren , Filip Johnsson","doi":"10.1016/j.segy.2024.100144","DOIUrl":"10.1016/j.segy.2024.100144","url":null,"abstract":"<div><p>This study examines the opportunities and challenges related to heat decarbonization in rural municipalities by applying a spatial analysis in combination with techno-economic modeling using TIMES. While the transition to low-carbon heating technologies is progressing in urban areas, this shift is happening more slowly in rural areas, reflecting a difference in decarbonization rate between urban and rural contexts. This study takes the Holbæk Municipality in Denmark as a case to investigate the potential for rural heating systems considering local fuels, excess heat, and investments in different energy infrastructures. The technology options investigated include both individual heating technologies, such as domestic boilers and heat pumps, and district heating. The modeling results demonstrate that use of excess heat from the municipal wastewater treatment plant and the neighboring industrial site for district heating competes with individual heating systems that have heat pumps and biogas-fueled boilers, where the mix depends on the conditions assumed for each technology and the heat demand density. The extent of district heating expansion differs between districts in the municipality, ranging from 14% to 100% depending on the heat demand density and proximity to the current district heating network. The different possibilities for the transition of the heating sector revealed in this work indicate that a successful transition will require both a clear policy for the heating sector and an explicit decarbonization strategy for the industries that can provide excess heat for district heating.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100144"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000145/pdfft?md5=8ad7fb235462313e34bd7cb210fd206f&pid=1-s2.0-S2666955224000145-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141054313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coordinating multiple Power-To-Gas plants for optimal management of e-fuel seasonal storage 协调多个 "电转气 "工厂，优化电子燃料季节性储存管理

Smart Energy Pub Date : 2024-05-01 DOI: 10.1016/j.segy.2024.100143

Emanuela Marzi , Mirko Morini , Costanza Saletti , Agostino Gambarotta

{"title":"Coordinating multiple Power-To-Gas plants for optimal management of e-fuel seasonal storage","authors":"Emanuela Marzi , Mirko Morini , Costanza Saletti , Agostino Gambarotta","doi":"10.1016/j.segy.2024.100143","DOIUrl":"10.1016/j.segy.2024.100143","url":null,"abstract":"<div><p>Seasonal storage is a key feature of future decarbonized energy systems with a high share of renewable energy integration. Power-to-Gas technologies represent a promising solution to enable such storage. They allow the conversion of surplus renewable electricity into e-fuels and their storage in the long-term. Their utilization enables the integration of the electrical, fuel and heating sectors, by converting electricity into fuels and recovering the waste heat from the process. Nevertheless, to design the most profitable management strategy for such systems, advanced control tools are required. This study introduces a novel control architecture for multiple multi-energy systems that share an e-fuel seasonal storage. Each energy system has its own short-term control logic, based on Model-Predictive Control (MPC), which manages day-ahead energy exchanges, while a long-term MPC controller considers yearly dynamics and the system as a whole. This gives additional constraints to the short-term controllers, which ensure the fulfillment of yearly goals. A multi-temporal and multi-spatial hierarchical control architecture is proposed, which enables optimal seasonal storage management, and its operation is verified in a Model-in-the-Loop configuration. The controller efficiently uses seasonal storage to balance seasonal mismatch between production and demand, resulting in higher utilization of renewable energy, lower emissions and costs.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100143"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000133/pdfft?md5=2d5a060c3b660f470bd07994c5e40fb6&pid=1-s2.0-S2666955224000133-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140793389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Developing energy system scenarios for municipalities - Introducing MUSEPLAN 为市政当局制定能源系统方案 - 引入 MUSEPLAN

Smart Energy Pub Date : 2024-05-01 DOI: 10.1016/j.segy.2024.100141

Rasmus Magni Johannsen , Peter Sorknæs , Poul Alberg Østergaard , Diana Moreno , Steffen Nielsen , Sara Abd Alla , Giorgio Bonvicini

{"title":"Developing energy system scenarios for municipalities - Introducing MUSEPLAN","authors":"Rasmus Magni Johannsen , Peter Sorknæs , Poul Alberg Østergaard , Diana Moreno , Steffen Nielsen , Sara Abd Alla , Giorgio Bonvicini","doi":"10.1016/j.segy.2024.100141","DOIUrl":"10.1016/j.segy.2024.100141","url":null,"abstract":"<div><p>The value of energy system scenarios is increasingly asserted in a decentralised and municipal context. There is, however, a lack of suitable tools for designing such scenarios, particularly tools that empower local planning practitioners in active participation. With this study, we introduce a novel tool designed specifically for municipal energy system modelling, thus bridging the gap between model developers and planning practitioners. The applicability and suitability of the new MUSEPLAN tool is investigated through its application in a case municipality, revolving around the needs of planning practitioners, supporting the build-up of modelling capacity, and focusing on the practical development of energy system scenarios. MUSEPLAN draws on the specialist simulation model EnergyPLAN but provides an environment for integrated design and comparison of multiple scenarios while reducing the complexity through discarding some of the more advanced options. In conclusion, MUSEPLAN resolves the identified challenges to the integration of energy system modelling in municipal energy planning, while simplifying the modelling and scenario evaluation process.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100141"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266695522400011X/pdfft?md5=35ef3471698eac85903c24feb542a88b&pid=1-s2.0-S266695522400011X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140764660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Water resiliency score – Is relying on freshwater to generate electricity a good idea? 水资源恢复能力得分 - 依靠淡水发电是个好主意吗？

Smart Energy Pub Date : 2024-04-18 DOI: 10.1016/j.segy.2024.100142

Javier Farfan , Alena Lohrmann , Henrik Saxén

{"title":"Water resiliency score – Is relying on freshwater to generate electricity a good idea?","authors":"Javier Farfan , Alena Lohrmann , Henrik Saxén","doi":"10.1016/j.segy.2024.100142","DOIUrl":"https://doi.org/10.1016/j.segy.2024.100142","url":null,"abstract":"<div><p>One commonly-used argument against fluctuating renewables is their unpredictability. In contrast, thermal power generation and hydropower are regularly presented as reliable and dispatchable. However, droughts and floods can render useless the share of the power generation infrastructure that directly depends on freshwater. In this work, the global power sector is analysed from an energy-water nexus perspective to evaluate its reliability in case of severe water scarcity on a per-power plant basis, proposing a new method for combining it with water stress scores. At a country level, known individual thermal and hydropower plants are paired with regional water stress projections from 2020 to 2030 and their water source as a bottom-up approach to account for the capacities at risk and identify the points where water dependence could render a power system unreliable. The results show that, globally, about 65 % of generating capacities are directly freshwater-dependent. Moreover, the share of capacities placed in the low-resiliency group increases from 9 % of the total installed in 2020 to over 24 % in 2030 in all scenarios. The findings could help guide the development of the global power sector towards a less water-dependent system and accelerate the deployment of low water-demand power generation technologies.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100142"},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000121/pdfft?md5=5469c75a318fe0808561af9c6537e615&pid=1-s2.0-S2666955224000121-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140641018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Can behavioral interventions optimize self-consumption? Evidence from a field experiment with prosumers in Germany 行为干预能否优化自我消费？来自德国消费者实地实验的证据

Smart Energy Pub Date : 2024-03-29 DOI: 10.1016/j.segy.2024.100140

Sabine Pelka , Anne Kesselring , Sabine Preuß , Emile Chappin , Laurens de Vries

{"title":"Can behavioral interventions optimize self-consumption? Evidence from a field experiment with prosumers in Germany","authors":"Sabine Pelka , Anne Kesselring , Sabine Preuß , Emile Chappin , Laurens de Vries","doi":"10.1016/j.segy.2024.100140","DOIUrl":"https://doi.org/10.1016/j.segy.2024.100140","url":null,"abstract":"<div><p>Aligning prosumers' electricity consumption to the availability of self-generated electricity decreases CO<sub>2</sub> emissions and costs. Nudges are proposed as one behavioral intervention to orchestrate such changes. At the same time, fragmented findings in the literature make it challenging to identify suitable behavioral interventions for specific households and contexts - specifically for optimizing self-consumption. We test three sequentially applied interventions (feedback, benchmark, and default) delivered by digital tools in a field experiment with 111 German households with rooftop-photovoltaics. The experiment design with a control-group, baseline measurements, and high-frequency smart-meter-data allows us to examine the causal effects of each intervention for increasing self-consumption. While feedback and benchmark deliver small self-consumption increases (3–4 percent), the smart changing default leads to a 16 percent increase for active participants. In general, households with controllable electric vehicles show stronger effects than those without. For upscaling behavioral interventions for other prosumers, we recommend interventions that require little interaction and energy literacy because even the self-selected, motivated sample rarely interacted with the digital tools.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100140"},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000108/pdfft?md5=af13be00b44e1736b90cb302361f5fdd&pid=1-s2.0-S2666955224000108-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140342275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep reinforcement learning based dynamic pricing for demand response considering market and supply constraints 基于深度强化学习的需求响应动态定价，考虑市场和供应限制因素

Smart Energy Pub Date : 2024-03-27 DOI: 10.1016/j.segy.2024.100139

Alejandro Fraija , Nilson Henao , Kodjo Agbossou , Sousso Kelouwani , Michaël Fournier , Shaival Hemant Nagarsheth

{"title":"Deep reinforcement learning based dynamic pricing for demand response considering market and supply constraints","authors":"Alejandro Fraija , Nilson Henao , Kodjo Agbossou , Sousso Kelouwani , Michaël Fournier , Shaival Hemant Nagarsheth","doi":"10.1016/j.segy.2024.100139","DOIUrl":"https://doi.org/10.1016/j.segy.2024.100139","url":null,"abstract":"<div><p>This paper presents a Reinforcement Learning (RL) approach to a price-based Demand Response (DR) program. The proposed framework manages a dynamic pricing scheme considering constraints from the supply and market side. Under these constraints, a DR Aggregator (DRA) is designed that takes advantage of a price generator function to establish a desirable power capacity through a coordination loop. Subsequently, a multi-agent system is suggested to exploit the flexibility potential of the residential sector to modify consumption patterns utilizing the relevant price policy. Specifically, electrical space heaters as flexible loads are employed to cope with the created policy by reducing energy costs while maintaining customers' comfort preferences. In addition, the developed mechanism is capable of dealing with deviations from the optimal consumption plan determined by residential agents at the beginning of the day. The DRA applies an RL method to handle such occurrences while maximizing its profits by adjusting the parameters of the price generator function at each iteration. A comparative study is also carried out for the proposed price-based DR and the RL-based DRA. The results demonstrate the efficiency of the suggested DR program to offer a power capacity that can maximize the profit of the aggregator and meet the needs of residential agents while preserving the constraints of the system.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100139"},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000091/pdfft?md5=1d534f2342596c403bc6386d5fedd0aa&pid=1-s2.0-S2666955224000091-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140328592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning-based energy monitoring method applied to the HVAC systems electricity demand of an Italian healthcare facility 将基于机器学习的能源监测方法应用于意大利一家医疗机构的暖通空调系统用电需求

Smart Energy Pub Date : 2024-03-21 DOI: 10.1016/j.segy.2024.100137

Marco Zini, Carlo Carcasci

{"title":"Machine learning-based energy monitoring method applied to the HVAC systems electricity demand of an Italian healthcare facility","authors":"Marco Zini, Carlo Carcasci","doi":"10.1016/j.segy.2024.100137","DOIUrl":"https://doi.org/10.1016/j.segy.2024.100137","url":null,"abstract":"<div><p>The buildings energy consumption is a great part of Europe's overall energy demand. The development of diagnostic methods capable of promptly alerting users in case of issues (e.g. mild and progressive decrease in systems components performance) is crucial for the smart management of buildings. Machine learning-based building energy monitoring is a reliable approach for identifying subtle anomalies in the building energy demand behaviour. This study presents the application of a systematic procedure to develop a reliable monitoring method based on machine learning predictive models, ensuring minimal user knowledge requirements. The proposed method applied to the electricity demand of various components of the heating, ventilation and air conditioning system of a real Italian healthcare facility. The obtained models are exploited to apply the building energy monitoring method, assessing its capability to highlight mild changes in building energy demand behaviour. Considering that its application on specific system components implies an increased technical and economic effort to carry out data collection, the present work is aimed at assessing the benefits of such applications. Because of its high reproducibility and relatively simple integration into centralized building energy management systems, the proposed method offers a practical solution to enhance the smart management of building energy systems.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100137"},"PeriodicalIF":0.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000078/pdfft?md5=336dcc41f4fd95bc4b8d96d4d0ae999a&pid=1-s2.0-S2666955224000078-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140208969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The role of social learning on consumers’ willingness to engage in demand-side management: An agent-based modelling approach 社会学习对消费者参与需求方管理意愿的影响：基于代理的建模方法

Smart Energy Pub Date : 2024-03-20 DOI: 10.1016/j.segy.2024.100138

Sara Golmaryami, Manuel Lopes Nunes, Paula Ferreira

{"title":"The role of social learning on consumers’ willingness to engage in demand-side management: An agent-based modelling approach","authors":"Sara Golmaryami, Manuel Lopes Nunes, Paula Ferreira","doi":"10.1016/j.segy.2024.100138","DOIUrl":"https://doi.org/10.1016/j.segy.2024.100138","url":null,"abstract":"<div><p>Achieving a sustainable energy future requires a clean, affordable energy supply and active consumer engagement in the energy market. This study proposes to evaluate and simulate energy consumers' willingness to participate in demand-side management programs using an agent-based modelling approach to address the social learning effect as a key factor influencing energy consumer behaviour. The proposed agent-based model simulates households' electricity consumer interactions examining how the willingness to shift electricity usage is encouraged through the social environment, while accounting for the diversity among consumers. Data from a survey conducted in Portugal, including questions about the influence of recommendations from friends or family members on individuals' willingness to engage in demand response activities, are used to test the proposed simulation. The findings reveal that social learning significantly impacts demand response acceptance, yet the extent of this influence varies depending on the socio-economic characteristics of households’ electricity consumers. The study confirms agent-based model as an effective approach for capturing social dynamics and supporting electricity market decision making, providing valuable insights for devising consumers engagement strategies.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100138"},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266695522400008X/pdfft?md5=581ba3b8b8a53c88b92aa0c9f3750084&pid=1-s2.0-S266695522400008X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140309956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blended finance as a catalyst for accelerating the European heat transition? 混合融资是加速欧洲供热转型的催化剂？

Smart Energy Pub Date : 2024-03-19 DOI: 10.1016/j.segy.2024.100136

Tobias Popovic , Kristina Lygnerud , Ilka Denk , Nathalie Fransson , Burcu Unluturk

{"title":"Blended finance as a catalyst for accelerating the European heat transition?","authors":"Tobias Popovic , Kristina Lygnerud , Ilka Denk , Nathalie Fransson , Burcu Unluturk","doi":"10.1016/j.segy.2024.100136","DOIUrl":"10.1016/j.segy.2024.100136","url":null,"abstract":"<div><p>Against the background of accelerating climate change, this paper examines to which extent sustainable infrastructure finance can effectively contribute to the European heat transition as a part of a “Great Transformation” towards a climate neutral economy and society. Since the building sector is responsible for approximately 35% of the EU's carbon footprint, district heating and cooling networks can provide an efficient technology for decarbonizing the energy supply of buildings. New district heating and cooling networks technology allows for heat and hot water generation that is combustion free. A large-scale role-out of this infrastructure would require hundreds of billions EUR of investments within the next few years. In view of the high public debt, the public sector will not be able to finance the required investment volumes. Against the background of regulatory changes, such as the EU Action Plan on Financing Sustainable Growth, this paper examines in which way financial markets participants might be able to fill the funding gap. A particular focus lies on blended finance, since related instruments reduce investors' risks, esp. in early stages of the infrastructure lifecycle. Due to an improved risk-return-relationship this makes the investment more attractive to private investors. It is also essential for investors to understand the kind of business model they invest in. Therefore, we discuss the importance of key performance indicators in the four dimensions that are relevant for the investors' decision-making process: return, risk, liquidity and sustainability. With respect to the sustainability dimension, we elaborate on the relevance of EU-Taxonomy-aligned district heating and cooling networks' construction and operation.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"14 ","pages":"Article 100136"},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000066/pdfft?md5=173cc47e4ed220f437c22b1293c182e5&pid=1-s2.0-S2666955224000066-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140267956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0