Community Energy Systems Research Articles

Energy security in community energy systems: An agent-based modelling approach

In community energy systems, the energy demand of a group of households is met by collectively generated electricity and heat from renewable energy sources. What makes these systems unique is their collective and collaborative form of organization and their distributed energy generation. While these features are crucial to the resilience of these systems and are beneficial for the sustainable energy transition in general, they may at the same time undermine the security of energy within these systems. This paper takes a comprehensive view of the energy security of community energy systems by considering dimensions such as energy price, environment and availability, which are all impacted by decentralized and collective means of energy generation and distribution. The study analyses community energy systems' technical and institutional characteristics that influence their energy security. An agent-based modelling approach is used for the first time to study energy security, focusing on thermal energy communities given the considerable share of thermal energy applications such as heating, cooling, and hot tap water. The simulation results articulate that energy communities are capable of contributing to the energy security of individual households. Results demonstrated the substantial potential of energy communities in CO2 emissions reduction (60% on average) while being affordable in the long run. In addition, the results show the importance of project leadership (particularly regarding the municipality) concerning energy security performances. Finally, the results reveal that the amount of available subsidy and natural gas prices are relatively more effective for ensuring high energy security levels than CO2 taxes.

Collaborative Renewable Energy Generation among Industries: The Role of Social Identity, Awareness and Institutional Design

Like many other sectors, climate change strategies have put various restrictions on industry, the most prominent one being caps on CO2 and other energy-related emissions. At the same time, and especially in many developing economies, the industry struggles with an increasing gap between the fast development of the sector and lagging energy supply capacity. Collective generation of renewable energy is seen as a promising means of transition, next to other forms of renewable energy generation (centralised, individual). The aim of this research is to investigate factors influencing willingness to participate in Industrial Community Energy Systems (InCES). Using existing literature on Industrial Symbiosis and Community Energy Systems, we formulate plausible hypotheses on the most relevant factors for the willingness of industries to join such initiatives. As one of the largest and most diversified industrial clusters in Iran, Arak industrial park is selected as the case study. Data were collected from the CEOs of 96 companies through survey research. Our results highlight the crucial role of awareness about the benefits of renewable power generation in an InCES. Social identity among industries and trust between them are also determining factors for their willingness to join InCES. Finally, proper institutional design for overcoming the partnership complexities (e.g., conflict resolution) was highlighted as a crucial factor for industries. It can be concluded from the results of this study that policymakers should avoid one-size-fits-all incentive design approaches and reach out to larger companies with targeted incentives, introduce specially designed bank loans for different target groups, and make use of consulting companies as intermediaries to increase the awareness of the industries regarding the benefits of investing in an InCES.

Delivering an off-grid transition to sustainable energy in Ethiopia and Mozambique

BackgroundOff-grid and decentralized energy systems have emerged as an alternative to facilitate energy access and resilience in a flexible, adaptable way, particularly for communities that do not have reliable access to centralized energy networks both in rural and urban areas. Much research to date on community energy systems has focused on their deployment in Europe and North America. This paper advances these debates by looking at how community energy systems can support energy transitions in Africa. Specifically, it asks: what role can community energy systems play in the energy transition in East and Southern Africa?ResultsThis article investigates the potential for community energy to foster sustainable and just energy transitions in two countries in East and Southern Africa, namely Ethiopia and Mozambique. To do so, it explores transformations in Ethiopia and Mozambique’s energy systems through the lens of energy landscapes. This concept enables us to situate energy transitions within recent developments in energy governance and to understand current and future possibilities for change through the involvement of communities that currently lack access to reliable and clean energy. Our results show that when countries face the prospects of lucrative energy investments in natural gas or large hydropower, renewables are often deprioritized. Their suitability to address energy challenges and access gaps is de-emphasized, even though there is little evidence that investment in large-scale generation can handle the energy needs of the most disadvantaged groups. Initiatives and policies supporting community-focused renewable energy have remained limited in both countries. They tend to be designed from the top-down and focused on rural areas when they exist.ConclusionsEnergy transitions in Ethiopia and Mozambique, and many other countries with significant gaps in access to centralized energy systems, require putting inclusivity at the forefront to ensure that energy policies and infrastructure support the well-being of society as a whole. As long as investments in off-grid energy continue to depend on international organizations’ goodwill or development aid programs outside the ambit of national energy plans, energy access gaps will remain unaddressed, and there will not be a genuine and just transition to sustainable energy.

A multi-vector community energy system integrating a heating network, electricity grid and PV production to manage an electrified community

Electrification in energy supply–demand plays a critical role in domestic heating and road transport, delivering an electrified community to reduce carbon emissions. This solution, however, places a significant power demand increase on the distribution networks. To ensure the security of electricity supply, an efficient energy system and energy demand reduction are essential. In this paper, a multi-vector community energy system, applying an electrified heating network, electric vehicle smart charging, community-scale peak shaving and photovoltaic (PV) generation, is demonstrated in three models to manage an electrified community. Firstly, a heating network model, comprising a central ground source heat pump, low-temperature district heating system, electric heaters and thermal storage, is established to measure the optimum distribution temperature. Next, an electrified community model illustrates hourly electricity demands and performances of a community energy system, which is then used to identify the required degree of housing thermal efficiency improvement (i.e., heating demand reduction). The third model evaluates decentralised PV/storage units to maintain the power demand below a targeted power. Modelling results show that the demand ratio of domestic hot water to space heating determines the distribution temperature, which indicates the temperature is increasing with growing housing thermal efficiency. Moreover, the electrification of a community could increase the peak power demand on the highest demand day by over five times, converting heating demands into electricity directly. This significant peak demand can be possibly reduced to only a 33% increase by employing a community energy system. The model of PV/storage units is validated through a 12-week assessment. Ultimately, a modelling tool is developed by assembling the mentioned models, providing four pathways to attain electrification. Users can adjust specific parameters and database to align with the local conditions. The results indicate the requirements of building a community energy system and electricity demands in the highest consumption period.

Deterministic Robust Planning and Probabilistic Techno‐Economic Assessment of a Sector Coupled Community Energy System

AbstractThis paper proposes a systematic approach to examine the techno‐economical impact of a renewable based prosumer centric hybrid energy system (HES) connected to the local distribution grid. Systematic approach includes deterministic and probabilistic framework for optimal planning, scheduling, management, and assessment of HES. During the initiation stage, major components of the HES are identified as solar, Li‐ion batteries and biomass to enable cross‐sectoral participation whereas electric vehicle (EV) charging to promote smart electric‐mobility. Through stage‐wise data collection, processing, and training, hourly solar‐radiation historical data is classified into three seasons through kernelized space‐vector approach. Similarly, probabilistic assessment of EV arrival rate and charging requests are estimated through historical charging data. Based on initial system architecture, deterministic approach includes objective function formulation and its optimal solution through aggrandized class topper optimization (ACTO), particle swarm optimization (PSO), and JAYA algorithm. The objective function is realized through upper‐level economic problem and lower‐level technical sub‐problems. Analyzing the convergence characteristics, the optimal system dynamics and capacity estimated using ACTO is considered as the best with a minimum cost of energy of Rs. 4.235 per kWh. Finally, the probabilistic assessment is carried out through three levels of uncertainty to examine the system cost variations in each scenario.

Mapping a blue energy future for British Columbia: Creating a holistic framework for tidal stream energy development in remote coastal communities

This study develops and implements an interdisciplinary framework to provide a holistic examination of the potential for tidal stream turbines (TST) to displace diesel generated electricity in remote coastal First Nations communities in British Columbia. In doing so it seeks to answer the following research questions: what is the distribution of practical tidal resources in the study region, for which communities is tidal energy a potentially viable electricity source, and what are the benefits and challenges of TST development. GIS Multi-Criteria Decision Analysis and interviews with high level marine spatial planning decision makers are used to identify practical resource sites, bridge knowledge gaps, assess views towards TST development, and understand the desired characteristics of community energy systems. Additional techno-economic criteria for tidal site identification are included to identify communities that may be candidates for TST integration. Results illustrate the need for information provision to communities from resource quantification to characteristics of renewable energy technologies; self sufficiency as being the primary electrification driver; and funding/human resource capacity as being substantial barriers to development. Approximately 89.8 km2 of practical tidal resource is identified, with ≈21.9 km2 of techno-economically feasible practical resource in proximity to nine communities. Four communities appear to be promising candidates for tidal development, and overall results indicate significant interest within the study region for TST development. The interdisciplinary framework presented here provides a methodology that can be adapted and implemented in other jurisdictions to identify practical resources and incorporate social dimensions into MRE decision making.

Cost allocation in integrated community energy systems — Performance assessment

Integrated community energy systems (ICESs) are a modern development of local energy systems by integrating distributed energy resources and local communities. Cost allocation is one of the key issues affecting the success of ICESs. Costs should be allocated to those who cause them, and benefits to those who make the investments. A well-designed cost allocation approach will therefore contribute to a successful implementation and sustainable development of ICESs. This paper presents a general framework for designing cost allocation schemes in ICESs. Various cost allocation methods are proposed to compute the energy bills for local community members in an ICES. In addition, the cost reflectiveness of different cost allocation methods has been computed based on a case study of an ICES to gain insights into how well the costs are allocated. Next to this, the same is also done for the cost predictability to investigate how the energy costs would change in the long term. The results showed that methods with a single energy charging component perform the best in terms of the two criteria. Our assessment can facilitate local community members in selecting a method that satisfies their requirements. Overall, this research contributes to a successful implementation of cost allocation in an ICES.

A Decentralized Optimal Scheduling Method for Integrated Community Energy System

A Decentralized Optimal Scheduling Method for Integrated Community Energy System

Smart energy systems beyond the age of COVID-19: Towards a new order of monitoring, disciplining and sanctioning energy behavior?

The Corona pandemic has led to the increased use of online tools throughout society, whether in business, education, or daily life. This shift to an online society has led social scientists to question the extent to which increased forms of control, surveillance and enforced conformity to ways of thinking, attitudes and behaviors can be promoted through online activities. This question arises overtly amidst a pandemic, but it also lurks behind the widespread diffusion of smart energy systems throughout the world and the increased use of smart meters in those systems. The extent to which forms of monitoring, disciplining and sanctioning of energy behavior and practices could come to reality is thus an important question to consider. This article does so using the ideas of Michel Foucault, together with research on smart energy systems and current trends in energy policy. The article closes with a discussion of energy democracy and democratic legitimacy in the context of possible effects of smart technologies on community energy systems.

Successful implementation of low temperature district heating case studies

Low temperature district heating is recognized as a key technology for the (cost-) efficient integration of renewable energy and waste heat sources in our energy systems. Several studies indicate that a deployment of local district heating schemes is a key measure for reaching the politically set climate goals. Further, implementation of low temperature district heating systems are recommended for taking maximum advantages of synergies with other sectors for decarbonization of the heating sector. Within the IEA DHC Annex TS2 project already realized low temperature community energy system concepts as well as planned or designed systems are identified and visualized. Furthermore, projects showing an innovative heat use or operation of buildings are also included in the analyses. The different projects are assessed and compared. The presentation of the demonstrators is set up in such a way that knowledge is generated about the indoor heating system, the district heating system and of the competitiveness of low temperature district heating systems, giving the evidence that these systems are feasible, efficient and reliable under various boundary conditions. The demonstrators further indicate that there are existing challenges, where further research on innovative district heating concepts for integrating decentral feed-in of renewable energy is required. The demonstrators included in the IEA DHC Annex TS2 are analysed in regard to which elements of new knowledge they can generate. For each demonstrator there are specific innovations in focus. Furthermore, the case studies show that the related business models for the utilities change when system temperatures are lowered. The paper presents and discusses the results from current research work within of the IEA DHC Annex TS2 on Implementation of Low Temperature District Heating Systems (Averfalk et al., 2021; Annex TS2, 2021 [1]).

New clean energy communities in polycentric settings: Four avenues for future research

Given the gaps between EU ambitions regarding energy community development and the current reality of clean energy communities in Europe, we explore a research framework enabling viable multi- and interdisciplinary research into new clean energy communities. We offer a definition of new clean energy communities, discuss their potential for wider dissemination and identify four factors that contribute to the current mismatch between ambitions and reality in energy community development. As a broader framework for interdisciplinary research into the field of new clean energy communities, we propose polycentric governance theory, considering the fact that the area of community energy systems is essentially multi-scalar, and that the rules of engagement in such systems are of great significance. This opens up four avenues for research on energy communities, which we outline in terms of enabling institutional contexts, potential for learning and transferability, business models and value propositions, and evaluation of outcomes and processes.

Cost Allocation in Integrated Community Energy Systems—Social Acceptance

Integrated community energy systems (ICESs) are a good representative of local energy systems by integrating local distributed energy resources and local communities. It is proposed that costs should be allocated in a socially acceptable manner since there is no regulation in ICESs. In this paper, social acceptance is conceptualized from the dimension of community acceptance considering procedural and distributive justice. A fair process increases the understanding and the acceptance of the cost allocation outcomes, and a fair outcome leads to the acceptance of the cost allocation procedure. This approach adopted the multi-criteria decision-making technique to evaluate social acceptance to select a cost allocation method that was socially acceptable to local community members. The results show that our approach is unique and useful when multiple decision-making groups have to decide together upon the cost allocation method. It is able to provide quantitative results and optimal decisions from a multi-group decision-making perspective. The methodology developed in this research can be applied to any local community energy system to select a cost allocation method. Furthermore, the obtained results can be used by decision-makers to support them in the decision-making process. Based on our approach, policy implications are also analyzed to support the success of cost allocation in ICESs.

Decentralized optimal scheduling for integrated community energy system via consensus-based alternating direction method of multipliers

To transform the original centralized scheduling framework of integrated community energy systems (ICES), a decentralized scheduling method is proposed for the optimal operation of ICES. Firstly, linearized mathematical models of the electric distribution system and natural gas distribution system are established to eliminate the nonconvexity and nonlinearity of the multi-energy systems. Meanwhile, an improved energy hub model is proposed by introducing the state variable, which is able to obtain the optimal solution with better accuracy and higher efficiency. Secondly, a decentralized scheduling framework is developed via an improved consensus-based alternating direction method of multipliers (ADMM). By introducing several coupling links as consensus variables, the optimal operation of the ICES is decoupled according to the physical interactions among each sub-system, in which the original model can be solved parallelly in a decentralized manner. Only the consensus variables are exchanged among sub-systems so that the privacy and confidential items of each sub-system operated by different entities can be ensured. Finally, two different ICES test cases with different system scales are utilized to demonstrate the effectiveness of the proposed method, which is able to provide scheduling scheme same as the centralized method. Dynamic step size modification is further considered in the consensus-based ADMM. By updating the step size during each iteration, the computation expense of optimization process is reduced with less consuming time, iteration and apparent oscillation, by which the convergence performance of ADMM is improved with higher computation efficiency.

Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads

For the future development of integrated energy systems with high penetration of renewable energy, an integrated community energy systems (ICES) dispatch model is proposed including various renewable energy sources and energy conversion units. Energy coupling matrices of ICES based on traditional energy hub (EH) models are constructed. Uncertainties of long-term forecast data of renewable energy sources and internal loads are depicted by multi-interval uncertainty sets (MIUS). To cope with the impacts caused by uncertainties of renewable energy sources and internal loads, the whole dispatch process is divided into two stages. Considering various constraints of ICES, we solved the dispatch model through the improved particle swarm optimization (IPSO) algorithm in the first stage. The optimal evolutionary dispatch is then proposed in the second stage to overcome the evolution and errors of short-term forecast data and obtain the optimal dispatch plan. The effectiveness of the proposed dispatch method is demonstrated using an example considering dramatic uncertainties. Compared with the traditional methods, the proposed dispatch method effectively reduces system operating costs and improves the environmental benefits, which helps to achieve a win-win situation for both energy companies and users.

Quantifying the impacts of biomass driven combined heat and power grids in northern rural and remote communities

Northern rural and remote communities face several energy system related concerns such as high heating and electricity rates, dependence on imported energy, and low levels of energy security and autonomy. Many of these issues can be addressed via the implementation of local community-based sustainable energy generation technologies such as biomass driven combined heat and power (CHP) plants. The current research investigates the technical, economic, socio-economic, and environmental impacts of implementing biomass driven CHP plants as the primary energy source in both remote (off-grid) and rural (grid-connected) community energy systems that comprise a district heating grid. The MoCreebec Eeyoud community located in Northern Ontario, Canada, is used as the case study in the analysis. Results show that biomass driven CHP grids are an economically attractive alternative for both remote and rural energy systems. Biomass driven CHP grids are shown to be up to 42% less costly than conventional diesel power generation systems in remote community settings. Similarly, remote biomass driven CHP grids are shown to be up to 66% less costly than rural energy systems when electrical transmission grid extension lengths exceed 100 km. Biomass driven CHP grids can also drastically reduce greenhouse gas emissions, lower carbon tax payments, generate local economic employment, and increase energy autonomy. Although the findings of this study are specific to the community under investigation, the research methodology and insights gained are generalizable to remote and rural communities located across Canada and abroad.

Optimising Energy Flexibility of Boats in PV-BESS Based Marina Energy Systems

Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy.

Evaluating carbon capturing strategies for emissions reduction in community energy systems: A life cycle thinking approach

On-site carbon capturing, storage, and utilization (CCSU) has proven its’ potential to reduce CO2 emissions from large-scale fossil fuel combustion systems. However, the integration of CCSU in community-scale on-site energy generation applications such as district energy systems has not been comprehensively explored in literature. This study aims to propose a life cycle thinking-based framework to compare and prioritize emission reduction strategies that include CCSU and renewable energy technologies to develop zero-emission community energy systems. The framework incorporates multi-criteria decision-making approaches to rank and prioritize community energy emission mitigation strategies. A scenario-based method was employed in assessing the performance of CCSU technologies along with other compatible alternative energy choices. The framework was demonstrated for all the provinces in Canada. Results show that CCSU is more favorable for regions with high dependence on fossil fuel-based energy sources. CCSU could reach the commercial scale if the cost of emission avoided drops below the cost of CO2 emissions. . The findings of this study are geared towards providing practical decision-support tools for stakeholders who hold responsible for policy and investment decisions in community energy. The developed framework is a generalized technique that provides the flexibility to be employed in any location across the globe.

Towards a cost-effective remote community energy system model: Evaluating trade-offs between supply and demand-side interventions

Most remote communities in Canada rely upon diesel generators as the primary means of delivering electricity and heat to residents. Though diesel generators are a mature and reliable technology, they are a leading source of a number of environmental, social, and economic problems faced in these communities such as high levels of pollution, energy insecurity, and high energy costs, respectively. In recent years, significant progress has been made with regards to developing demand and supply-side technology-based interventions that allow remote communities to address these problems in a manner that is both economically viable and environmentally sound. Two interventions that fall within these categories are building-based envelope energy retrofits and biomass driven district heating grids. In the current study, an analysis is conducted to assess the impacts of implementing a wide range of packaged envelope energy retrofits on the economic viability of biomass driven district heating grids in remote communities. Results show that from an economic standpoint it is preferable for communities to invest in building-based demand-side interventions instead of a biomass driven district heating grid. However, these results vary substantially depending on factors such as the community building layout, state of building energy efficiency, and energy rate paid by residents.

Optimal Integration of Building Heating Loads in Integrated Heating/Electricity Community Energy Systems: A Bi-Level MPC Approach

This paper proposes a bi-level optimal integration scheme for buildings' space heating loads in the integrated community energy system (ICES). The optimal integration scheme consists of an efficient energy management method and a heating pricing method for the ICES with buildings. At the upper level, the ICES operator optimizes the schedules of energy generation and supply, and the heating prices to buildings to maximize its profit. At the lower level, consumers in buildings optimize the water flow rates in the radiators to minimize their heating costs. The thermal dynamics of the building with controllable indoor radiators is modeled using the model of Resistor-Capacitor thermal network. Moreover, the model predictive control (MPC) is integrated with the bi-level optimization to achieve economic and reliable scheduling of the ICES and buildings in the presence of uncertainties. The bi-level MPC optimization is reformulated as an MPC based mixed-integer linear program using the Karush-Kuhn-Tucker optimality conditions and several linearization techniques. Numerical studies show that the bi-level MPC method can obtain a balanced scheduling scheme between the energy costs of consumers in buildings and the ICES operator's profits. The MPC method can ensure higher profits of the ICES operator and simultaneously, lower energy costs of consumers in buildings.

Retail dynamic pricing strategy design considering the fluctuations in day-ahead market using integrated demand response

The imbalance between fixed retail prices and fluctuating wholesale prices imposes enormous stresses on the profits of residential retailers. Dynamic pricing (DP) can be regarded as an effective measure for retailers to motivate demand resources and reduce their market risks. However, existing DP programs cannot be adapted to all residents, as these programs can bring financial risk to some groups, influencing their marketability to some extent. In this study, a DP model is proposed considering the fluctuation in the day-ahead market from the view of retailers. This model consists of two parts: (i) the fixed price, representing the existing price, and (ii) the floating price, which is a real-time reflection of the fluctuating day-ahead price. Then, a two-step settlement mode is adopted for this DP to ensure that there is no expenditure supplement of residents compared with the existing price. Further, in a community energy system, an integrated demand response strategy for profit maximization of the retailer is proposed to determine the optimal DP, in which the response behavior of residents is established using the demand price elasticity matrix on the whole. A detailed case study is conducted in three price scenarios to verify its applicability and effectiveness. The results show that DP strategies are beneficial for both the retailer and all residents. In addition, this approach can benefit residents who use more energy in valley hours but less energy during peak hours.