Search Results (87)

This paper presents SEAMS (Solar Energy Aggregator Management System), an optimization-based framework for managing solar energy trading in smart communities under Thailand’s regulatory constraints. A major challenge is the prohibition of residential grid feed-in, which limits the use of conventional peer-to-peer energy models. Additionally, fixed pricing is required to ensure simplicity and trust among users. SEAMS coordinates prosumer and consumer households, a shared battery energy storage system (BESS), and a centralized aggregator (AGG) to minimize total electricity costs while maintaining financial neutrality for the aggregator. A mixed-integer linear programming (MILP) model is developed to jointly optimize PV sizing, BESS capacity, and internal buying price, accounting for Time-of-Use (TOU) tariffs and local policy limitations. Simulation results show that a 6 kW PV system and a 70–75 kWh shared BESS offer optimal performance. A 60:40 prosumer-to-consumer ratio yields the lowest total cost, with up to 49 percent savings compared to grid-only systems. SEAMS demonstrates a scalable and policy-aligned approach to support Thailand’s transition toward decentralized solar energy adoption and improved energy affordability. Full article

In the housing sector emission reduction builds on a shift from fossil fuels to renewable energy sources and increasing the efficiency of energy usage, with heating playing a dominant role in comparison to that of electricity. For electricity production in the residential sector, research shows that different settings of (co-)ownership in renewables are linked to a greater tendency to invest in energy-efficient devices or to adopt more energy-conscious behaviours. The empirical analysis demonstrates that fully-fledged prosumers, i.e., consumers who have the option to choose between self-consumption and selling to third parties or the grid, exhibit a higher tendency to invest in energy efficiency and that only this group manifests a greater likelihood of engaging in conscious-energy consumption behaviour. This paper extends the analysis to include heating in the residential sector. The study conducted an ANCOVA based on a sample of 2585 German households. The findings show that, depending on the (co-)ownership setting, the willingness to invest and to adopt energy-efficient practices grows considerably. Consumer-sellers demonstrate the highest willingness to invest and adapt energy conscious behaviour. Furthermore, regarding heating in particular, self-consumers are also inclined to invest and engage in energy-savings behaviour. Full article

This study evaluates the cost-effectiveness and environmental benefits of two residential photovoltaic (PV) on-grid systems in Poland: a 4.35 kWp system (V1) and a 5.70 kWp system (V2). With growing interest in prosumer energy and climate goals, assessing small-scale PV systems is critical for sustainable energy planning. Economic performance was analyzed using net present value (NPV), internal rate of return (IRR), and discounted payback period (DPP). Sensitivity analyses identified key factors affecting investment outcomes. V2 demonstrated superior performance, with an NPV five times higher than that of V1 and annual savings of EUR 1392 compared to EUR 270. V2 also achieved a 15.66% IRR and 7.7-year DPP, outperforming V1′s 5.85% IRR and 17.3-year DPP. CO₂ emission reductions were 2.6 and 3.6 Mg/year for V1 and V2, respectively. The findings emphasize the importance of tailored financial incentives and regulatory reforms to support prosumers and optimize grid integration in Poland. Full article

The Renewable Energy Community (REC) has emerged in Europe, encouraging the use of renewable energy sources (RESs) within localities, bringing social, economic, and environmental benefits. RESs are characterized by various loads, including household consumption, storage systems, and the increasing integration of electric vehicles (EVs). EVs offer opportunities for distributed RESs, such as photovoltaic (PV) systems, which can be economically advantageous for RECs whose members own EVs and charge them within the community. This article focuses on the integration of PV systems and the management of energy loads for different participants—consumers and prosumers—along with a small EV charging setup in the REC. A REC consisting of a multi-unit building is examined through a mathematical and numerical model. In the model, hourly PV generation data are obtained from the PVGIS tool, while residential load data are modeled by converting monthly electricity bills, including peak and off-peak details, into hourly profiles. Finally, EV hourly load data are obtained after converting the data of voltage and current data from the charging monitoring portal into power profiles. These data are then used in our mathematical model to evaluate energy fluxes and to calculate self-consumed, exported, and shared energy within the REC based on energy balance criteria. In the model, an energy management system (EMS) is included within the REC to analyze EV charging behavior and optimize it in order to increase self-consumption and shared energy. Following the EMS, it is also suggested that the number of EVs to be charged should be evaluated in light of energy-sharing incentives. Numerical results have been reported for different seasons, showing the possibility for the owners of EVs to charge their vehicles within the community to optimize self-consumption and shared energy. Full article

Expanding the installation and use of renewable energy sources will help Europe reach its energy and climate goals. Additionally, users of small-scale photovoltaic systems will be essential to the energy transition by forming renewable energy communities (RECs). This paper offers a techno-economic analysis of the Italian REC incentive system and a suitable business model to encourage residential photovoltaic and battery installations and lower electricity costs. In this paper, we present a community model that includes a set number of prosumers, a growing number of consumers, and various configurations and management strategies for photovoltaic (PV) and battery systems. Key elements of novelty include (i) the implementation of a fully-solar REC with PV and storage under the Italian incentive scheme, (ii) the introduction a of novel centralized BESS control strategy based on firm generation that maximises energy sharing while minimising its grid impact, (iii) the economic profitability analysis of the PV and storage system for consumers and prosumers when different BESS control strategies are applied. The simulation results show that energy performance increases if a centralized battery management strategy is activated and more consumers join the community. In addition, the proposed business model shows that the best profitability is achieved when there are as many consumers as prosumers. Most importantly, the approach was extended to the extreme case of a “fully solar-powered” community, demonstrating that the REC model is viable even with the current PV and battery costs. Finally, we show that fully solar-powered communities can be easily implemented where homeowners have enough surface for PV installation and purchase a central battery through crowdfunding. Full article

The implementation of photovoltaic and home storage systems in multi-family houses (MFHs) in Germany lags significantly behind their development in single-family houses. The Landlord-to-Tenant (L2T) power supply model is meant to reduce this gap, yet few projects have been implemented to date. In this model, the landlord must fulfill the tenants’ power demand through a combination of photovoltaic generation and storage and electricity from the grid, for which the landlord pays an auxiliary electricity price that greatly influences the financial viability of a project. Our contribution focuses on the impact of electricity price variations and recent policy changes on the financial viability of small-scale L2T concepts. We considered component investment costs, building sizes, photovoltaic yields, and future developments. Recent policy changes have improved the financial viability of L2T projects, increasing the maximal auxiliary electricity price for which an investment is viable by 13 ct/kWh for a four-party MFH. Minimal auxiliary electricity prices justifying the installation of home storage systems (HSSs) decreased by 9 ct/kWh from 2020 to 2023. Autarky rates are substantially different across the considered scenarios, with the autarky rate being defined as the percentage of consumption of self-generated energy relative to the total energy consumption. For a 22-party MFH the autarky rate decreases by 17% compared to a 4-party MFH. HSSs have the potential to increase autarky rates while maintaining the financial viability of L2T projects. Full article

In the context of the increasing integration of renewable energy sources (RES) and smart devices in domestic applications, the implementation of Home Energy Management Systems (HEMS) is becoming a pivotal factor in optimizing energy usage and reducing costs. This review examines the role of reinforcement learning (RL) in the advancement of HEMS, presenting it as a powerful tool for the adaptive management of complex, real-time energy demands. This review is notable for its comprehensive examination of the applications of RL-based methods and tools in HEMS, which encompasses demand response, load scheduling, and renewable energy integration. Furthermore, the integration of RL within distributed automation and Internet of Things (IoT) frameworks is emphasized in the review as a means of facilitating autonomous, data-driven control. Despite the considerable potential of this approach, the authors identify a number of challenges that require further investigation, including the need for robust data security and scalable solutions. It is recommended that future research place greater emphasis on real applications and case studies, with the objective of bridging the gap between theoretical models and practical implementations. The objective is to achieve resilient and secure energy management in residential and prosumer buildings, particularly within local microgrids. Full article

The rising demand for water and energy is driving the overuse of natural resources and contributing to environmental degradation. To address these challenges, the focus has shifted to low- and zero-emission technologies that utilize alternative sources of water and energy. Although such systems are commonly applied in residential, commercial, and industrial buildings, facilities along transportation routes generally depend on grid connections. This study aimed to enhance operational independence and reduce environmental impacts by modernizing the Rest Area Stobierna (RAS) along Poland’s S19 expressway, part of the Via Carpatia road. A comprehensive technical, economic, and environmental analysis was conducted using HOMER Pro software (3.18.3 PRO Edition) and a simulation model based on YAS operating principles. The proposed Hybrid Renewable Energy System (HRES) incorporates photovoltaic panels, battery storage, and a rainwater harvesting system (RWHS). Two configurations of the HRES were evaluated, a prosumer-based setup and a hybrid-island mode. Optimization results showed that the hybrid-island configuration was most effective, achieving a 61.6% share of renewable energy in the annual balance, a 7.1-year return on investment, a EUR 0.77 million reduction in Net Present Cost (NPC), and a 75,002 kg decrease in CO₂ emissions over the system’s 25-year lifecycle. This study highlights the potential of integrating renewable energy and water systems to improve sustainability, reduce operational costs, and enhance service quality in road infrastructure facilities, offering a replicable model for similar contexts. Full article

Rooftop PV-BESS installations often lose profitability despite policy support to accelerate capacity growth. This paper performs techno-economic analysis to assess the effect of heterogeneity in real-world conditions on the economic viability of residential rooftop PV-BESSs. The stochastic nature of generation and consumption is modeled as multiple deterministic scenarios that vary in the capacity rating of the PV system, climatic conditions (insolation and temperature), self-consumption ratio (SCR), generation–demand concurrence, and the presence/absence of capacity and storage subsidies. The results indicate that PV-BESSs are mostly profitable when operating at a capacity factor ≥ 18%. Furthermore, higher daytime electricity consumption enables greater savings with smaller storage capacities, thereby facilitating cost-effective installations at capacity factors ≥ 8%. However, low-yielding PV-BESSs and prosumers exhibiting low generation–demand concurrence require suitable subsidy allocations to become profitable. Full article

In order to reach climate protection goals at national or international levels, new forms of combined heating and cooling networks with ultra-low network temperatures (5GDHC) are viable alternatives to conventional heating networks. This paper presents a simulation library for 5GDHC networks as sustainable shared energy systems, developed in the object-oriented simulation framework OpenModelica. It comprises sub-models for residential buildings acting as prosumers in the network, with additional roof-mounted thermal systems, dynamic thermo-hydraulic representations of distribution pipes and storage, time-series-based sources for heating and cooling, and weather conditions adjustable to user-specified locations. A detailed insight into an in-house development of a sub-model for horizontal ground heat collectors is given. This sub-model is directly coupled with thermo-hydraulic network simulations. The simulation results of energy balances and energetic efficiencies for an example district are described. Findings from this study show that decentralised roof-mounted solar thermal systems coupled to the network can contribute 21% to the total source heat provided in the network while annual thermal gains from the distribution pipes add up to more than 18% within the described settings. The presented simulation library can support conceptual and advanced planning phases for renewable heating and cooling supply structures based on environmental sources. Full article

Photovoltaic (PV) systems are becoming increasingly popular, especially in residential buildings. However, the high penetration of prosumer PV micro-installations can have a negative impact on the operation of distribution networks due to the low self-consumption of the energy produced. One way to mitigate this problem is to use a residential energy storage system (RESS) and load shifting under a demand-side management (DSM) scheme. Energy management systems (EMSs) are used to control the operation of RESSs and to implement DSM. There are two main categories of EMSs: rule-based and optimization-based. Optimization-based EMSs provide better results than rule-based EMSs but can be computationally expensive. This article proposes an optimization-based EMS that is designed specifically for residential buildings. The proposed home energy management system (HEMS) uses a particle swarm optimization method to maximize the prosumer’s financial neutrality, which is calculated based on dynamic energy prices. Simulation-based evaluation using the measurements taken in a building equipped with a PV source, RESS, and shiftable loads shows the improved performance of the proposed HEMS compared to rule-based RESS control. The results show that the designed HEMS increases self-consumption, thus reducing the impact of the prosumer’s PV micro-installations on the distribution grid. Full article

The growing adoption of behind-the-meter (BTM) photovoltaic (PV) systems, electric vehicle (EV) home chargers, and heat pumps (HPs) is causing increased grid congestion issues, particularly in power distribution grids. Leveraging BTM prosumer flexibility offers a cost-effective and readily available solution to address these issues without resorting to expensive and time-consuming infrastructure upgrades. This work evaluated the effectiveness of this solution by introducing a novel modeling framework that combines a rolling horizon (RH) optimal power flow (OPF) algorithm with a customized piecewise linear cost function. This framework allows for the individual control of flexible BTM assets through various control measures, while modeling the power flow (PF) and accounting for grid constraints. We demonstrated the practical utility of the proposed framework in an exemplary residential region in Schutterwald, Germany. To this end, we constructed a PF-ready grid model for the region, geographically allocated a future BTM asset mix, and generated tailored load and generation profiles for each household. We found that BTM storage systems optimized for self-consumption can fully resolve feed-in violations at HV/MV stations but only mitigate 35% of the future load violations. Implementing additional control measures is key for addressing the remaining load violations. While curative measures, e.g., temporarily limiting EV charging or HP usage, have minimal impacts, proactive measures that control both the charging and discharging of BTM storage systems can effectively address the remaining load violations, even for grids that are already operating at or near full capacity. Full article

Renewable energy communities foster the users’ engagement in the energy transition, paving the way to the integration of distributed renewable energy sources. So far, the scientific literature has focused on residential users in energy communities, thus overlooking the opportunities for industrial and commercial members. This paper seeks to bridge this gap by extending the analysis to the role of non-residential users. The proposed methodology develops an effective clustering approach targeted to actual non-residential consumption profiles. It is based on the k-means algorithm and statistical characterization based on relevant probability density function curves. The employed clusterization procedure allows for effectively reducing a sample of 49 real industrial load profiles up to 11 typical consumption curves, whilst capturing all the relevant characteristics of the initial population. Furthermore, a peer-to-peer sharing strategy is developed accounting for distributed and shared storage. Three scenarios are considered to validate the model with different shares of non-residential users, and the results are then evaluated by means of shared energy, self-consumption, and self-sufficiency indices. Moreover, the results show that the integration of a large non-residential prosumer in a REC may increase the self-sufficiency of residential members by 8.2%, self-consumption by 4.4%, and the overall shared energy by 37.3%. Therefore, the residential community consistently benefits from the presence of non-residential users, with larger users inducing more pronounced effects. Full article

Residential segments are of the greatest interest from the point of view of Demand-Side Resources and Decarbonization. Main end-uses such as water heaters, heating, and cooling have interesting opportunities: first, they can store energy, and this is relevant for the integration of renewables. Second, they are candidates for efficiency and electrification, increasing their demand share and the flexibility of demand. This paper aims to formulate an elemental Physical-Based Heat Pump Water Heater model that will enable the use of these energy-efficient appliances through aggregation in complex products, considering the advantages for demand and supply sides. Simulation results show that the individual performance is quite accurate and that the proposed model is flexible enough to be used to take more profit from energy markets or to easily respond to fast-occurring events. The model can be easily aggregated and used to obtain baselines, an important point for Demand Response evaluation. Results also demonstrate that demand–supply coordination and balance can be improved using these models to reduce or mitigate the risks and volatility of renewables without inducing a noticeable loss of service. Consequently, the contribution of this responsive load can be modelled through this methodology, making the engagement of more customer segments in Demand Response policies more credible and deploying new segments, such as prosumers. Full article

Rising energy demands, economic challenges, and the urgent need to address climate change have led to the emergence of a market wherein consumers can both purchase and sell electricity to the grid. This market leverages diverse energy sources and energy storage systems to achieve significant cost savings for consumers while providing critical grid support for utilities. In this study, an energy management system has been employed to tackle the optimization problem associated with various energy sources. This approach relies on mixed-integer linear programming (MILP) to optimize energy utilization while adhering to diverse constraints, yielding a feasible energy solution. This model is applied to real-world energy system consumption data and forecasts the most cost-effective day-ahead energy plans for different types of loads engaged in demand response. Furthermore, time-based charging and discharging strategies for electric vehicles and energy storage systems are considered, conducting a comprehensive analysis of energy costs across various storage devices. Our findings demonstrate that implementing this model can lead to an 18.26% reduction in operational costs when using lithium batteries and a remarkable 14.88% reduction with lead–acid batteries, particularly when integrating solar power and an EV into the system, while GHG is reduced by 36,018 grams/day for a load of 25 kW in one particular scenario. However, the analysis reveals that integrating wind power is not economically viable due to its comparatively higher operational costs. Full article