Energy and Buildings · 2024 · 30 citations · 23 references
AgricultureEconomicsEnergy EconomicsEnergy ManagementRenewable Energy SystemsDistributed Energy ResourcesEnergy ConservationEnergy IncentivesEnergy Management SystemsEnergy UseRenewable EnergyCollective ConsumptionCommunity Energy SystemsEconomic IncentivesEnergyEnergy AllocationEnergy ConsumptionPearson Correlation CoefficientRenewable Energy Self-consumption
The potential of sharing energy from production plants is characterized as a new paradigm for the production and consumption of energy from renewable sources. The emergence of Renewable Energy Communities (REC) and Collective Self Consumption (CSC) in the European context has supported the regulation of the concept of shared energy and provided economic saving to its members. Many countries have adopted a virtual scheme for local energy sharing without a physical basis for calculating intra-community energy exchanges and national legislation often provides economic incentives for shared energy within the community. However, many of the management aspects regarding the distribution of shared energy and therefore economic gain are managed internally by members, allowing for various configurations that depending on the type of generation systems, users, and purposes of the community. Since a unique method is not established, it is crucial to define fair criteria for energy allocation among the community members rewarding virtuous behaviour. This work proposes four algorithms for dynamic sharing keys based on participants’ contributions to the community: a consumption-proportional key, a Pearson correlation coefficient-based key to evaluate synchronism between electricity drawn from the grid and the surplus fed into the grid, a trend-based key that accounts for the difference between purchased and injected energy, and a combination of the previous two keys. A Renewable Energy Community (REC), under Italian regulation, consisting of eight representative users was simulated using real hourly energy consumption and production profiles. The aim was to perform an annual comparative analysis between the developed methods and identify the different amount of shared energy assigned to each user based on their contribution, highlighting their strengths and limitations. The results show how some of the algorithms assign to users with the highest consumption an amount of shared energy higher than their real sharing potential, while users with greater sharing potential are penalised.
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Jens Lowitzsch, Christina E. Hoicka, F.J. van Tulder · Renewable and Sustainable Energy Reviews · 2020 · 562 citations · Full text
Public Affairs, Environmental Policy, Community Governance +16
Renewable Energy Communities business models under the 2020 Italian regulation
A. Cielo, P. Margiaria, Paolo Lazzeroni et al. · Journal of Cleaner Production · 2021 · 163 citations