Marialaura Di Somma , Mohammad Dolatabadi , Alessandro Burgio , Pierluigi Siano , Domenico Cimmino , Nicola Bianco
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引用次数: 0
Abstract
Renewable energy communities (RECs) are considered a promising tool for putting the citizens at the center of the energy transition, while also promoting self-sufficiency coming from local resources and decarbonization through high penetration of renewables. A key challenge when operating RECs is represented by the number of decision variables to consider depending on the number and type of community participants and distributed technologies, while also considering the associated uncertainties. Moreover, the monetarization of energy shared in the community for benefitting residential users is crucial. The contribution of this paper is to present an innovative stochastic linear programming model for optimizing the energy sharing in RECs to maximize revenues associated with the incentives for the energy shared as established by the Italian regulation. The REC under study consists of a condominium with a PV plant installed on the rooftop, and air conditioning and battery storage systems installed in each apartment. The problem is to find the optimal control strategies for air conditioning systems and batteries with a 15-minute time-step, which maximize the expected revenue from energy sharing while meeting the users’ comfort requirements and preventing users’ bills from increasing. Numerical results demonstrate the effectiveness of the optimization model to maximize the energy shared and the related revenues through the optimal control of installed assets. The combined optimized strategies of both air conditioning and batteries allow for finding the best performance of the REC in terms of maximization of the energy shared. In this latter case, the expected total revenue for users for the energy sharing increases by 59.7 %, 38.7 % and 12.6 % as compared to the baseline case with no optimal control, the case with control of air conditioning only, and the case with control of batteries only, respectively.
期刊介绍：
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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