Bahman Ahmadi, Aditya Pappu, Gerwin Hoogsteen, Marco E.T. Gerards, Johann L. Hurink
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引用次数: 0
Abstract
This paper presents a decentralized energy management approach based on a Multi-Objective Energy Management System called DMOEMS, designed for Energy Communities (ECs), aiming to create resilient and sustainable energy systems. DMOEMS integrates a multi-objective optimization framework that aggregates conflicting goals–minimizing electricity cost and CO2, reducing Photovoltaic (PV) curtailment, and maximizing self-consumption–by converting them into a single objective using user-defined weight factors. Each local controller optimizes the operation of distributed assets based on localized constraints and user preferences, while an EC controller coordinates aggregated power profiles through an iterative feedback mechanism. This coordination dynamically adjusts weight factors and curtailment strategies to resolve grid congestion without compromising individual privacy. Simulation studies on the realistic Aardehuizen EC demonstrate that DMOEMS effectively mitigates overloading scenarios across diverse operating conditions (high EV charging, normal demand, and excess PV generation), enhances user satisfaction, reduces operational costs, and lowers CO2 emissions. The proposed framework highlights the potential of a democratic, decentralized approach to energy management in modern ECs. The numerical results for asset management using DMOEMS indicate improvements in different aspects such as reduction of 20 % in CO2 emissions, improvement of 4 % in electricity cost savings, and a 30 % reduction in PV curtailment relative to baseline scenarios. Furthermore, the proposed mechanism in the DMOEMS shows improvement in computational cost by converging faster to resolve grid congestion compared to conventional approaches.
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.