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Optimal design of hybrid power generation system and its integration in the distribution network

机译:混合发电系统的优化设计及其在配电网中的集成

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The inability of conventional energy sources to fully meet the rapidly increasing energy demands in today's world has led to the growing importance of hybrid power generation systems that incorporate renewable energy sources. This work proposes an optimally designed multi-source standalone hybrid generation system comprising of photovoltaic panels, wind turbine generators, batteries and diesel generator. This design aims at minimizing emissions and cost, expressed in the form of the Net Present Value (NPV) of the system, while simultaneously maximizing its Energy Index of Reliability (EIR). The designed hybrid power generation system is further integrated into the distribution system as a Distributed Generation (DG); this is to optimally improve the performance of the distribution system by minimizing the total losses and the total voltage deviation of the distribution system. The combined cost and emissions incurred due to the energy purchased from the grid and the energy generated by DG are also reduced. For this purpose an improvised Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is developed taking care of contradicting objectives. The proposed optimization algorithms are implemented using MATLAB for a standard IEEE 69-bus distribution system, using an hour-wise annual data of Spain. The location and size of DGs and the type and number of each generating source of the hybrid system are considered as decision variables. The effectiveness of the proposed optimal design using the improvised MOPSO algorithm is established in comparison with Improved Hybrid Optimization by Genetic Algorithm (i-HOGA) results. (C) 2016 Elsevier Ltd. All rights reserved.
机译:传统能源无法完全满足当今世界迅速增长的能源需求,这导致了结合了可再生能源的混合发电系统的重要性日益提高。这项工作提出了一种优化设计的多源独立混合发电系统,该系统包括光伏板,风力发电机,电池和柴油发电机。此设计旨在以系统的净现值(NPV)形式表示的排放量和成本最小化,同时最大化其能源可靠性指数(EIR)。设计的混合发电系统作为分布式发电(DG)进一步集成到配电系统中;这是通过最小化配电系统的总损耗和总电压偏差来最佳地改善配电系统的性能。从电网购买的能源和DG产生的能源所产生的总成本和排放也减少了。为此目的,开发了一种改进的多目标粒子群优化(MOPSO)算法,以解决相互矛盾的目标。拟议的优化算法是使用MATLAB针对标准IEEE 69总线配电系统使用西班牙每小时的年度数据来实现的。 DG的位置和大小以及混合系统的每个发电源的类型和数量都被视为决策变量。与改进的遗传算法混合优化(i-HOGA)结果相比,使用改进的MOPSO算法的拟议优化设计的有效性得以确立。 (C)2016 Elsevier Ltd.保留所有权利。

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