Grey Wolf Optimization Algorithm based Combined Economic and Emission Dispatch Problem

K. Manikandan, Kesamreddy Swapna, Narendra Naik J, K. N. Kumar, Kaku Rakesh, Kamisetty Vaishnavi
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Abstract

Economic dispatch for the microgrid (MG) is better adapted to the needs of a system in actual operation in the current scenario because it not only takes into account the scheduling cycle's lowest cost but also coordinates between several distributed generations (DGs) over a long period of time. Due of the unpredictable fluctuations and intervals that wind and solar energy are subject to, the economic dispatch problem is quite challenging to resolve. Intelligent algorithms and multi-objective optimum dispatching systems are acknowledged as excellent strategies for enhancing the economics and environmental friendliness of microgrid applications. The Multi Objective Optimal Dispatching System is developed for microgrids made up of photovoltaic cells (PV), wind turbines (WT), micro turbines (MT), fuel cells (FC), and battery storage (BT). The microgrid's dispatching problems might be solved and its dispatching convergence accuracy., stability., and speed all increased by using optimization techniques.
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基于经济与排放联合调度问题的灰狼优化算法
微网经济调度既考虑调度周期成本最低,又兼顾多个分布式发电机组之间的长时间协调,因此更能适应当前场景下系统的实际运行需求。由于风能和太阳能具有不可预测的波动和周期,因此经济调度问题的解决具有很大的挑战性。智能算法和多目标优化调度系统被认为是提高微电网应用经济性和环境友好性的优秀策略。针对由光伏电池(PV)、风力涡轮机(WT)、微型涡轮机(MT)、燃料电池(FC)和蓄电池(BT)组成的微电网,开发了多目标优化调度系统。解决了微电网调度问题,提高了微电网调度收敛精度。、稳定。,速度都通过使用优化技术而提高。
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