用粒子群算法求解混合可再生能源系统经济负荷调度问题的有效方法

IF 0.5 Q4 AUTOMATION & CONTROL SYSTEMS
Nimish Kumar,  Rahul Raman
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引用次数: 0

摘要

将可再生能源纳入经济负荷调度问题(eldp)并非易事。本文提出了一种求解由热能、风能和太阳能光伏(PV)发电机组成的混合可再生能源系统(HRES)的eldp的可靠方法。可再生能源的发电成本可以忽略不计,但可再生能源运营商要求收取一些所谓的可再生/维护/回报成本来运行工厂。因此,线性成本函数已被实现为RE代(REGs)。基于reg的成本考虑了两种情况,一种是reg的无成本,另一种是reg的线性成本函数。常用的优化技术粒子群优化(PSO)被用于求解eldp问题。利用IEEE 30总线系统、太阳能光伏和风力发电机组成的测试系统,研究了该方法的强度。仿真结果表明,仅太阳能光伏发电、仅风能发电和同时太阳能光伏和风能发电时,在负荷需求为283.4 MW的情况下,发电成本分别节省63.829、74.99和182.937美元/h和139.53、150.468和358.883美元/h。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Efficient Approach for Solving Economic Load Dispatch Problems of Hybrid Renewable Energy System Using Particle Swarm Optimization Algorithm

Efficient Approach for Solving Economic Load Dispatch Problems of Hybrid Renewable Energy System Using Particle Swarm Optimization Algorithm

The incorporation of renewable energy (RE) in the economic load dispatch problems (ELDPs) is not an easy task. This paper presents a reliable approach to solve the ELDPs of the hybrid renewable energy system (HRES) that consists of thermal, wind, and solar photovoltaic (PV) generators. The generation cost of RE is negligible, but the renewable operators demand some charge so-called renewable/maintenance/payback cost to run the plant. Therefore, the linear cost function has been implemented for RE generations (REGs). Two cases have been considered based on the cost of REGs, one is no cost for REGs and other is linear cost functions for REGs. The popular optimization technique known as particle swarm optimization (PSO) has been adopted to solve the ELDPs. A test system made of IEEE 30-bus system, solar PV, and wind generator has been considered to investigate the strength of the proposed approach. The simulation results show that the saving of 63.829, 74.99, and 182.937 $/h in one case and the saving of 139.53, 150.468, and 358.883 $/h in another case in the generation cost for a load demand of 283.4 MW are remarkable, when only solar PV, only wind and both solar PV and wind respectively, are in operation.

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来源期刊
AUTOMATIC CONTROL AND COMPUTER SCIENCES
AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.70
自引率
22.20%
发文量
47
期刊介绍: Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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