Optimal economic load dispatch based on wind energy and risk constrains through an intelligent algorithm

Sina Ghaffari, G. Aghajani, A. Noruzi, Hadi Hedayati Mehr
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引用次数: 7

Abstract

This article focus on optimal economic load dispatch based on an intelligent method of shark smell optimization (SSO). In this problem, the risk constrains has been considered which has root in uncertainity and unpredictable behavior of wind power. Regarding to increasing of this clean energy in power systems and un-dispatchable behavior of wind power, its conditional value at risk index considered in this article which consists of loss from load and “spilling” wind energy connected with unpredictable imbalances among generation and load. This problem has been considered as an optimization problem based on SSO that evaluate the balance between cost and risk. This algorithm is based on distinct shark smell abilities for localizing the prey. In sharks' movement, the concentration of the odor is an important factor to guide the shark to the prey. In other words, the shark moves in the way with higher odor concentration. This characteristic is used in the proposed SSO algorithm to find the solution of an optimization problem. Effectiveness of the proposed method has been applied over 30-bus power system in comparison with other techniques. © 2016 Wiley Periodicals, Inc. Complexity, 2016
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基于风能和风险约束的智能负荷优化经济调度
本文研究了基于鲨鱼气味优化(SSO)的智能负荷优化经济调度方法。在此问题中考虑了风险约束,其根源在于风电的不确定性和不可预测性。针对这一清洁能源在电力系统中的不断增加和风电的不可调度行为,本文考虑了风电的条件风险值指标,该指标由负荷损失和“外溢”风能组成,并与发电与负荷之间不可预测的不平衡有关。该问题被认为是一个基于单点登录的成本与风险平衡的优化问题。该算法基于鲨鱼独特的嗅觉能力来定位猎物。在鲨鱼的运动中,气味的集中是引导鲨鱼找到猎物的重要因素。换句话说,鲨鱼以气味浓度较高的方式移动。所提出的单点登录算法利用这一特性寻找优化问题的解。与其他技术相比,该方法已在30母线电力系统中得到了有效的应用。©2016 Wiley期刊公司复杂性,2016
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