考虑风电不确定性的坡道约束经济调度

Mengshi Li, T. Ji, Qinghua Wu, P. Wu
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引用次数: 2

摘要

本文旨在利用细菌群算法(BSA)解决风电经济调度问题。风力发电机组在电力系统中的大规模安装对传统的经济调度提出了挑战。随着风电装机容量的增加,风电场的坡道容量与不确定的风速相关,而不是像传统发电机那样具有固定的比值。因此,经济调度的斜坡约束可以推广为与风速相关的概率。为了解决约束优化问题,本文通过选择合适的控制变量来控制动力系统,从而采用BSA来降低燃料成本。该方法已通过IEEE 30总线测试系统进行了验证。仿真结果表明,该方法显著降低了燃油成本,满足斜坡约束。
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Economic dispatch with ramp constraints concerning wind power uncertainty
This paper aims to solve an economic dispatch problem concerning wind power using a Bacterial Swarm Algorithm (BSA). The massive installation of the wind turbines in power system presents a challenge for the conventional economic dispatch. With increasing wind power penetration, the ramp capability of wind farms correlates with the uncertain wind speed rather than a fix ratio as conventional generators. Therefore, the ramp constraints of the economic dispatch can be extended to a probability which is related to the wind speed. In order to solve the constrained optimization problem, this paper employs the BSA to reduce the fuel cost by selecting suitable control variables governing the power systems. The proposed method has been evaluated using an IEEE 30-bus test system. Simulation results indicate that the proposed method significantly reduces the fuel cost and satisfies the ramp constraints.
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