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Dispatch of distributed energy resources to provide energy and reserve in smart grids using a particle swarm optimization approach

机译:使用粒子群优化方法分配分布式能源,以在智能电网中提供能量和储备

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The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.
机译:智能电网概念是未来电力系统(即配电级别)中的关键问题,在这些系统的运行和规划中存在深切关注。人们认识到电力系统和电力市场在技术和经济运行方面的多种优势和收益。需求响应和分布式发电资源的集成不断增加,所有这些大多数都具有小规模的分布式特征,因此需要聚合诸如Virtual Power Player之类的实体。在智能电网运营的背景下,运营业务模型变得更加复杂。考虑时间约束,可以使用计算智能方法为资源调度问题提供合适的解决方案。本文提出了一种用于需求响应和分布式发电联合调度的方法,以通过运营配电网络的虚拟电力公司提供能源和储备。最佳计划可以最大程度地降低运营成本,它是使用粒子群优化方法获得的,与确定性方法作为参考方法进行了比较。该方法适用于具有32个中压用户和66个分布式发电单元的33总线配电网络。

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