Contemporary distribution networks can be seen with diverse dispatchable and nondispatchable energy resources. The coordinated scheduling of these dispatchable resources, together with nondispatchable resources, can provide several technoeconomic and social benefits. Since battery energy storage systems (BESSs) and microturbine units (MT units) are capital-intensive, a thorough investigation of their coordinated scheduling under the economic criterion will be a challenging task while considering dynamic electricity prices and uncertainties of renewable power generation and load demand. This paper proposes a comprehensive methodological framework for optimal coordinated scheduling of BESSs with MT unit considering existing renewable energy resources and dynamic electricity prices to maximize the daily profit function of the utility by employing a recently explored modified African buffalo optimization algorithm. The key attributes of the proposed methodology are comprised of mean price-based adaptive scheduling embedded within a decision mechanism system (DMS) to maximize arbitrage benefits. DMS keeps track of system states as a priori, thus resulting in an artificial intelligence-based solution technique for sequential optimization. Further, a novel concept of fictitious charges is also proposed to restrict the counterproductive operational management of BESSs. The proposed model and method are demonstrated on the 33-bus distribution system, and the obtained results verify the effectiveness of the proposed methodology.

中文翻译：

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具有电池储能和价格响应需求的主动配电系统中的最优协调能源管理

可以看到现代分销网络具有多种可调度和不可调度的能源。这些可调度资源与不可调度资源的协调调度可以提供多种技术经济和社会效益。由于电池储能系统（BESS）和微型涡轮机（MT单元）是资本密集型的​​，因此在考虑动态电价以及可再生能源发电和负荷需求的不确定性的情况下，在经济标准下彻底研究其协调调度将是一项艰巨的任务。 。本文提出了一种综合的方法框架，该方法框架考虑了现有的可再生能源和动态电价，采用MT单元优化BESS的最佳协调调度，从而通过采用最近探索的改进的非洲水牛优化算法来最大化公用事业的每日利润函数。所提出方法的关键属性包括嵌入在决策机制系统（DMS）中的基于均价的自适应调度，以最大化套利收益。DMS先验地跟踪系统状态，从而产生了一种用于顺序优化的基于人工智能的解决方案技术。此外，还提出了虚拟收费的新概念，以限制BESS的适得其反的运营管理。