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An Approximate Dynamic Programming Approach for Wind Power Dispatch in Wind Farms

机译:风电场风电调度的近似动态规划方法

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With appropriate control based on predicted data of renewable energy sources, battery energy storage systems (BESS) can increase the dispatchability of wind and solar power. In a deregulated electricity market, proper charge and discharge decisions of BESS made at different price periods are likely to increase the profit for renewable power plants. In this paper, we propose an energy trading strategy for wind farms with BESS to control the actual power sold to the electric grid. To maximize the income and minimize the battery lifetime consumption, an approximate dynamic programming algorithm is produced to solve the optimal charge and discharge actions of the BESS within a future period. The rolling horizon approach is utilized, and the algorithm works with both short-term and long-term predicted data that are updated in every control step. The use of an approximate technique is to avoid the long computation time resulted from a large-scale BESS, and to meet time constraints in the rolling horizon approach. The algorithm is tested with practical wind power and electricity price data.
机译:通过基于可再生能源的预测数据进行适当控制,电池储能系统(BESS)可以提高风能和太阳能的可调度性。在放松管制的电力市场中,在不同的价格时段做出的BESS正确的充放电决定可能会增加可再生能源发电厂的利润。在本文中,我们提出了一种利用BESS的风电场能源交易策略,以控制出售给电网的实际功率。为了使收入最大化并使电池寿命消耗最小化,将产生一种近似的动态编程算法,以解决BESS在未来一段时间内的最佳充电和放电动作。利用了滚动视野方法,该算法可在每个控制步骤中更新的短期和长期预测数据中使用。近似技术的使用是为了避免大规模BESS导致的计算时间过长,并满足滚动视界方法中的时间限制。该算法已通过实际的风力和电价数据进行了测试。

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