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Reliability centered planning for distributed generation considering wind power volatility

机译：考虑风电波动性的以可靠性为中心的分布式发电规划

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This paper investigates a stochastic planning model to minimize the lifecycle cost of distributed generation (DG) systems under the energy reliability criterion, namely the loss-of-load probability. In particular, our study focuses on the DG system penetrated by renewable wind technology. The optimization is formulated to determine the wind turbine capacity and their placement in the DG system with the intent to minimize the capital, operational and environmental costs. Statistical moments including mean and variance are utilized to characterize the wind power volatility and the load uncertainty. Genetic algorithm combined with heuristic search is used to find the best sitting and sizing of the distributed energy recourses. Our study is among the first attempts in the literature to model and optimize DG system based on continuous probabilistic theory. The moment methods are shown to be effective in characterizing the stochastic behavior of wind power and load dynamics. Case studies are provided to demonstrate the application and performance of the planning method.
机译：本文研究了一种随机计划模型，以在能量可靠性准则下将分布式发电（DG）系统的生命周期成本降至最低，即负载损失概率。特别是，我们的研究集中在可再生风能技术渗透的DG系统上。制定了优化方案，以确定风力涡轮机的容量及其在DG系统中的位置，以最大程度地降低资金，运营和环境成本。利用包括均值和方差在内的统计矩来表征风能波动性和负荷不确定性。遗传算法与启发式搜索相结合，用于找到分布式能源资源的最佳位置和规模。我们的研究是文献中基于连续概率理论对DG系统进行建模和优化的首次尝试。结果表明，矩量法可以有效地表征风能和负荷动力学的随机行为。提供了案例研究来说明计划方法的应用和性能。

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