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A Linearized Optimization Method for Distributed Generation Planning Studies

机译:分布式发电计划研究的线性优化方法

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Utilizing renewable energy sources as distributed generation (DG) reduces the pollutant emissions of conventional fossil-fueled generation. Optimized planning is required to prevent serious technical issues resulting from poor implementation. This paper presents an optimization scheme which simplifies the problem by using linearization. Power flow equations are linearized at steady-state operating points, and sensitivity coefficients are calculated for constraints such as voltage and distribution system flow limits. Linear programming (LP) finds the optimal capacities of DG units. Compared to commonly used artificial intelligence (AI) techniques which are computationally expensive, the proposed method is more efficient for finding the optimal capacity of DGs in large distribution systems. The proposed framework is appropriate for planning applications in which efficiency and accuracy are prioritized.
机译:将可再生能源用作分布式发电(DG)可减少传统化石燃料发电的污染物排放。需要优化规划,以防止由于实施不当而导致的严重技术问题。本文提出了一种优化方案,该方案通过使用线性化来简化问题。在稳态工作点将潮流方程线性化,并针对诸如电压和配电系统流量限制之类的约束条件计算灵敏度系数。线性编程(LP)找到DG单元的最佳容量。与在计算上昂贵的常用人工智能(AI)技术相比,该方法在大型配电系统中查找DG的最佳容量更有效。提议的框架适用于计划优先考虑效率和准确性的应用程序。

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