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Method for a Parallel Solution of a Combined Economic Emission Dispatch Problem

机译:组合经济排放调度问题的并行求解方法

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The power system simulation software tools are traditionally designed for serial codes and optimized using single-processor computers. They are inadequate in terms of computational efficiency and execution time for the ever-increasing complexity of the power grid. Due to the above-mentioned sequential computing demerits, this paper used MATLAB data parallelism message passing interface software to execute the Lagrange's and Particle Swarm Optimization (PSO) algorithms in parallel with multiple processor units with different and large data sets for the solution of the Combined Economic Emission Dispatch (CEED) problem. The two important advantages of using parallel computing approach to solve the power system economic dispatch problem are 1) to increase the efficiency (solution quality) and 2) to reduce the execution time (speed-up) of the parallelization process for the CEED problem solution. The comparison between the Lagrange's and PSO data-parallel solution quality and execution time is presented for the CEED problem for Institute of Electrical and Electronic Engineers (IEEE) 30 bus and IEEE 118 bus systems. The paper contributes to the on-line real-time market analyses of the deregulated power system, which need improved solution quality and a fast computation process to solve the power system energy management (CEED) problems for proper discussion and decision making at the control center level.
机译:电力系统仿真软件工具传统上是为串行代码设计的,并使用单处理器计算机进行了优化。它们在计算效率和执行时间方面不足以应对不断增加的电网复杂性。由于上述顺序计算的缺点,本文使用MATLAB数据并行消息传递接口软件,与具有不同数据量和较大数据集的多个处理器单元并行执行Lagrange和粒子群优化(PSO)算法,以解决组合式解决方案。经济排放调度(CEED)问题。使用并行计算方法解决电力系统经济调度问题的两个重要优点是:1)提高效率(解决方案质量)和2)减少CEED问题解决方案并行化过程的执行时间(加速)。 。针对电气和电子工程师协会(IEEE)30总线和IEEE 118总线系统的CEED问题,提出了Lagrange和PSO数据并行解决方案质量和执行时间之间的比较。本文为解除管制的电力系统的在线实时市场分析做出了贡献,该分析需要改进的解决方案质量和快速的计算过程来解决电力系统的能源管理(CEED)问题,以便在控制中心进行适当的讨论和决策。水平。

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