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Solution of Economic and Environmental Power Dispatch Problem of an Electrical Power System using BFGS-AL Algorithm

机译:使用BFGS-AL算法解决电力系统的经济环境权力派出问题解决方案

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This paper presents a deterministic optimization strategy to solve the economic-environmental power dispatch (EEPD) problem of an electrical power system, using a Broyden Fletcher Goldfarb Shanno based on the augmented Lagrangian (BFGS-AL) algorithm. This problem is a nonlinear constrained multi-objective optimization. The objectives of this optimization are minimized the total fuel cost and emission amount for thermal generators while satisfying electric power systems equality and inequality constraints. The proposed approach is applied on the standard IEEE 30 bus test system, where the power transmission losses are taken into account. Simulation results proved that the proposed approach gives better-quality solution in terms of accuracy and convergence to the best compromise solution compared to other deterministic and meta-heuristic optimization techniques.
机译:本文介绍了解决电力系统的经济环境权力调度(EEPD)问题的确定性优化策略,基于增强拉格朗日(BFGS-AL)算法,使用泡沫浮雕碎片金粪牧师。这个问题是非线性约束的多目标优化。该优化的目的是最小化热发电机的总燃料成本和排放量,同时满足电力系统平等和不等式约束。所提出的方法应用于标准IEEE 30总线测试系统,其中考虑了电力传输损耗。仿真结果证明,与其他确定性和元启发式优化技术相比,该方法在准确性和收敛方面提供了更好的质量解决方案。

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