利用人工蜂群算法优化经济环境电力调度

Elia Erwani Hassan, Hanan Izzati Mohd Noor, Mohd Ruzaini Bin Hashim, M. F. Sulaima, N. Bahaman
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引用次数: 0

摘要

如今,全球大多数发电厂主要使用天然气、煤炭和石油等化石燃料作为能源再生的主要资源。经济环境电力调度(EEPD)问题的新术语是发电机和化石燃料排放的总成本最小,以解决大气污染问题。因此,重要的目标函数被确定为最小化发电成本、最少量的污染物排放和最低的系统损耗。 作为替代方案,使用 MATLAB 编程环境,在标准 IEEE 26 总线系统和 IEEE 57 总线系统的电力系统中分别采用人工蜂群 (ABC) 算法来解决 EEPD 问题。根据简单的数学分析,如与所得结果的简单偏差及其百分比,对所引入算法的性能进行了测量。从数学测量结果来看,与使用牛顿-拉斐尔森方法的梯度法相比,ABC 算法在短计算时间内对每个已确定的单一目标函数都有所改进。
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Optimal economic environmental power dispatch by using artificial bee colony algorithm
Today, most power plants worldwide use fossil fuels such as natural gas, coal, and oil as the primary resource for energy reproduction primarily. The new term for economic environmental power dispatch (EEPD) problems is on the minimum total cost of the generator and fossil fuel emissions to address atmosphere pollution. Thus, the significant objective functions are identified to minimize the cost of generation, most minor emission pollutants, and lowest system losses individually.  As an alternative, an Artificial Bee Colony (ABC) swarming algorithm is applied to solve the EEPD problem separately in the power systems on both standard IEEE 26 bus system and IEEE 57 bus system using a MATLAB programming environment. The performance of the introduced algorithm is measured based on simple mathematical analysis such as a simple deviation and its percentage from the obtained results. From the mathematical measurement, the ABC algorithm showed an improvement on each identified single objective function as compared with the gradient approach of using the Newton Raphson method in a short computational time.
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