Heuristic control of power consumption by up to 1000 V electrical loads at mining enterprises

O. Sinchuk, M. V. Rogoza, O. Y. Mykhailenko, D. Kobeliatskyi, V. Fedotov
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Abstract

Purpose. To develop a method for synthesizing the structure and algorithm of the system for automated control of power consumption by up to 1000 V electrical receivers at mining enterprises with iron ore underground mining methods. This enables direct control of the load connection to the industrial power grid to ensure minimum power costs depending on its cost per day ahead. Methodology. The problem of controlling power consumption of electrical receivers at iron ore underground mines is formalized as a binary form of mixed integer programming. To solve it, a binary implementation of the heuristic genetic algorithm is used. The mathematical modeling method analyzes the impact of genetic algorithm settings, such as the number of phenotypes in the population, the number of elite phenotypes that pass unchanged to the next generation, and the method of phenotype crossover on its quality. Findings. As a result of the research, it is found that the most effective way to control the process of power consumption based on an evolutionary genetic algorithm is to use the Laplace crossover function and keep the percentage of elite phenotypes in the population at 10 %. Moreover, at the smallest population size, the best accuracy is observed when using the Laplace function, while at one- and two-point crossover functions, it worsens, but not significantly (no more than 0.2 %). However, as the number of elite phenotypes increases, the duration of the evolutionary search in the control process is reduced by almost a factor of two in the case of one- and two-point crossovers. Originality. For the first time, the structure of a heuristic system for automated control of power consumption by underground electrical receivers with a supply voltage of up to 1000 V at iron ore underground mines has been developed on the basis of an evolutionary genetic algorithm. Depending on the designed volumes of ore production and the daily power cost per day, this allows determining the optimal power load schedule of underground distribution substations in advance, which, subject to the accepted limits on hourly and daily power, minimizes the cost of purchasing power, and thus reduces the cost of the final product. Practical value. The architecture of a heuristic system for controlling power consumption by electrical receivers with a voltage of up to 1000 V based on an evolutionary genetic algorithm is developed and recommended when optimizing the power load schedule of transformer substations of mining and metallurgical enterprises, in particular, of iron ore underground mines operating in this voltage class.
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矿业企业高达 1000 V 电力负载耗电量的启发式控制
目的开发一种合成系统结构和算法的方法,用于自动控制采用铁矿石地下开采方法的采矿企业中电压高达 1000 V 的电力接收器的耗电量。这样就能直接控制与工业电网的负载连接,确保根据每天的成本提前将电力成本降至最低。方法。控制铁矿地下矿井电力接收器功耗的问题被形式化为混合整数编程的二进制形式。为了解决这个问题,采用了启发式遗传算法的二进制实现方法。数学建模方法分析了遗传算法设置对其质量的影响,如种群中的表型数量、不变传递给下一代的精英表型数量以及表型交叉方法。研究结果研究结果发现,基于进化遗传算法控制功耗过程的最有效方法是使用拉普拉斯交叉函数,并将种群中精英表型的百分比保持在 10%。此外,在种群规模最小时,使用拉普拉斯函数的精确度最高,而使用单点和两点交叉函数时,精确度会降低,但降低幅度不大(不超过 0.2%)。不过,随着精英表型数量的增加,在单点和两点交叉的情况下,控制过程中进化搜索的持续时间几乎缩短了两倍。独创性在进化遗传算法的基础上,首次开发了一种启发式系统结构,用于自动控制铁矿地下矿井供电电压高达 1000 V 的地下电力接收器的耗电量。根据设计的矿石产量和每天的电力成本,该系统可以提前确定地下配电变电站的最佳电力负荷计划,在符合公认的每小时和每天电力限制的情况下,最大限度地降低购买电力的成本,从而降低最终产品的成本。实用价值。在优化矿业和冶金企业(尤其是在该电压等级下运行的铁矿地下矿井)变电站的电力负荷计划时,推荐使用基于进化遗传算法的启发式系统架构来控制电压高达 1000 V 的电力接收器的电力消耗。
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CiteScore
1.70
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发文量
148
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