Conventional unit commitment problem (UCP) consists of thermal generating units and its participation schedule, which is a stimulating and significant responsibility of assigning produced electricity among the committed generating units matter to frequent limitations over a scheduled period view to achieve the least price of power generation. However, modern power system consists of various integrated power generating units including nuclear, thermal, hydro, solar and wind. The scheduling of these generating units in optimal condition is a tedious task and involves lot of uncertainty constraints due to time carrying weather conditions. This difficulties come to be too difficult by growing the scope of electrical power sector day by day, so that UCP has connection with problem in the field of optimization, it has both continuous and binary variables which is the furthermost exciting problem that needs to be solved. In the proposed research, a newly created optimizer, i.e., Harris Hawks optimizer (HHO), has been hybridized with sine–cosine algorithm (SCA) using memetic algorithm approach and named as meliorated Harris Hawks optimizer and it is applied to solve the photovoltaic constrained UCP of electric power system. In this research paper, sine–cosine Algorithm is used for provision of power generation (generating units which contribute in electric power generation for upload) and economic load dispatch (ELD) is completed by Harris Hawks optimizer. The feasibility and efficacy of operation of the hybrid algorithm are verified for small, medium power systems and large system considering renewable energy sources in summer and winter, and the percentage of cost saving for power generation is found. The results for 4 generating units, 5 generating units, 6 generating units, 7 generating units, 10 generating units, 19 generating units, 20 generating units, 40 generating units and 60 generating units are evaluated. The 10 generating units are evaluated with 5% and 10% spinning reserve. The efficacy of the offered optimizer has been verified for several standard benchmark problem including unit commitment problem, and it has been observed that the suggested optimizer is too effective to solve continuous, discrete and nonlinear optimization problems.

中文翻译：

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改良后的Harris Hawks优化器，用于光伏应用中的组合机组承诺问题

常规机组承诺问题（UCP）由火力发电机组及其参与计划组成，这是激励性的重大责任，即在计划的时间段内将承诺的发电机组中的发电分配给频繁的限制，以实现最低的发电价格。但是，现代电力系统由各种集成发电设备组成，包括核能，热能，水力，太阳能和风能。这些发电机组在最佳状态下的调度是一项繁琐的工作，并且由于携带时间的天气状况而涉及许多不确定性约束。通过日益扩大电力行业的范围，这些困难变得太困难了，因此，UCP与优化领域的问题有关，它具有连续变量和二进制变量，这是需要解决的最令人兴奋的问题。在拟议的研究中，使用模因算法方法将一种新创建的优化器，即Harris Hawks优化器（HHO）与正弦余弦算法（SCA）混合，并命名为改良的Harris Hawks优化器，并将其应用于解决光伏约束问题。电力系统的UCP。在本研究论文中，正弦余弦算法用于提供发电（有助于上载发电的发电单元），而经济负荷分配（ELD）由Harris Hawks优化器完成。对于夏季和冬季考虑可再生能源的中小型电力系统和大型系统，验证了混合算法的可行性和有效性。并找到了节省发电成本的百分比。对4个发电机组，5个发电机组，6个发电机组，7个发电机组，10个发电机组，19个发电机组，20个发电机组，40个发电机组和60个发电机组的结果进行评估。对这10个发电机组进行了5％和10％的纺纱储备评估。已针对包括单元承诺问题在内的多个标准基准问题验证了所提供优化器的有效性，并且已观察到所建议的优化器对于解决连续，离散和非线性优化问题过于有效。评估了40个发电机组和60个发电机组。对这10个发电机组进行了5％和10％的纺纱储备评估。已针对包括单元承诺问题在内的多个标准基准问题验证了所提供优化器的有效性，并且已观察到所建议的优化器对于解决连续，离散和非线性优化问题过于有效。评估了40个发电机组和60个发电机组。对这10个发电机组进行了5％和10％的纺纱储备评估。已针对包括单元承诺问题在内的多个标准基准问题验证了所提供优化器的有效性，并且已观察到所建议的优化器对于解决连续，离散和非线性优化问题过于有效。