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<p>In power system economics, hydrothermal scheduling is essential because it optimizes the hourly output of producing units with the goal of minimizing the overall production cost. However, a number of uncertainty limitations related to both hydro and thermal units make this scheduling procedure a very difficult and nonlinear optimization issue. However, the high frequency of outages and the sporadic nature of energy sources may have a detrimental effect on the grid’s overall stability. Programs for demand-side management (DSM) address these problems by cutting costs and improving power system security. This article introduces an order characterized load-shifting policy (OCLSP) to solve short-term hydrothermal scheduling problem. This technique is easy to implement and efficiently lowers peak demand as well as load factor. To minimize the parameters, crayfish optimization algorithm (COA) is implemented. Three test systems, each with varying numbers of hydro and thermal units, are analyzed. After applying the load-shifting policy to restructure the load demand, a reduction in generation cost is observed in all three cases. Additionally, the load factor improved by 5.41, 7.01, and 7.30% for test systems 1, 2, and 3, respectively. Correspondingly, peak demand decreased by 5.12, 6.54, and 6.90% across the three test systems compared to base load profile.</p>

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Adaptive load sifting strategy for short-term hydrothermal energy scheduling using crayfish optimization algorithm

  • 期刊论文

  • 发表日期：

    2026年2月16日

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  • Sujoy Das,
  • Bishwajit Dey,
  • Laishram Khumanleima Chanu

摘要

In power system economics, hydrothermal scheduling is essential because it optimizes the hourly output of producing units with the goal of minimizing the overall production cost. However, a number of uncertainty limitations related to both hydro and thermal units make this scheduling procedure a very difficult and nonlinear optimization issue. However, the high frequency of outages and the sporadic nature of energy sources may have a detrimental effect on the grid’s overall stability. Programs for demand-side management (DSM) address these problems by cutting costs and improving power system security. This article introduces an order characterized load-shifting policy (OCLSP) to solve short-term hydrothermal scheduling problem. This technique is easy to implement and efficiently lowers peak demand as well as load factor. To minimize the parameters, crayfish optimization algorithm (COA) is implemented. Three test systems, each with varying numbers of hydro and thermal units, are analyzed. After applying the load-shifting policy to restructure the load demand, a reduction in generation cost is observed in all three cases. Additionally, the load factor improved by 5.41, 7.01, and 7.30% for test systems 1, 2, and 3, respectively. Correspondingly, peak demand decreased by 5.12, 6.54, and 6.90% across the three test systems compared to base load profile.