This paper bestows a new swarm intelligence approach, Squirrel Search Algorithm (SSA) to solve Economic Load Dispatch (ELD) of the thermal unit by addressing the valve point loading effects and multiple fuel options. SSA inspires the foraging behavior of squirrels which is based on dynamic jumping and gliding strategies. The main intention of the ELD problem is to minimize the total generation cost of units while assuring various system constraints. Renovate strategy and selection rules are used in the SSA algorithm to handle the constraints appropriately. The practicability of the proposed algorithm is tested on six different power test systems having different sizes and intricacies. Simulation results ascertain that the proposed SSA approach outperforms the other existing heuristic optimization techniques in terms of solution quality, robustness, and computational efficiency. Consequently, the proposed SSA can be an efficient approach for solving the ELD problems with valve point loading impacts and multi-fuel options.

本文提出了一种新的群智能方法，即松鼠搜索算法（SSA），通过解决阀点负载影响和多种燃料选择来解决热力单元的经济负荷分配（ELD）。SSA激发了基于动态跳跃和滑行策略的松鼠的觅食行为。ELD问题的主要目的是在确保各种系统约束的同时，将单元的总发电成本降至最低。SSA算法中使用了更新策略和选择规则来适当处理约束。在具有不同大小和复杂度的六个不同功率测试系统上测试了所提出算法的实用性。仿真结果确定，所提出的SSA方法在解决方案质量，鲁棒性，和计算效率。因此，提出的SSA可能是解决ELD问题的有效方法，该问题具有阀点负载影响和多种燃料选择。