Squirrel Search Optimizer: Nature Inspired Metaheuristic Strategy for Solving Disparate Economic Dispatch Problems

Abstract

In this paper, a new meta-heuristic algorithm, called Squirrel Search Optimizer (SSO) is applied to solve various types of economic load dispatch (ELD) problems. The SSO mimics the foraging behavior of squirrels which is based on the dynamic jumping and gliding strategies. In SSO algorithm, predator presence behavior and a seasonal monitoring condition are employed to increase the search ability of the algorithm, and to balance the exploitation and exploration. The key idea of the suggested approach is to determine the optimal generation scheduling by minimizing total generation cost of units while satisfying various constraints such as power balance constraint, prohibited operating zones (POZ), ramp rate constraints and operating limits of generators. The different generating unit's characteristics, quadratic fuel cost function, non-convex fuel cost function and multiple fuel options (MFO) are also considered. The feasibility of the proposed algorithm is tested on four different power test systems having different sizes and intricacies. The results are examined in terms of both solution quality and the computational efficiency, and compared with the other approaches in the literature. The comparisons prove the robustness and effectiveness of the proposed algorithm and show that it could be used as a consistent optimizer for solving various ELD problems.

Optimal backstepping controller for controlling DC motor speed

“…The squirrel search algorithm (SSA) was a novel optimization method proposed by Jain et al [20], it assumes that (n) flying squirrels have (n) deciduous trees in the search space, each squirrel have one tree and the manner of searching is done individually, tree types is classified into three (normal, oak or acorn nuts and hickory) and the final assumptions is that three trees is classified as oak tree and one as hickory. The location vector for each ith flying squirrel is defined as follows [21]- [23]:…”

Pelican Optimization Algorithm for Optimal Demand Response in Islanded Active Distribution Network Considering Controllable Loads

“…On the other hand, as per the free lunch theorem (NFLT), there is no such algorithm for all kinds of optimization problems for proving global optima. In this regard, the computational efficiency of POA should be compared to that of other recent algorithms, such as the multi leader optimizer (MLO) [31], the three influential members based optimizer (TIMBO) [32], the randomly selected leader based optimizer (RSLBO) [33], the squirrel search optimizer (SSO) [34], the puzzle optimization algorithm (POA) [35], and the ring toss game-based optimization algorithm (RTGBO) [36].…”

Retired Electric Vehicle Battery for Optimal Dynamic Economic Dispatch Against the Intermittent of Photovoltaic Power Output

“…In [6], the intermittent of the wind power output was studied for the DED problem and solved using a robust optimization model. Artificial intelligence method has been successfully applied for solving economic load dispatch problems such as chaotic social group optimization (CSGO) [7], squirrel search optimizer (SSO) [8], orthogonal particle swarm optimization [9], and water wave optimization algorithm (WWOA) [10]. In [7], CSGO has been applied to solve the economic dispatch problem with multiple fuel sources.…”

“…The efficacy of this technique is examined by using four tested systems (10-units, 20-units, 30units, and 40-units). In [8], the SSO algorithm was utilized to solve various types of economic load dispatch problems by minimizing the total generation cost of units while satisfying various constraints such as power balance constraints, prohibited operating zones, ramp rate constraints, and operating limits of generators. In [9], the effect of load demand management for the DED problem was analyzed.…”

“…In this study, the planning issue comprises the total fuel cost function with valve-point loading effect and the transmission power losses. All proposed techniques [5][6][7][8][9][10] have shown sophisticated results in solving the DED problem. Moreover, the methods above require more experiments and statistical analysis to obtain their best performance due to being stochastically solved.…”