The Arithmetic Optimization Algorithm for Optimal Energy Resource Planning

A multi-objective framework for distributed energy resources planning and storage management

“…Feeder data of the test systems are taken from [41,42], and [43]. Reliability data, load types, and the number of customers at each bus are extracted from Table 11 in the Appendix for 141bus system, [44,45] for 33-bus and 69-bus system. Optimization period is selected as 72 h (24 h for each representative summer, winter and spring/fall day) to account the seasonal effects.…”

A Decentralized Control Strategy for Voltage Regulators and Energy Storage Devices in Active Unbalanced Distribution Systems

“…The near-optimal tap position of VRs is determined using the proposed advanced arithmetic optimizer (AAO) algorithm. Besides the optimal control strategy for the VRs and ESDs, the AAO algorithm is proposed based on the improvement of the convergence speed of the arithmetic optimization algorithm (AOA) [13] and adapting the algorithm to solve the specific problem of DNs' voltage control strategy. Compared to the cited references, the proposed algorithm enhances the search capability of the AOA and improves its suitability for dealing with mixedinteger nonlinear programming (MINLP) problems.…”

“…The proposed optimization algorithm for solving the problem of unbalanced networks is tested on the IEEE 13-bus and the IEEE 123-bus systems with a high integration of PV units. The optimization result found by the presented AAO method are compared to the AOA [14] method, grey wolf optimization (GWO) [15], and particle swarm optimization (PSO) [13] in terms of convergence speed and the quality of the solutions.…”

“…AAO is a modified version of the Arithmetic optimization algorithm (AOA) [13] and it aims to enhance the search capability of the AOA at finding good approximations of the global minimum solution. The main arithmetic operators (addition, subtraction, multiplication, and division) are the primary motivation of the AAO algorithm formulation.…”

“…Compared to the AOA formulations, both exploitation and a exploration phases methodology were modified to improve the global search capability in the first iterations and improve the exploitation in the last iterations. Besides the improvements in the exploitation and a exploration behavior, AAO used a new boundary check method called mirroring correction [13] for checking the variables constraints and also a dynamic stopping criterion for stooping optimization process [4].…”