Received: December 30, 2021. Revised: January 19, 2022. 329 International Journal of Intelligent Engineering and Systems, Vol.15, No.2, 2022 DOI: 10.22266/ijies2022.0430.30 Coordinated Optimal Placement of Energy Storage System and Capacitor Bank Considering Optimal Energy Storage Scheduling for Distribution System Using Mixed-Integer Particle Swarm Optimization Korawitch Kaiyawong 1 Keerati Chayakulkheeree 1 * 1 School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology, Nakhonratchasima, Thailand * Corresponding author’s Email: keerati.ch@sut.ac.th Abstract: This paper proposes a mixed-integer particle swarm optimization (MIPSO) for coordinated optimal placement of energy storage system (ESS) and capacitor bank (CB). In the propose method, optimal ESS scheduling (OESSS) is solved by particle swarm optimization (PSO), as a subproblem, the optimal coordinated placement (COP) for ESS and CB, simultaneously. The distribution system annual loss minimization (DSALM) is used as the objectives of COP problem. The proposed method was tested with the IEEE 33-bus radial distribution test system. The results demonstrated that the proposed method is successful and robust in minimizing system losses, which loss saving of 35.12% when compare to the based case, which is the best solution among other existing methods. Keywords: Optimal placement, Optimal scheduling, Minimize power loss, Energy storage system, Capacitor bank. 1. Introduction Nowadays, in distribution system, day-to-day fluctuations in power consumption. distributed high, resulting in significant power loss in the system. Therefore, a reduction in power loss and improved voltage are very important for the electrical distribution power systems (EDPs) to reduce energy consumption and operating costs. This problem can be solved by installing capacitor bank (CB) to compensate for reactive power and power consumption variations that can be managed with an energy storage system (ESS). A number of methods have been presented with the purpose of reducing power loss and improving voltage in electrical power systems. such as, distribution system reconfiguration using modified particle swarm optimization (MPSO) [1], Soft Open Point (SOP) which is a type of power electrical component which can be used to replace traditional switches or normally open points (NOP) in network distribution was proposed in [2]. In [3], parameter improved particle swarm optimization (PIPSO) is solver for optimal sizing and placement of a distributed generation (DG), this paper integrating real power supporting of DG with IEEE 33 bus and 69 bus radial distribution network. CB has been used to solve optimal dispatch problem for reactive power in [4]. Particle swarm optimization (PSO) was utilized to test a power system to reduction in a power loss in [5]. In other system of this challenge, [6] calculated the operation of CB and tap-changing transformer using the Newton-Raphson load flow technique. When minimizing power loss is integrated with other aims, such as controlling voltage drop in the electrical system, fuzzy multi-objective optimization has been used genetic algorithms (GA) for control device in power system [7]. These methods, aimed at minimizing real power loss. Optimal placement of CB is a method of locating the proper CB installation for the electrical system's best benefit. The capacitor placement challenge is a very well-known topic that has been discussed by a number of authors in the past, such as, genetic algorithm method [8, 9], the sperm whale algorithm (SWA) [10], moth-flame optimization algorithm [11] and complex calculation methods like fuzzy logic