University of Isfahan Computational Intelligence in Electrical Engineering 2821-0689 14 3 2023 09 23 Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory 95 106 27657 10.22108/isee.2023.134689.1578 FA Houman Bastami Department of Electrical Engineering, Faculty of Engineering, Lorestan University, Khorramabad, Iran Mahmood Reza Shakarami Professor, Department of Electrical Engineering, Faculty of Engineering, Lorestan University, Khorramabad, Iran Meysam Doostizadeh Assistant Professor, Department of Electrical Engineering, Faculty of Engineering, Lorestan University, Khorramabad, Iran Journal Article 2022 08 10 In this paper, a three-level framework is proposed to determine the optimal scheduling of a Multi-Area Active Distribution Network in the presence of inter-area Soft Open Points (SOPs). In this framework, the uncertainty of renewable generation and forecasted demand is modeled using information gap decision theory in a risk-averse manner. Coordinated scheduling of Controllable Distributed Generators (CDGs) and SOPs, inter-area energy exchanges and energy trading with upstream network considering the uncertainties are the contribution of the presented method. To improve the computational efficiency and to achieve the optimal solution, the scheduling problem is modeled as a second-order conic programming in which the operational and security constraints of the network, CDG limitations, and operational constraints of SOPs are accurately modeled and the problem is solved by executing CPLEX solver in MATLAB environment. A case study on IEEE 33-bus test system showcases the superiority of the proposed model compared to meta-heuristic algorithms such as particle swarm optimization, genetic algorithm, and gravitational search algorithm. In this paper, a three-level framework is proposed to determine the optimal scheduling of a Multi-Area Active Distribution Network in the presence of inter-area Soft Open Points (SOPs). In this framework, the uncertainty of renewable generation and forecasted demand is modeled using information gap decision theory in a risk-averse manner. Coordinated scheduling of Controllable Distributed Generators (CDGs) and SOPs, inter-area energy exchanges and energy trading with upstream network considering the uncertainties are the contribution of the presented method. To improve the computational efficiency and to achieve the optimal solution, the scheduling problem is modeled as a second-order conic programming in which the operational and security constraints of the network, CDG limitations, and operational constraints of SOPs are accurately modeled and the problem is solved by executing CPLEX solver in MATLAB environment. A case study on IEEE 33-bus test system showcases the superiority of the proposed model compared to meta-heuristic algorithms such as particle swarm optimization, genetic algorithm, and gravitational search algorithm. https://isee.ui.ac.ir/article_27657_253348c5185abaad325adf7152622edd.pdf