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This study presents a novel algorithm for the optimal placement of underground cables in a concrete duct bank to simultaneously maximize ampacity and minimize cable system cost for the first time. The self-adaptive particle swarm optimization (SAPSO) method -which has been used to solve multi-objective optimization problems- is used to solve the multi-objective problem. The main novelty of this paper is finding optimal cable placement by finding maximum ampacity and minimum cable system cost, simultaneously. The proposed method is used in a test case to show how the cable placement is affected by the total ampacity and cable cost in the duct bank. The obtained results show the total fundamental ampacity decrease and the total cable cost increase, on the existence of power system harmonics. The output of the optimization problem is a Pareto optimal solution which gives the cable placement for the concurrent maximized ampacity and minimized total cost. As a case in point, at a specific ampacity of the worst cable configuration, the total cable system cost is more than the total cost of the cable configuration obtained from the optimal Pareto solution, based on simulation results. Highlights An analytical formula is studied to compute the temperature of underground cables. The Thermal Margin Index (TMI) is introduced and the probability of unreliability is calculated. Obtained simulation results have shown that HPEM requires less input data.

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This paper proposes a novel energy and reserve scheduling model for power systems with high penetration of wind turbines (WTs). The objective of the proposed model is to minimize the total operation cost of the system while static and dynamic security is guaranteed by preserving the frequency nadir, RoCoF, and quasi-steady-state frequency in the predefined range. Likewise, a supervisory, control, and data acquisition (SCADA) system is developed which allows Vanadium Redox Flow Batteries (VRFBs) to continuously communicate and participate in the primary frequency response. To cope with the uncertainties, adaptive information gap decision theory is used that ensures a target operating cost for the risk-averse operator of the power system. The proposed scheduling model is applied on a modified IEEE 39 bus test system to verify the impacts of the fast reserve provided by the VRFBs in the dynamic frequency security enhancement of the power system with high penetration of WTs.