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Usually, the optimal integration of thyristor-controlled series compensators (TCSCs) aims at enhancing power system performance like all of flexible AC transmission systems (FACTS) devices. The insertion of TCSC unites targets to minimize active/reactive power losses, increase transmission-lines flow reserve beyond the thermal limit, and improve the voltage profile while maintaining the total generation cost of the system slightly affected compared to its single objective base case. In this paper, the optimal power flow (OPF) framework is considered to find the best site and size of the TCSCs devices considering techno-economic issues for reducing the costs of installed TCSCs devices as well as for generation costs. An adaptive parallel seeker optimization algorithm (APSOA) is investigated to employ this techno-economic study. The proposed APSOA is used to solve the multi-objective OPF problem while LSR reduces the search space. The proposed algorithm is tested over three IEEE standards with 9−, 30− and 57-bus test systems at normal and contingency operating conditions. Also, a large system of IEEE 118-bus is used also in order for the proposed technique to be adopted by industry, sound solutions for practical and realistic test systems are needed besides proof of concept on small IEEE test systems. Four-study cases considered to demonstrate the capabilities and gains of the proposed method from the point of view of reducing losses and total voltage deviation to lower levels as compared to those on literature for better energy utilization efficiency. INDEX TERMS Energy utilization efficiency, optimal power flow problem, compensation, power loss minimization, FACTS devices.

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Active distribution networks concerned with providing efficient control technologies for large-scale integration of distributed generation (DG) units into the distribution systems. This research proposes a methodology for distribution networks reconfiguration by controlling number, sharing, size, and location of DG units. Also, the soft-open points (SOPs) are added instead of the tie line switches. The SOPs are benefited with its high capability in controlling active/reactive power flow to enhance transmission system performance. The main target of this work is to increase the efficiency of energy utilization through minimizing the power system losses and improving system voltage profile while preserving all system constraints within permissible limits with reliable and flexible networks in normal and abnormal conditions with a suitable penetration level of DG. A modified particle swarm optimizer is developed to find the best system configuration, size, and placement of DG units as well as the size and allocation of SOPs. Research methodology is tested on two standards: the IEEE 33-node and 69-node distribution networks under different operating cases. This paper compares the obtained results with those in the literature to prove the capabilities of the proposed work. Finally, the suggested work pursues the optimal number of DG units with their appropriate penetration levels and selects the most convenient location of SOPs for adequate network reconfiguration. INDEX TERMS Efficiency of energy utilization, active distribution networks, distributed generation, soft-open points, modified particle swarm optimization.

SUMMARYUnified power flow controller (UPFC) is one of the most effective flexible AC transmission systems (FACTS) devices for enhancing power system security. However, to what extent the performance of UPFC can be brought out, it highly depends upon the location and parameters setting of this device in the system. This paper presents an approach based on evolutionary algorithms (EAs) techniques to find out the optimal placement and settings of UPFC for enhancing power system security under single line contingencies (N-1 contingency). Firstly, we perform a contingency analysis and ranking process to determine the most severe line outage contingencies considering line overloads and bus voltage limit violations as a performance index. Secondly, we apply an evolutionary optimization technique, namely: differential evolution (DE) to find out the optimal location and parameters setting of UPFC under the determined contingency scenarios. To verify our proposed approach and for comparison purposes, we perform simulations on an IEEE 14-bus and an IEEE 30-bus power systems. The results we have obtained indicate that DE is an easy to use, fast, and robust optimization technique compared with genetic algorithm (GA). Installing UPFC in the optimal location determined by DE can significantly enhance the security of power system by eliminating or minimizing the overloaded lines and the bus voltage limit violations.

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