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 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 reduction 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 a 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.

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 is 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 standard 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.

The electrical energy storage system faces numerous obstacles as green energy usage rises. The demand for electric vehicles (EVs) is growing in tandem with the technological advance of EV range on a single charge. To tackle the low-range EV problem, an effective electrical energy storage device is necessary. Traditionally, electric vehicles have been powered by a single source of power, which is insufficient to handle the EV’s dynamic demand. As a result, a unique storage medium is necessary to meet the EV load characteristics of high-energy density and high-power density. This EV storage system is made up of two complementing sources: chemical batteries and ultracapacitors/supercapacitors. The benefits of using ultracapacitors in a hybrid energy storage system (HESS) to meet the low-power electric car dynamic load are explored in this study. In this paper, a HESS technique for regulating the active power of low-powered EV simulations was tested in a MATLAB/Simulink environment with various dynamic loading situations. The feature of this design, as noted from the simulation results, is that it efficiently regulates the DC link voltage of an EV with a hybrid source while putting minimal load stress on the battery, resulting in longer battery life, lower costs, and increased vehicle range.

This research develops an overall framework for optimal operation of Hybrid Renewable Energy Resources (HRERs) system that involves the combination of PV/WT/Diesel units. In the proposed framework, a co-simulator tool is proposed to find the optimal scheduling of HRERs parameters. It composes HOMER PRO and NEPALN packages that are managed by C++ based online optimizer. Different scenarios of hybridization of energy resources are considered achieving technical, economic and environmental perspectives using the HOMER PRO package. The best allocation and sizing of Soft Open Points (SOPs) and the sharing of HRERs are obtained via multi-objective Artificial Electric Field Algorithm (AEFA). The simulation results propose a new hybrid grid-connected system to supply a realistic case study in Sohag-Egypt. That proposed HRERs system demonstrated a feasible economic solution at acceptable levels of gases emission and fuel consumption. Besides, the optimal operation of the HRERs system with SOPs potentially achieve significant technical perspectives that enhance the system losses, improve the voltage profile and increase the loading capacities of transmission lines. The technical perspective is handled using NEPLAN software. Furthermore, the simulation studies prove the high flexible planning and operation of distribution system at significant improvements technical, economic and environmental perspectives.

A distribution system’s network reconfiguration (NR) is the process of changing the status of the switches to change the topology of the feeders. Using optimal NR at various network load levels, this research proposed an economical way for improving the voltage profile and reducing power loss in distribution systems. A new metaheuristic Heap-based optimizer based on the corporate rank hierarchy is used to solve the optimization problem in order to find the optimal radial distribution network. The objective functions used in this article include voltage profile improvement, power loss reduction, reduction of operation cost, and minimization of gas emissions. This novel technique provides accurate results while avoiding the issue of premature convergence and requires fewer control parameter settings. The proposed method is evaluated at three different load levels on a standard IEEE 33-bus test system, and the simulation results are compared to those of other optimization methods published in the literature, demonstrating that the proposed method improves the system voltage profile while minimizing losses and power costs, establishing that this technique is effective in finding the best result. The Wilcoxon and Friedman tests are also used to verify the effectiveness of the proposed technique.