Minimization Of Total Power Losses Research Articles

A soft computing technique based on PSO algorithm and energy management strategy for optimal allocation and placement of PVDG-BES units

In the pursuit of achieving a harmonious equilibrium between electricity production and consumption, the integration of distribution generators (DG) has garnered substantial attention. Yet, the escalated integration of DG systems has given rise to the predicament of reverse power flow, instigating elevated system power losses and voltage profile distortions. Thus, an imperative emerges to judiciously apportion and dimension DG systems, complemented by the incorporation of battery energy storage (BES) systems, as a remedial measure against these challenges. In this scholarly work, we present an innovative approach rooted in a precise energy management strategy (EMS) aimed at the adept allocation and capacity optimization of (PVDG-BES) systems. The study employs a two-step optimization methodology, the former facet of which expounds on the influence of BES system integration on grid power losses and voltage profiles during stable operational conditions. Subsequently, a pioneering optimization technique is formulated in the latter facet to identify the optimal siting and capacity allocation of the aforementioned system based on an optimal EMS framework. The primary focal point of this investigation is the minimization of total power losses. Validation of our proposition is conducted on the IEEE 14-bus standard system, incorporating the particle swarm optimization (PSO) algorithm. Simulation outcomes incontrovertibly affirm the efficacy and robustness of the proposed EMS, yielding substantive reductions in power losses and noteworthy enhancements in voltage profile integrity. Notably, the implementation of EMS leads to a remarkable 31% reduction in total power losses as compared to the initial scenario, prior to the amalgamation of PVDG-BES components. In sum, this study epitomizes a comprehensive strategy for fortifying power grid efficiency by orchestrating the symbiotic interplay of distribution generators and battery energy storage systems through an adept energy management paradigm.

Optimal integration and coordination of distributed generation and shunt compensators using improved African vultures optimizer

This article aims to improve the performance of radial distribution systems (RDSs) by accurately solving the optimal energy management of the active powers of distributed generation units based on renewable energy and the reactive powers of shunt compensator-based flexible AC transmission system technology. An adaptive African vultures optimizer (AAVO) is proposed and applied to optimize individually and simultaneously various objective functions, including the minimization of total power loss, minimization of total voltage deviation and maximization of the loading margin. The efficacy of the proposed AAVO method is validated on three RDSs, the 33-bus, the 85-bus and the large RDS with 141-bus, under normal conditions and considering uncertainties of loads. Compared to many other techniques, the results clearly demonstrate the robustness and competitiveness of the proposed new variant in solving the power management optimization of a large-scale RDS.

Single-phase grid interface for home energy storage

In this paper, an overview of a novel home energy storage system is presented. The aim of the system is the utilization of community solar panels in urban environments with decentralized energy storage at the household level. An increase in the total energy production from renewable energy sources as well as a reduction in energy costs for the consumer are the obvious benefits of such a system. The key focus of the paper presented is to model, design, and optimize a Dual Active Bridge that serves as a low-voltage grid-battery interface for the proposed storage system. A state-of-the-art loss model of the Dual Active Bridge is presented along with a novel optimization method intended for total power loss minimization.

Restoration of a new age power distribution system

The new age transformed distribution system became the most popular content in the literature. In that regard a simulation is attempted for the load flow with dynamically changing system data. Any topic of interest like electrical vehicle, distributed generators, FACTS devices were generalized and considered as an element and placed at different possible locations to observe their effect. The outcomes of the work were generalized to re-consider on site. As the power industry is undergoing a drastic change throughout the world. Restoration of a distribution system along with switching sequence has become a challenging task. In the last half of the twentieth century, analysis of transmission system was the prime concern and faced many challenges to power engineers. The chosen equivalent IEEE 33-bus electric power distribution system has been considered to analyze the system properties such as its maximum capacity, operating limits, restoration issues. The placement of static var compensator (SVC) was experimented for each and every bus. Considering the minimization of total power loss as a prime objective, the best location was found. This analysis also suggested a ranking of different buses and can be helpful in deciding the switching sequence, provided in case of fault, weak area clustering is done. So, congestion is managed in this distribution system.

Optimal Allocation of Distributed Generation, Capacitor Banks and D-STATCOM in Distribution Systems

This paper demonstrates the problem of simultaneous optimal allocation of distributed generations (DGs), shunt capacitor banks (CBs), and distribution FACTSs based D-STATCOMs in distribution network for the improvement of the entire system performance. Here, two objectives, total power loss minimization, and overall voltage stability index (VSI) maximization are considered. In general, minimization of power loss is the primary objective, and VSI is considered for improved voltage stability. VSI must be positive to obtain a stable operation and a higher VSI value represents better stability of the RDS. These objectives are solved subject to constraints related to power balance, DGs, CBs, D-STATCOM powers, bus voltages, and VSI. Here, single objective problem is solved using Particle swarm optimization (PSO), and the multi-objective problem is solved using multi-objective PSO (MO-PSO). Standard 33 bus RDS is considered for solving this problem. The results obtained show that proposed optimization has improved the voltage profile and overall VSI of the RDS and minimized the system power losses.

Power loss minimization with simultaneous location and sizing of distribution generation units using artificial algae algorithm

Power loss is one <span lang="EN-US">of the important pointers used to measure the performance of distributions networks. Many optimization algorithms have been proposed to solve various optimal power flow problems in Electrical Engineering. In this paper, a novel technique, artificial algae algorithm is developed to robustly detect the optimal location and size of distributed generation (DG) units for minimization of total power losses without violating the equality and inequality constraints. The main objective of optimal power flow (OPF) is to maximize or minimize the objective function using various constraint so that steady-state operation point is achieved. The concept of optimal power flow in power system helps to minimize real power loss. In the proposed approach, various control variables like generator bus, voltage magnitudes, and transformer tap settings are considered. The proposed algorithm is simulated in MATLAB and effectiveness is carried on IEEE 33 bus radial distribution system and satisfactory results are achieved when compared with other optimization techniques. A notable improvement in reduction of active power losses with 3 DG operating at different power factors are 65.5%, 42.4%, and 77.8% respectively, were achieved in comparison to the system without DGs and as compared with other research papers.</span>

Characterization and optimization of gate driver turn-off voltage for eGaN HEMTs in a phase-leg configuration

Affected by high switching speed and parasitic parameters, crosstalk problem of eGaN HEMT in a phase-leg configuration cannot be ignored. By decreasing gate driver turn-off voltage, the false turn-on phenomenon of device caused by crosstalk can be avoided, but it is hard to realize the minimization of total power loss. Thus, we analyze the influence of gate driver turn-off voltage on eGaN HEMT reverse conduction loss, switching loss and crosstalk voltage, and propose an optimized design rules for determining turn-off voltage value in a phase-leg configuration. By reasonably choosing gate driver turn-off voltage, a balance between optimal loss and reliable operation is achieved, thereby effectively alleviating the conflict between efficiency and reliability in the power electronic system.

Voltage Profile Enhancement and Loss Minimization Using Optimal Placement and Sizing of Distributed Generation in Reconfigured Network

Power loss and voltage instability are major problems in distribution systems. However, these problems are typically mitigated by efficient network reconfiguration, including the integration of distributed generation (DG) units in the distribution network. In this regard, the optimal placement and sizing of DGs are crucial. Otherwise, the network performance will be degraded. This study is conducted to optimally locate and sizing of DGs into a radial distribution network before and after reconfiguration. A multi-objective particle swarm optimization algorithm is utilized to determine the optimal placement and sizing of the DGs before and after reconfiguration of the radial network. An optimal network configuration with DG coordination in an active distribution network overcomes power losses, uplifts voltage profiles, and improves the system stability, reliability, and efficiency. For considering the actual power system scenarios, a penalty factor is also considered, this penalty factor plays a crucial role in the minimization of total power loss and voltage profile enhancement. The simulation results showed a significant improvement in the percentage power loss reduction (32% and 68.05% before and after reconfiguration, respectively) with the inclusion of DG units in the test system. Similarly, the minimum bus voltage of the system is improved by 4.9% and 6.53% before and after reconfiguration, respectively. The comparative study is performed, and the results showed the effectiveness of the proposed method in reducing the voltage deviation and power loss of the distribution system. The proposed algorithm is evaluated on the IEEE-33 bus radial distribution system, using MATLAB software.

Optimal sizing and location of multiple distributed generation for power loss minimization using genetic algorithm

This paper presents a Genetic Algorithm (GA) for optimal location and sizing of multiple distributed generation (DG) for loss minimization. The study is implemented on a 33-bus radial distribution system to optimally allocate different numbers of DGs through the minimization of total active power losses and voltage deviation at power constraints of 0 – 2 MW and 0 – 3 MW respectively. The study proposed a PQ model of DG and Direct Load Flow (DLF) technique that uses Bus Incidence to Branch current (BIBC) and Branch Current to Bus Voltage (BCBV) matrices. The result obtained a minimum base case voltage level of 0.9898 p.u at bus 18 with variations of voltage improvements at other buses after single and multiple DG allocations in the system. Besides, the total power loss before DG allocation is observed as 0.2243 MW, and total power loss after DG allocation was determined based on the power constraints. Various optimal locations were seen depending on the power limits of different DG sizes. The results have shown that the impact of optimal allocation and sizing of three DG is more advantageous concerning voltage improvement, reduction of the voltage deviation and also total power loss in the distribution system. The results obtained in the 0 – 2 MW power limit is consistent to the 0 – 3 MW power limits regarding the influence of allocating DG to the network and minimization of total power losses.

NSGA-II+FEM Based Loss Optimization of Three-Phase Transformer

In order to obtain a good optimization method for the electrical transformer design with optimal selection of parameters, performance evaluation of three evolutionary algorithms (EAs), namely, genetic algorithm (GA), differential evolution algorithm, and nondominated sorting GA (NSGA-II), is carried out. The aim of this paper is to optimize parameters of transformer design (core thicknesses, primary-turn number, secondary-turn number, primary conductor area, and secondary conductor area) for minimization of total power losses (no-load losses and load losses) in three-phase transformer topology while maintaining high efficiency and low cost. The method used for this optimization scheme combines the finite-element method (FEM) and EAs to provide an accurate selection of parameters together with the optimized magnetic flux density and decreased loss. Experimental results show that NSGA-II+FEM model successfully provides a global feasible solution by minimizing total loss and related cost while improving the efficiency of three-phase transformer, rendering it suitable for application in the design environment of industrial transformers.

Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches

This report addresses the problem of optimal location and sizing of constant power sources (distributed generators (DGs)) in direct current (DC) networks for improving network performance in terms of voltage profiles and energy efficiency. An exact mixed-integer nonlinear programming (MINLP) method is proposed to represent this problem, considering the minimization of total power losses as the objective function. Furthermore, the power balance per node, voltage regulation limits, DG capabilities, and maximum penetration of the DG are considered as constraints. To solve the MINLP model, a convex relaxation is proposed using a Taylor series expansion, in conjunction with the transformation of the binary variables into continuous variables. The solution of the relaxed convex model is constructed using a sequential quadratic programming approach to minimize the linearization error using the Taylor series method. The solution of the relaxed convex model is used as the input for a heuristic random hyperplane method that facilitates the recovery of binary variables that solve the original MINLP model. Two DC distribution feeders, one having 21 and the other having 69 nodes, were used as test systems. Simulation results were obtained using the MATLAB/quadprog package and contrasted with the large-scale nonlinear solvers available for General algebraic modeling system (GAMS) software metaheuristic optimization approaches to demonstrate the robustness and effectiveness of our proposed methodology.

Optimal Modulation for a Fifth-Order Dual-Active-Bridge Resonant Immittance DC–DC Converter

This paper proposes a fifth-order resonant immittance network based dual-active-bridge (DAB) converter and an optimal modulation method that will ensure high-efficiency operation of the converter under wide-range variations in voltage ratio and output power level. The proposed modulation method is based on the concept of total power loss minimization, where a loss model is developed and an optimization algorithm is formulated to compute the optimal set of internal and external phase shift parameters that will lead to the maximum efficiency for a given set of operating parameters including voltage ratio and output power level. It is found that to maintain high-efficiency operation under wide-range variations in voltage ratio and output power level, the DAB converter is required to switch between different operation modes and neither soft-switching operation nor unity-power-factor operation is able to achieve wide-range high efficiency performance when used alone. The importance of $reconfigurability$ of operation mode for achieving wide-range high efficiency performance is clearly illustrated in this paper.

Multi-objective planning for the allocation of PV-BESS integrated open UPQC for peak load shaving of radial distribution networks

Abstract This paper presents a multi-objective planning approach for the optimal allocation of PV-BESS integrated open UPQC (PV-BESS-UPQC-O) for peak load shaving of radial distribution networks. The open UPQC (UPQC-O) is a custom power device which consists of series and shunt inverters. It is designed to provide reactive power compensation and to mitigate some power quality problems. The UPQC-O is integrated with BESS to inject active power to the network during peak hour for peak load shaving. The charging of BESS is to be done using PV panel. A multi-objective optimization problem is formulated, in which maximization of peak load shaving, minimization of cost of placement of PV-BESS-UPQC-O, and minimization of total power loss during peak load demand with the placement of PV-BESS-UPQC-O are the objective functions. The limits on bus voltage magnitude, line current flow, and PV capacity are the constraints of this optimization problem. The Pareto-based multi-objective particle swarm optimization (MOPSO) is used to simultaneously optimize these objectives so as to obtain a set of Pareto-approximation solutions. From this set, a distribution network owner can choose a solution depending upon its desired level of peak load shaving, power loss, and capital expenditure budget.

Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital

This paper presents an optimization solution for renewable Distributed Generation (DG), as imposed in the Green Building Rating System (GBRS) for a public hospital. Solar photovoltaic DG unit (PV-DG) is identified as a type of DG used in this paper. The proposed optimization via PV-DG coordination will improve the sustainable energy performance of the green building by power loss reduction within accepted lower losses region using Artificial Bee Colony (ABC) algorithm. The setup input data from one of Malaysian public hospitals’ power distribution system is been adopted and simulation results via MATLAB programming show that the optimization of DG forming into bigger-scale imposed system provides a better outcome in minimization of total power losses within appropriate voltage profile as compared to current PV-DG imposed in GBRS. The objective function representing total power losses which also supported by related literature give a measure that forming sufficient and optimal PV-DG assessment criteria is highly important, thus, current PV-DG assessment in GBRS is proposed to be reviewed into new parameter setting for public hospital due to its’ high energy demand and distinctive electrical load profile.

Impact of DG and D-STATCOM Placement on Improving the Reactive Loading Capability of Mesh Distribution System

In this paper, Distribution Generation (DG) and Distribution STATic COMpensator (D-STATCOM) are optimally placed in mesh distribution systems using sensitivity approaches. The objective of this paper is to improve the reactive loading capability of the network with maintaining voltage profile in an acceptable limit. Optimal locations of DG and D-STATCOM are determined using Voltage Stability Index and Combined Power Loss Sensitivity approaches respectively. The size of DG and D-STATCOM are determined by variational algorithm subjected to minimization of total power loss. In order to quantitatively analyze the impact of DG and D-STATCOM on voltage stability margin, Q-V curves are drawn using continuation power flow method. In this study the impact of simultaneous placement of DG and D-STATCOM is investigated separately for large industrial motor load as well as industrial load. Also, load growth scenario is considered for better planning of the system. The results are obtained on standard IEEE-33 and 69-bus mesh distribution systems to check the feasibility of proposed methodology.

Impact of D-STATCOM Placement on Improving the Reactive Loading Capability of Unbalanced Radial Distribution System

In this paper, Distribution STATic COMpensator (D-STATCOM) are optimally placed in unbalanced radial distribution systems (UBRDS) using sensitivity approaches with an objective of improving the reactive loading capability of the network with maintaining voltage profile in an acceptable limit. Optimal locations of D-STATCOM are determined using Voltage Stability Index (VSI). Optimum size of D-STATCOM is obtained by variational algorithm subjected to minimization of total power loss. In order to quantitatively analyze the impact of D-STATCOM on voltage stability margin, Q-V curves are drawn using continuation power flow method. In this study the impact of D-STATCOM placement is investigated for large industrial load model with light, medium and high loading conditions. Also, load growth scenario is considered for better planning of the system. The results are obtained on standard 25-bus and IEEE-37 bus UBRDS to verify the practicability of proposed methodology.

On Optimally Reducing Power Loss in Micro-grids With Power Storage Devices

Chapter 5 described a strategy to allow the micro grids to make coalitions and exchange power with other micro grids and/or the macro station. In this chapter, we are going to carry on from that strategy and enhance the model further by considering micro grids to use power storage devices. Recently, the micro grid developers and operators are exhibiting a great deal of interest in using lithium-ion batteries and flow batteries. The battery technologies have become quite mature and they are currently capable enough to provide exceptional renewable power integration in the micro grids based energy systems [1, 2]. In [3], it was demonstrated how the storage devices can supplement energy generation to consumption to achieve a balance between energy demand and supply within the micro grid. Necessity of optimal control of the power storage devices of the micro grid was also indicated in [3]. A new photovoltaic power generation and load power consumption prediction algorithm was designed in [4] which was specifically designed for a residential storage controller. However, these existing works usually focused on a single micro grid and did not consider the power losses impacting the entire system including the macro station and multiple micro grids. Instead, they had a localized approach such as how to reduce the power loss within a given micro grid, how to charge and discharge the storage device periodically, and so forth. In this chapter, we adopt a different approach by focusing on a scalable total power loss minimization approach across the entire smart grid.

Fuzzy based controller for dynamic Unified Power Flow Controller to enhance power transfer capability

In this paper, a dynamic model of Unified Power Flow Controller (UPFC) is developed to improve the power transfer capability (PTC) through the transmission line. Improvement of the bus voltages profiles along with the reduction of total power losses is also intended with UPFC’s presence. The UPFC shunt and series controllers are developed based on Fuzzy Logic (FL) which has been designed as a stand-alone module in PSCAD environment. Sinusoidal pulse width modulation (SPWM) technique is applied as a modulation technique to generate switching signals for the converter switches. The proposed UPFC controller is tested by using IEEE-5 and 14 bus systems with various case studies. The performance of the proposed controllers is also compared with different control methods. From the test results, significant improvement of PTC has been achieved with the minimization of total power losses.

Locating Power Supplies on a Personal Rapid Transit System to Minimize System Losses

A personal rapid transit (PRT) system is a computer-controlled and lightweight railway vehicle using linear motors. The speeds of vehicles are controlled to be constant, and the distance between vehicles is also strictly controlled to be only 12 m at 40 km/h. Thus, the vehicle density of the PRT system is much higher than that of the mass railway train (MRT) system. Moreover, the required power of a PRT vehicle is much smaller than that of an MRT vehicle. Therefore, the methodology to allocate the position of power supplies for an MRT system is thought to be improper for a PRT system. This paper proposes a practical method that locates power supplies optimally for a PRT system to achieve a load power balance and a total power loss minimization. This method uses an iterative approach based on a new virtual isolation concept among power supplies. The effectiveness and feasibility of the proposed method is confirmed by simulation results and example studies.