Real Power Loss Cost Research Articles

Optimal Siting and Sizing of Battery Energy Storage: Case Study Seventh Feeder at Nakhon Phanom Substation in Thailand

The optimal siting and sizing of battery energy storage system (BESS) is proposed in this study to improve the performance of the seventh feeder at Nakhon Phanom substation, which is a distribution network with the connected photovoltaic (PV) in Thailand. The considered objective function aims to improve the distribution network performance by minimizing costs incurred in the distribution network within a day, comprising of voltage regulation cost, real power loss cost, and peak demand cost. Particle swarm optimization (PSO) is applied to solve the optimization problem. It is found that the optimal siting and sizing of the BESS installation could improve the performance of the distribution network in terms of cost minimization, voltage profile, real power loss, and peak demand. The results are investigated from three cases where case 1 is without PV and BESS installation, case 2 is with only PV installation, and case 3 is with PV and BESS installations. The comparison results show that case 3 provided the best costs, voltage deviation, real power loss, and peak demand compared to those of cases 1 and 2; system costs provided by cases 1, 2 and 3 are USD 4598, USD 5418, and USD 1467, respectively.

A combined nodal and uniform pricing mechanism for congestion management in distribution power networks

Abstract We present a price-based approach for congestion management in distribution power systems with renewable generations with the final goal of maximizing a social welfare function which includes net revenues of network users as well as the cost of real power losses. Particularly, we design a combined nodal and uniform pricing mechanism for maximization of the social welfare function while maintaining voltage magnitudes in a desired bound and respecting the grid's actual capacity. Storage systems are considered in order to increase/add elasticity to generations and loads. Simulation results are provided for a modified IEEE-37 bus. A scenario is numerically simulated where the excess of generation in the absence of storage and price signals leads to deviations of voltages from a desired bound. Thereafter, it is shown that the application of the price signals is effective to maintain the voltages within the desired bound while the designed social welfare function is maximized.

Young scientist: Career prospect, research, and networking

We present a price-based approach for congestion management in distribution power systems with renewable generations with the final goal of maximizing a social welfare function which includes net revenues of network users as well as the cost of real power losses. Particularly, we design a combined nodal and uniform pricing mechanism for maximization of the social welfare function while maintaining voltage magnitudes in a desired bound and respecting the grid's actual capacity. Storage systems are considered in order to increase/add elasticity to generations and loads. Simulation results are provided for a modified IEEE-37 bus. A scenario is numerically simulated where the excess of generation in the absence of storage and price signals leads to deviations of voltages from a desired bound. Thereafter, it is shown that the application of the price signals is effective to maintain the voltages within the desired bound while the designed social welfare function is maximized.

Two‐layer volt/var/total harmonic distortion control in distribution network based on PVs output and load forecast errors

A two-layer control method is proposed for voltage and reactive power control in harmonic polluted distribution network with penetration of photovoltaic (PV) systems. Optimal scheduling of load tap changer and shunt capacitors for minimising energy losses and improving the power quality simultaneously are performed using P-particle swarm optimisation (PSO) optimisation method. Here, the minimising cost of real power losses and improving the power quality criteria have been pursued as the goals of an optimisation problem. Considering load and PVs output forecast, the first-layer control determines the optimal reactive power and control settings for all mechanical controllers. Hourly errors of load and power forecasts and mechanical control setting of the first layer are used to estimate optimised reactive power of PV in order to achieve maximum voltage regulation, reduce network losses and total harmonic distortion (THD). These data are trained a neural network (NN) to estimate optimised PV reactive power. This NN in the second layer is used to optimise the online reactive power setting based on online PV power. For more practical applications of the proposed method, simulation is carried out in a large distorted 37-bus distribution system. The algorithm will increase use of renewable energies, reduce voltage fluctuations, THD, and wear and tear of mechanical equipment.

Feeder reconfiguration and capacitor allocation in the presence of non‐linear loads using new P‐PSO algorithm

This study proposes a new particle swarm optimisation algorithm for combined problem of capacitor placement and network reconfiguration simultaneously in the presence of non-linear loads. Here, the minimising cost of real power losses and capacitor installation and also improving the power quality criteria have been pursued as the goals of an optimisation problem. In the proposed method, to achieve better control on the algorithm's exploration and exploitation capabilities, particles velocity will be dependent upon both particle's fitness and time. Perturbation module is adopted to perform perturbation on some particles and provide extra diversity to jump out from local optima and avoid premature convergence. The proposed model is implemented on two typical networks including 33-bus IEEE standard well-known test system and a 77-bus radial distribution network of Sirjan, Iran. Through showing numerical results, the performance of the presented method will be discussed in comparison to previously proposed ones. The numeric comparison also indicates that simultaneously capacitor placement and network reconfiguration lead to far better results than they are considered non-simultaneously. Furthermore, in regard to harmonic distortion, as a term of a multi-objective function, it also improves the power quality of the network during the reconfiguration and capacitor placement procedures.

Technical–economic analysis of including wind farms and HFC to solve hybrid TNEM–RPM problem in the deregulated environment

Abstract This paper addresses a mathematical model for solving transmission network expansion management (TNEM) associated with reactive power management (RPM) in the presence of double-fed induction generator (DFIG) variable speed wind turbine and hybrid flow controller (HFC). According to this plan, the reactive power capability of DFIG wind turbine is gained and the constraints of deliverable power are derived for each operation point. Strong control capability of the HFC with controlling bus voltage and line power flow offers a great potential for solving many of the problems facing electric utilities. For a precise steady-state analysis of HFC, the injection model is considered which it is an adaptive model in steady-state analysis. The main goals of the proposed management strategy are to minimize investment cost, real power loss cost in transmission lines and voltage deviation and maximize voltage stability index and social benefit at the same time. A three-stage scheme has been developed for solving hybrid TNEM–RPM problem. In the beginning of the plan, it is assumed that all the reactive demands are acquired from local sources and an optimal transmission plan is specified. After transmission lines are constructed, in the second step, reactive power sources will be allocated to weak buses. In order to assess reliability of the system, EENS criterion is used. Due to multi-objective nature of the proposed management method, an improved non-dominated sorting genetic algorithm-II (INSGA-II) style is applied for an optimization procedure. Also, a decision making method based on fuzzy decision making (FDM) is used for finding the best compromise solution from the set of Pareto-solution obtained by INSGA-II technique. In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from previous management methods and the proposed approach is represented.

Coordinated Voltage and Reactive Power Control Strategy with Distributed Generator for Improving the Operational Efficiency

This study proposes a voltage and reactive coordinative control strategy with distributed generator (DG) in a distribution power system. The aim is to determine the optimum dispatch schedules for an on-load tap changer (OLTC), distributed generator settings and all shunt capacitor switching on the load and DG generation profile in a day. The proposed method minimizes the real power losses and improves the voltage profile using squared deviations of bus voltages. The results indicate that the proposed method reduces the real losses and voltage fluctuations and improve receiving power factor. This paper proposes coordinated voltage and reactive power control methods that adjust optimal control values of capacitor banks, OLTC, and the AVR of DGs by using a voltage sensitivity factor (VSF) and dynamic programming (DP) with branch-and-bound (B&B) method. To avoid the computational burden, we try to limit the possible states to 24 stages by using a flexible searching space at each stage. Finally, we will show the effectiveness of the proposed method by using operational cost of real power losses and voltage deviation factor as evaluation index for a whole day in a power system with distributed generators.