Fuzzy Inference System for VOLT/VAR control in distribution substations in isolated power systems

This paper presents a fuzzy inference system for voltage/reactive power control in distribution substations. The purpose is go forward to automation distribution and its implementation in isolated power systems where control capabilities are limited and it is common using the same applications as in continental power systems. This means that lot of functionalities do not apply and computational burden generates high response times. A fuzzy controller, with logic guidelines embedded based upon heuristic rules resulting from operators at dispatch control center past experience, has been designed. Working as an on-line tool, it has been tested under real conditions and it has managed the operation during a whole day in a distribution substation. Within the limits of control capabilities of the system, the controller maintained successfully an acceptable voltage profile, power factor values over 0,98 and it has ostensibly improved the performance given by an optimal power flow based automation system

Distribution systems optimization with computational intelligence algorithms

A dual particle swarm optimization - immune algorithm solution is presented in this paper to deal with the problem of optimum radial reconfiguration and reactive power compensation in distribution systems. The optimization problem uses as minimization function power losses in the distribution system – lines and transformers – and addresses constraints referring lower and upper voltage limits, nodal reactive power limits, topology supply constraints and the maximum number of capacitor banks. The analysis conducted for a pilot and a complex test system has proven the feasibility of the proposed method

Coordinated Voltage and Reactive Power Control of Power Distribution Systems with Distributed Generation

Distribution system voltage and VAR control (VVC) is a technique that combines conservation voltage reduction and reactive power compensation to operate a distribution system at its optimal conditions. Coordinated VVC can provide major economic benefits for distribution utilities. Incorporating distributed generation (DG) to VVC can improve the system efficiency and reliability. The first part of this dissertation introduces a direct optimization formulation for VVC with DG. The control is formulated as a mixed integer non-linear programming (MINLP) problem. The formulation is based on a three-phase power flow with accurate component models. The VVC problem is solved with a state of the art open-source academic solver utilizing an outer approximation algorithm. Applying the approach to several test feeders, including IEEE 13-node and 37-node radial test feeders, with variable load demand and DG generation, validates the proposed control. Incorporating renewable energy can provide major benefits for efficient operation of the distribution systems. However, when the number of renewables increases the system control becomes more complex. Renewable resources, particularly wind and solar, are often highly intermittent. The varying power output can cause significant fluctuations in feeder voltages. Traditional feeder controls are often too slow to react to these fast fluctuations. DG units providing reactive power compensation they can be utilized in supplying voltage support when fluctuations in generation occur. The second part of this dissertation focuses on two new approaches for dual-layer VVC. In these approaches the VVC is divided into two control layers, slow and fast. The slow control obtains optimal voltage profile and set points for the distribution control. The fast control layer is utilized to maintain the optimal voltage profile when the generation or loading suddenly changes. The MINLP based VVC formulation is utilized as the slow control. Both local reactive power control of DG and coordinated quadratic programming (QP) based reactive power control is considered as the fast control approaches. The effectiveness of these approaches is studied with test feeders, utility load data, and fast-varying solar irradiance data. The simulation results indicate that both methods achieve good results for VVC with DG

REDUCTION OF LOSSES IN RADIAL DISTRIBUTION LINES USING FUZZY LOGIC

Distribution system provides the final link between the high voltage transmission system and the customers. Radial distribution system with a single circuit main feeder is popular because of simple design and generally low cost. The power loss in a distribution system is significantly high because of lower voltage hence high current and losses (I2R). Reduction of reactive power is beneficial to improve overall efficiency and reduce cost. This project is to analyze losses in radial distribution system and compensate the losses with an intelligent method using fuzzy logic. Fuzzy logic is used together with numerical approach to determine the suitable candidate node for capacitor placement at distribution load busbar to compensate losses in the line. This report will articulate the work that has been done by the author in the project for the purpose of fulfillment of the Final Year Project

Novel power flow problem solutions method’s based on genetic algorithm optimization for banks capacitor compensation using an fuzzy logic rule bases for critical nodal detections

The Reactive power flow’s is one of the most electrical distribution systems problem wich have great of interset of the electrical network researchers, it’s cause’s active power transmission reduction, power losses decreasing, and the drop voltage’s increase. In this research we described the efficiency of the FLC-GAO approach to solve the optimal power flow (OPF) combinatorial problem. The proposed approach employ tow algorithms, Fuzzy logic controller (FLC) algorithm for critical nodal detection and gentic algorithm optimization (GAO) algorithm for optimal seizing capacitor.GAO method is more efficient in combinatory problem solutions. The proposed approach has been examined and tested on the standard IEEE 57-bus the resulats show the power loss minimization denhancement, voltage profile, and stability improvement. The proposed approach results have been compared to those that reported in the literature recently. The results are promising and show the effectiveness and robustness of the proposed approach

Fuzzy inference system for integrated VVC in isolated power systems

This paper presents a fuzzy inference system for integrated volt/var control (VVC) in distribution substations. The purpose is go forward to automation distribution applying conservation voltage reduction (CVR) in isolated power systems where control capabilities are limited. A fuzzy controller has been designed. Working as an on-line tool, it has been tested under real conditions and it has managed the operation during a whole day in a distribution substation. Within the limits of control capabilities of the system, the controller maintained successfully an acceptable voltage profile, power factor values over 0,98 and it has ostensibly improved the performance given by an optimal power flow based automation system. CVR savings during the test are evaluated and the aim to integrate it in the VVC is presented.Comment: arXiv admin note: substantial text overlap with arXiv:1401.163

Optimal Capacitor Placement in Radial Distribution Systems using Artificial Bee Colony (ABC) Algorithm

This paper presents a new method which applies an artificial bee colony algorithm (ABC) for capacitor placement in distribution systems with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two a new algorithm called Artificial Bee Colony Algorithm(ABC) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The ABC algorithm is a new population based meta heuristic approach inspired by intelligent foraging behavior of honeybee swarm. The advantage of ABC algorithm is that it does not require external parameters such as cross over rate and mutation rate as in case of genetic algorithm and differential evolution and it is hard to determine these parameters in prior. The other advantage is that the global search ability in the algorithm is implemented by introducing neighborhood source production mechanism which is a similar to mutation process. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 34-bus system and compared the results with the other approach available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency

Optimal Capacitor Placement - A Bibliometric Survey

In this paper, Bibliometric survey has been carried out on Optimal Capacitor Placement from 1981 to 2021. Scopus database has been used for the analysis. There were total 909 documents found on the topic of Optimal Capacitor placement. The statistical analysis is carried out source-wise, year-wise, area-wise, Country-wise, University wise, author-wise, and based on funding agency. Network analysis is also carried out based on Co-authorship, Co-occurrence, Citation Analysis and Bibliographic coupling. Results are presented. During 2016, there were 77 documents published which is the highest. International Journal of Electrical Power and Energy Systems of Elsevier has published 37 documents during the period of study which is highest under the category of sources. VOSviewer 1.6.16 is the software that is used for statistical analysis and network analysis on the database. It provides a very effective way to analyze the co-authorship, co-occurrences, citations and bibliometric couplings etc. The source for all Tables and figures is www.scopus.com, The data is assessed on 6th June, 2021