Session 14: Distribution Networks
Maximization of Social Welfare in Distribution Network with Distributed Generations using Genetic Algorithm
University of Pretoria, South Africa
Retail electrical power marketers, also known as retailers, typically set up contracts with suppliers to secure electricity at fixed prices on the one hand and with end users to meet their load requirements at agreed rates on the other hand. High penetration of distributed generation (DG) resource is increasingly observed worldwide. This paper analyzes the problem of setting up contracts on both the supplier and end-user sides to maximize profits while maintaining a minimum operational cost of the distribution network with distributed generations. Proposed genetic algorithm in this paper, can minimize cost of distribution system with Distributed Generation and maximize profits of retailers. Numerical simulations are carried out based on an IEEE 33-bus test distribution network. Test results are included to show the performance of the proposed method.
Tariff Redesign in the Purpose of Increasing Market Business Quality in Distribution System
1Regulatory Commission for Electricity in Federation Bosnia and Herzegovina -FERK, Bosnia and Herzegovina; 2University of Tuzla, Faculty of Electrical Engineering; 3Independent System Operator in Bosnia and Herzegovina
Main principle of a tariff system for electricity is that customers should cover all costs appeared in the power system, but as realistic as it possible in accordance with a place and time of delivered energy. Defining real economical price of electricity for customers at the low voltage distribution level presents main problem due to a lack of data related to daily load diagram. Fuzzy logic and fuzzy c-means clustering was applied to development of a model for consumers’ classification. Obtained results could be used as an input for more realistic calculation of cost for electrical energy consumption of customers in household category. Additionally, the difference in calculation of electricity consumption cost based on the obtained values from proposed model and on current tariff system in Bosnia and Herzegovina is discussed.
Financial Impact of Penalties Applied to Brazilian Energy Distribution Companies by Exceeded of the Limits of Performance of Power Supply Continuity
1Universidade Federal de Santa Maria- UFSM, Brazil; 2Companhia Estadual de Distribuição de Energia Elétrica- CEEE-D
The regulation of power quality in Brazil has had a number of changings and adjustments aiming at the continuous improvement in the quality of product and quality of service. Related to this issue, this paper presents an analysis of the methodologies currently applied to evaluate and define limits of performance of the quality of service provided from power utilities. From tables and graphs given is going to be assessed the financial impact caused by financial penalties applied for violation of limits of performance. This paper also presents a preliminary fuzzy modeling, which is used to obtain new limits of performance considering technical and operational aspects of distribution networks.
Optimizing Capacitor Banks Management in Distribution Networks, with Large Presence of Distributed Generation
EDP Distribuição, Portugal
An ever increasing integration of Distributed Generation (DG) in Distribution Networks (DN) has triggered the imbalance between reactive power generated by DG and reactive power demanded by the same grid. This together with the new rules defined by the Portuguese system regulator (costumers’ power factor improvement, different DG reactive power generation limits, and the change of reactive power integration period from monthly to daily) set the need for a new model of reactive power management in networks with a high penetration of DG. This paper presents a model for optimizing the DN management of capacitor banks installed in HV/MV substations. The objective function aims to minimise Power Factor penalties at the EHV/HV substations and DN losses, considering demand tracking, capacitor banks availability, network topology and distributed generation.
Impact of Distributed Generation (DG) on Voltage Profile in 38kV Distribution System
1Cork Institute of Technology,; 2Electricity Supply Board; 3Dublin Institute of Technology
This paper presents a case study of the integration of a relatively large amount of distributed generation (DG) into a weak distribution network (DN). It addresses the problem of voltage rise mitigation in DN with DG connected. The main focus is on a comparison of methods to increase the integration capacity of DG into DN and the technical requirements from the Distribution System Operator (DSO)’s point of view. The paper considers voltage rise issues in real-life DN that incorporate different types of DG such as Combined Heat and Power (CHP) and wind power generation. The objective of this study is to propose an approach that will demonstrate the impact of DN components on voltage profile violation caused by the connection of DG. The aim of the proposed approach is not to control the bus voltage but to guarantee that DG injection alone will not cause a significant voltage rise: a solution in which DNs are kept to their traditional task of voltage regulation for load demand. The approach is discussed from the perspective of effectiveness and adequacy. Validation of the study is carried out by using the ERAC power flow analysis software on a seven busbars DN which resembles a part of a real network consisting of number of DG units connected at the 38kV voltage level.
Optimal Switch Placement in Distribution Power System Using Linear Fragmented Particle Swarm Optimization Algorithm Processed by GA
1Mapna group, Islamic Republic of Iran; 2Behrad consulting engeeners, Iran, Islamic Republic of
In recent years, Distributed Generation (DG) has become an efficient and clean alternative to traditional distribution systems, therefore new algorithms should be able to solve problems in presence of DGs. Reliability improvement and cost reduction are two important goals of utilities which are usually in opposite of each other. The Islanding operation scheme is dynamically formed when fault occurs, which is based on the location of the fault, location of switches and the actual status of distribution network operation before fault occurs. Optimal allocation of switches in distribution power systems can improve reliability of a power system by reducing the total time of fault detection, isolation and restoration. In this paper, a three-state approach inspired from the discrete version of a powerful Particle swarm optimization (PSO) algorithm is developed and presented to determine the optimum number and locations of two types of switches (sectionalizers and breakers) in radial distribution systems. The novelty of the proposed algorithm is a new linear method for fragmentation particles to probability calculation of switch type offer to each candidate locations. Genetic preprocessing algorithm is used in proposed algorithm for generate suitable first population in PSO and summarize search space for enhance main PSO algorithm operation to escape from local minimums and decrease time of optimization. Using of this method on RBTS-BUS4 test system have appropriate results.
Distributed Generation Dispatch Optimization by Artificial Neural Network Trained by Particle Swarm Optimization Algorithm
1Mapna group, Tehran, Islamic Republic of Iran; 2Behrad consulting engeeners, Esfehan, Islamic Republic of Iran
Distributed power generation is a small-scale power generation technology that provides electric power at a site closer to customers than the central generating stations. The Distributed Generation (DG) has been created a challenge and an opportunity for developing various novel technologies in power generation. The proposed work discusses the primary factors that have lead to an increasing interest in DG. DG reduces line losses, increases system voltage profile and hence improves power quality. The proposed work finds out the optimal generation dispatch of the DG by artificial neural network. This ANN has been trained by optimal values of power generation by each DG at different status of network. In order to get over the insufficiency of back-propagation (BP) algorithm, after analyses of particle swarm optimization (PSO) a continues version of PSO algorithm is proposed. The objective function of PSO algorithm is a combination of cost of loss and cost of power generation by each DG with considering different load state. The feasibility of the proposed method is demonstrated for typical distribution network, and it is compared with the other researches.