Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Feasibility of Electronic Tap-Changing Stabilizers for Medium Voltage Lines-Precedents and New Configurations

Thyristor-based onload tap-changing ac voltage stabilizers are cheap and robust. They have replaced most mechanical tap-changers in low voltage applications from 300 VA to 300 M. Nevertheless, this replacement hardily applies to tap-changers associated to transformers feeding medium-voltage lines (typically 69 kV primary, 34.5 kV line, 10 MVA) which need periodical maintenance of contacts and oil. The Electric Power Research Institute (EPRI) has studied the feasibility of this replacement. It detected economical problems derived from the need for series association of thyristors to manage the high voltages involved, and from the current overload developed under line fault. The paper reviews the configurations used in that field and proposes new solutions, using a compensating transformer in the main circuit and multi-winding coils in the commutating circuit, with reduced overload effect and no series association of thyristors, drastically decreasing their number and rating. The stabilizer can be installed at any point of the line and the electronic circuit can be fixed to ground. Subsequent works study and synthesize several commutating circuits in detail.

FOOD, FUEL, FORESTS, AND THE PRICING OF ECOSYSTEM SERVICES

U.S. Department of Energy (DOE), Office of Science[DE-FG02-94ER61937]

An??lise da aloca????o de investimentos de empresas privadas e p??blicas no setor el??trico brasileiro

Este trabalho analisa a aloca????o de recursos de empresas p??blicas e privadas do setor el??trico brasileiro no per??odo de 1995-2005 e a contribui????o das estrat??gias de investimentos dessas empresas para o crescimento sustentado do setor. Para tanto, primeiramente, avalia-se a evolu????o da tarifa m??dia de energia frente aos diferentes ??ndices de pre??os da economia e seus poss??veis reflexos sobre o consumo de energia e sobre os resultados financeiros das empresas. Em seguida, analisa-se o comportamento dos investimentos realizados pelas empresas p??blicas e privadas no setor el??trico ao longo do per??odo observado, tomando como refer??ncia dois modelos de determina????o de investimento, em diferentes contextos. O trabalho aponta a necessidade de continuidade da participa????o da empresa p??blica no novo modelo regulat??rio do setor el??trico brasileiro, que desempenha papel importante no ajustamento da aloca????o de recursos, com vistas a promover o desenvolvimento sustentado do setor el??trico brasileiro.

(Virtual) Agents for running electricity markets

This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, named TEMMAS (The Electricity Market Multi-Agent Simulator), explores the integration of two design constructs: (i) the specification of the environmental physical market properties and (ii) the specification of the decision-making (deliberative) and reactive agents. TEMMAS is materialized in an experimental setup involving distinct power generator companies that operate in the market and search for the trading strategies that best exploit their generating units' resources. The experimental results show a coherent market behavior that emerges from the overall simulated environment.

Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to eat her studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement.

Simulação interactiva do mercado de energia eléctrica

A área de comercialização de energia eléctrica conheceu uma profunda mudança após a liberalização do sector eléctrico, que levou à criação de algumas entidades, as quais gerem os mercados de electricidade europeus. Relativamente a Portugal e Espanha, durante esse processo de liberalização, deu-se também um acordo que os levou à criação de um mercado conjunto, um mercado Ibérico (MIBEL). Dentro deste mercado estão contemplados dois operadores, sendo que um deles representa o pólo Português (OMIP) e o outro representa o pólo Espanhol (OMEL). O OMIP contempla os mercados a prazo, ou futuros, normalmente apresenta contratos de energia comercializada com durabilidade de semanas, meses, trimestres, semestres ou mesmo anos. Diariamente estes contratos poderão vencer no OMEL, que engloba os mercados, diário e intradiário. Este, ao contrário do OMIP negoceia para o dia seguinte (mercado diário) ou para uma determinada altura do dia (mercado intra diário). O mercado diário será o exemplo usado para a criação do simulador interactivo do mercado de energia eléctrica. Este será composto por diversos utilizadores (jogadores), que através de uma plataforma HTML irão investir em centrais de energia eléctrica, negociar licitações e analisar o funcionamento e resultados deste mercado. Este jogo subdividir-se-á então em 3 fases: 1. Fase de investimento; 2. Fase de venda (licitações); 3. Fase de mercado. Na fase do investimento, o jogador terá a possibilidade de adquirir unidades de geração de energia eléctrica de seis tipos de tecnologia: 1. Central a Carvão; 2. Central de Ciclo Combinado; 3. Central Hídrica; 4. Central Eólica; 5. Central Solar; 6. Central Nuclear. Com o decorrer das jogadas o jogador poderá aumentar a sua capacidade de investimento, com a venda de energia, sendo o vencedor aquele que mais saldo tiver no fim do número de jogadas previamente definidos, ou aquele que mais depressa atingir o saldo definido como limite pelo administrador do jogo. A nível pedagógico este simulador é muito interessante pois para além de o utilizador ficar a conhecer as tecnologias em causa e as vantagens e desvantagens das centrais de energia renovável e das centrais a combustíveis fósseis, este ganha igualmente uma sensibilidade para questões de nível ambiental, tais como o aumento dos gases de estufa e o degelo resultante do aquecimento global provocado por esses gases. Para além do conhecimento adquirido na parte de energia eléctrica este jogo dará a conhecer ao utilizador o funcionamento do mercado da energia eléctrica, bem como as tácticas que este poderá usar a seu favor neste tipo de mercado.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

Geoquímica de radionuclídeos naturais e biomonitoramento em área de mineração de carvão no sul do Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

A study on the encryption algorithm for RFID tag (SEED : 8 Rounds × 64 bits block)

Although it is always weak between RFID Tag and Terminal in focus of the security, there are no security skills in RFID Tag. Recently there are a lot of studying in order to protect it, but because it has some physical limitation of RFID, that is it should be low electric power and high speed, it is impossible to protect with the skills. At present, the methods of RFID security are using a security server, a security policy and security. One of them the most famous skill is the security module, then they has an authentication skill and an encryption skill. In this paper, we designed and implemented after modification original SEED into 8 Round and 64 bits for Tag.