Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

Ground fault protectionmethods for distribution systems

The system grounding method option has a direct influence on the overall performance of the entire medium voltage network as well as on the ground fault current magnitude. For any kind of grounding systems: ungrounded system, solidly and low impedance grounded and resonant grounded, we can find advantages and disadvantages. A thorough study is necessary to choose the most appropriate grounding protection system. The power distribution utilities justify their choices based on economic and technical criteria, according to the specific characteristics of each distribution network. In this paper we present a medium voltage Portuguese substation case study and a study of neutral system with Petersen coil, isolated neutral and impedance grounded.

Sistema de controlo de um veículo autónomo terrestre

A crescente necessidade imposta pela gama de aplicações existentes, torna o estudo dos veículos autónomos terrestres um objecto de grande interesse na investigação. A utilização de robots móveis autónomos originou quer um incremento de eficiência e eficácia em inúmeras aplicações como permite a intervenção humana em contextos de elevado risco ou inacessibilidade. Aplicações de monitorização e segurança constituem um foco de utilização deste tipo de sistemas quer pela automatização de procedimentos quer pelos ganhos de eficiência (desde a eficiência de soluções multi-veículo à recolha e detecção de informação). Neste contexto, esta dissertação endereça o problema de concepção, o desenvolvimento e a implementação de um veículo autónomo terrestre, com ênfase na perspectiva de controlo. Este projecto surge pois no âmbito do desenvolvimento de um novo veículo terrestre no Laboratório de Sistemas Autónomos (LSA) do Instituto Superior de Engenharia do Porto (ISEP). É efectuado um levantamento de requisitos do sistema tendo por base a caracterização de aplicações de monitorização, transporte e vigilância em cenários exteriores pouco estruturados. Um estado da arte em veículos autónomos terrestres é apresentado bem como conceitos e tecnologias relevantes para o controlo deste tipo de sistemas. O problema de controlo de locomoção é abordado tendo em particular atenção o controlo de motores DC brushless. Apresenta-se o projecto do sistema de controlo do veículo, desde o controlo de tracção e direcção, ao sistema computacional de bordo responsável pelo controlo e supervisão da missão. A solução adoptada para a implementação mecânica da estrutura do veículo consiste numa plataforma de veículo todo terreno (motociclo 4X4) disponível comercialmente. O projecto e implementação do sistema de controlo de direcção para o mesmo é apresentado quer sob o ponto de vista da solução electromecânica, quer pelo subsistema de hardware de controlo embebido e respectivo software. Tendo em vista o controlo de tracção são apresentadas duas soluções. Uma passando pelo estudo e desenvolvimento de um sistema de raiz capaz de controlar motores BLDC de elevada potência, a segunda passando pela utilização de uma solução através de um controlador externo. A gestão energética do sistema é abordada através do projecto e implementação de um sistema de controlo e distribuição de energia específico. A implementação do veículo foi alcançada nas suas vertentes mecânica, de hardware e software, envolvendo a integração dos subsistemas projectados especialmente bem como a implementação do sistema computacional de bordo. São apresentados resultados de validação do controlo de locomoção básico quer em simulação quer descritos os testes e validações efectuados no veículo real. No presente trabalho, são também tiradas algumas conclusões sobre o desenvolvimento do sistema e sua implementação bem como perspectivada a sua evolução futura no contexto de missões coordenadas de múltiplos veículos robóticos.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

Desenvolvimento de ferramenta de apoio ao dimensionamento de sistemas de autoconsumo fotovoltaico em ambiente doméstico

Nos últimos anos, tem-se assistido a uma maior preocupação com o meio ambiente, a atual conjuntura mundial está cada vez mais direcionada para a eficiência energética e para a utilização de fontes de energias renováveis. Os principais governos mundiais, incluindo o português, já perceberam a necessidade de enveredar por esse caminho e nesse sentido aplicam medidas que direcionam e consciencializam a população para a eficiência energética e para as energias renováveis. Em Portugal, o setor das energias renováveis assume atualmente uma posição de extrema importância, resultante da expressão que governo português tem vindo a implementar no panorama energético nacional, da qual resulta uma importante contribuição para o desenvolvimento económico, na criação de riqueza e geração de emprego. Neste contexto, e no caso particular da energia fotovoltaica têm sido implementadas medidas que incentivam a aposta nesta tecnologia, prova disso é o Decreto-Lei n.º 153/2014 aprovado em conselho de ministros em Setembro de 2014, que promove essencialmente o autoconsumo. O autoconsumo consiste na utilização de painéis fotovoltaicos para produção de energia elétrica para consumo próprio com ou sem recurso a equipamentos de acumulação. Em termos práticos, este sistema permite que os consumidores produzam a sua própria energia através de uma fonte renovável ao invés de adquirir essa energia na rede elétrica de serviço público. As políticas de incentivo ao autoconsumo proporcionam uma oportunidade para os consumidores interessados em investir na produção da própria energia elétrica, neste sentido e de forma a ajudar no dimensionamento de unidades de produção de autoconsumo foi desenvolvida, no âmbito desta tese, uma ferramenta de apoio ao dimensionamento de sistemas de autoconsumo fotovoltaico sem acumulação em ambiente doméstico, com o objetivo de estimar as necessidades de potência fotovoltaica a instalar em habitações de baixa tensão normal. Na base da construção desta ferramenta estiveram essencialmente os perfis de consumo, aprovados pela Entidade Reguladora dos Serviços Energéticos, de todos os clientes finais que não dispõem de equipamento de medição com registo de consumos e também a estimativa de produção fotovoltaica desenvolvida pelo Centro Comum de Investigação da Comissão Europeia. A aplicação desenvolvida tem como principal funcionalidade proporcionar ao utilizador o dimensionamento de unidades de produção de autoconsumo fotovoltaico, mediante a introdução de alguns dados tais como o distrito, a potência contratada, a tarifa e o consumo energético anual. Esta aplicação apresenta resultados relativos ao dimensionamento do sistema, como é o caso da potência a instalar e da estimativa de produção fotovoltaica anual, e resultados relativos à análise económica do sistema como é o caso do valor atual líquido, da taxa interna de rentabilidade e do payback do investimento.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Increase of the Delivered Power Probability in Distribution Networks using Pareto DC Programming

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network

Multi-criteria optimisation approach to increase the delivered power in radial distribution networks

This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .