Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Support System for Rational Use of Electric Energy

This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

A Data Mining Framework for Electric Load Profiling

This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

Real-Time Tariffs for Electric Vehicles in Wind Power based Power Systems

The use of Electric Vehicles (EVs) will change significantly the planning and management of power systems in a near future. This paper proposes a real-time tariff strategy for the charge process of the EVs. The main objective is to evaluate the influence of real-time tariffs in the EVs owners’ behaviour and also the impact in load diagram. The paper proposes the energy price variation according to the relation between wind generation and power consumption. The proposed strategy was tested in two different days in the Danish power system. January 31st and August 13th 2013 were selected because of the high quantities of wind generation. The main goal is to evaluate the changes in the EVs charging diagram with the energy price preventing wind curtailment.

Short-term Wind Speed Forecasting using Support Vector Machines

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.

Energy Resource Management under the Influence of the Weekend Transition Considering an Intensive use of Electric Vehicles

Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

Uso Sustentável de Vapor

Em 2006, a IEA (Agência Internacional de Energia), publicou alguns estudos de consumos mundiais de energia. Naquela altura, apontava na fabricação de produtos, um consumo mundial de energia elétrica, de origem fóssil de cerca 86,16 EJ/ano (86,16×018 J) e um consumo de energia nos sistemas de vapor de 32,75 EJ/ano. Evidenciou também nesses estudos que o potencial de poupança de energia nos sistemas de vapor era de 3,27 EJ/ano. Ou seja, quase tanto como a energia consumida nos sistemas de vapor da U.E. Não se encontraram números relativamente a Portugal, mas comparativamente com outros Países publicitados com alguma similaridade, o consumo de energia em vapor rondará 0,2 EJ/ano e por conseguinte um potencial de poupança de cerca 0,02 EJ/ano, ou 5,6 × 106 MWh/ano ou uma potência de 646 MW, mais do que a potência de cinco barragens Crestuma/Lever! Trata-se efetivamente de muita energia; interessa por isso perceber o onde e o porquê deste desperdício. De um modo muito modesto, pretende-se com este trabalho dar algum contributo neste sentido. Procurou-se evidenciar as possibilidades reais de os utilizadores de vapor de água na indústria reduzirem os consumos de energia associados à sua produção. Não estão em causa as diferentes formas de energia para a geração de vapor, sejam de origem fóssil ou renovável; interessou neste trabalho estudar o modo de como é manuseado o vapor na sua função de transporte de energia térmica, e de como este poderá ser melhorado na sua eficiência de cedência de calor, idealmente com menor consumo de energia. Com efeito, de que servirá se se optou por substituir o tipo de queima para uma mais sustentável se a jusante se continuarem a verificarem desperdícios, descarga exagerada nas purgas das caldeiras com perda de calor associada, emissões permanentes de vapor para a atmosfera em tanques de condensado, perdas por válvulas nos vedantes, purgadores avariados abertos, pressão de vapor exageradamente alta atendendo às temperaturas necessárias, “layouts” do sistema de distribuição mal desenhados, inexistência de registos de produção e consumos de vapor, etc. A base de organização deste estudo foi o ciclo de vapor: produção, distribuição, consumo e recuperação de condensado. Pareceu importante incluir também o tratamento de água, atendendo às implicações na transferência de calor das superfícies com incrustações. Na produção de vapor, verifica-se que os maiores problemas de perda de energia têm a ver com a falta de controlo, no excesso de ar e purgas das caldeiras em exagero. Na distribuição de vapor aborda-se o dimensionamento das tubagens, necessidade de purgas a v montante das válvulas de controlo, a redução de pressão com válvulas redutoras tradicionais; será de destacar a experiência americana no uso de micro turbinas para a redução de pressão com produção simultânea de eletricidade. Em Portugal não se conhecem instalações com esta opção. Fabricantes da República Checa e Áustria, têm tido sucesso em algumas dezenas de instalações de redução de pressão em diversos países europeus (UK, Alemanha, R. Checa, França, etc.). Para determinação de consumos de vapor, para projeto ou mesmo para estimativa em máquinas existentes, disponibiliza-se uma série de equações para os casos mais comuns. Dá-se especial relevo ao problema que se verifica numa grande percentagem de permutadores de calor, que é a estagnação de condensado - “stalled conditions”. Tenta-se também evidenciar as vantagens da recuperação de vapor de flash (infelizmente de pouca tradição em Portugal), e a aplicação de termocompressores. Finalmente aborda-se o benchmarking e monitorização, quer dos custos de vapor quer dos consumos específicos dos produtos. Esta abordagem é algo ligeira, por manifesta falta de estudos publicados. Como trabalhos práticos, foram efetuados levantamentos a instalações de vapor em diversos sectores de atividades; 1. ISEP - Laboratório de Química. Porto, 2. Prio Energy - Fábrica de Biocombustíveis. Porto de Aveiro. 3. Inapal Plásticos. Componentes de Automóvel. Leça do Balio, 4. Malhas Sonix. Tinturaria Têxtil. Barcelos, 5. Uma instalação de cartão canelado e uma instalação de alimentos derivados de soja. Também se inclui um estudo comparativo de custos de vapor usado nos hospitais: quando produzido por geradores de vapor com queima de combustível e quando é produzido por pequenos geradores elétricos. Os resultados estão resumidos em tabelas e conclui-se que se o potencial de poupança se aproxima do referido no início deste trabalho.