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 .

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.

Energy resources management for more sustainable distribution systems: an intelligent approach

Energy Resources Management can play a very relevant role in future power systems in SmartGrid context, with high penetration of distributed generation and storage systems. This paper deals with the importance of resources management in incident situation. The system to consider a high penetration of distributed generation, demand response, storage units and network reconfiguration. A case study evidences the advantages of using a flexible SCADA to control the energy resources in incident situation.

Emergency energy resource management in SmartGrids

Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

Gaseificação de resíduos: uma alternativa de gestão de resíduos sólidos urbanos na Região Autónoma dos Açores

Dissertação de Mestrado, Ambiente, Saúde e Segurança, 18 de Fevereiro de 2011, Universidade dos Açores.

The adjusted effect of maternal body mass index, energy and macronutrient intakes during pregnancy, and gestational weight gain on body composition of full-term neonates

Objective - To evaluate the effect of prepregnancy body mass index (BMI), energy and macronutrient intakes during pregnancy, and gestational weight gain (GWG) on the body composition of full-term appropriate-for-gestational age neonates. Study Design - This is a cross-sectional study of a systematically recruited convenience sample of mother-infant pairs. Food intake during pregnancy was assessed by food frequency questionnaire and its nutritional value by the Food Processor Plus (ESHA Research Inc, Salem, OR). Neonatal body composition was assessed both by anthropometry and air displacement plethysmography. Explanatory models for neonatal body composition were tested by multiple linear regression analysis. Results - A total of 100 mother-infant pairs were included. Prepregnancy overweight was positively associated with offspring weight, weight/length, BMI, and fat-free mass in the whole sample; in males, it was also positively associated with midarm circumference, ponderal index, and fat mass. Higher energy intake from carbohydrate was positively associated with midarm circumference and weight/length in the whole sample. Higher GWG was positively associated with weight, length, and midarm circumference in females. Conclusion - Positive adjusted associations were found between both prepregnancy BMI and energy intake from carbohydrate and offspring body size in the whole sample. Positive adjusted associations were also found between prepregnancy overweight and adiposity in males, and between GWG and body size in females.

Produção de hidrogénio por fotoeletrólise da água – aproveitamento do subproduto oxigénio

A noção de Economia relativa ao Hidrogénio no vocabulário dos líderes políticos e empresariais tem vindo a mudar sobretudo pela preocupação da poluição global, segurança energética e mudanças climáticas, para além do crescente domínio técnico dos cientistas e engenheiros. O interesse neste composto, que é o elemento mais simples e abundante no universo, está a crescer, devido aos avanços tecnológicos das células de combustível – as potenciais sucessoras das baterias dos aparelhos portáteis eletrónicos, centrais elétricas e motores de combustão interna. Existem métodos já bem desenvolvidos para produzir o hidrogénio. Contudo, destacase a eletrólise da água, não só por ser um método simples mas porque pode utilizar recursos energéticos renováveis, tais como, o vento ou os painéis fotovoltaicos, e aumentar a sua eficiência. Os desafios para melhorar a utilização deste método consistem em reduzir o consumo, a manutenção e os custos energéticos e aumentar a confiança, a durabilidade e a segurança. Mais ainda, consistem em rentabilizar o subproduto oxigénio pois é um gás industrial e medicinal muito importante. Neste trabalho, estudou-se a viabilidade económica da instalação de uma unidade de produção de hidrogénio e oxigénio puros por eletrólise da água, utilizando como fonte energética a energia solar, na empresa Gasoxmed – Gases Medicinais S.A., pretendendo num futuro próximo, comercializar o hidrogénio como fonte de energia, e por outro lado, aproveitar o subproduto oxigénio para utilização industrial. Projetou-se assim uma unidade utilizando um eletrolisador da marca Proton, modelo C30, com capacidade de produção gasosa de 3 kg/h (30 m3/h) de hidrogénio e 20 kg/h (15 m3/h) de oxigénio. Os gases produzidos são comprimidos num compressor da marca RIX a 200 bares para posterior armazenamento em cilindros pressurizados. Dimensionou-se ainda um sistema de miniprodução fotovoltaico com potência 250 kW para alimentar eletricamente a instalação. A realização do projeto na nova área de produção necessitará de 1.713.963€, os quais serão adquiridos por empréstimo bancário. Definiram-se todos os custos fixos associados ao projeto que perfazem um total de 62.554€/mês para os primeiros 5 anos (duração do crédito bancário) findo o qual diminuirão para 21.204€/mês. Da comercialização do hidrogénio, do oxigénio industrial e da eletricidade produzida no sistema de miniprodução de 250 kW, prevê-se um lucro mensal de 117.925€, perfazendo assim um total líquido mensal positivo de 55.371€ durante os primeiros 5 anos e a partir daí de 96.721€/mês, resultando uma amortização do investimento inicial no final do 3º ano.

Matching CO2 large point sources and potential geological storage sites in mainland Portugal

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia do Ambiente, Perfil Gestão e Sistemas Ambientais

How market power affects the behaviour of a pumped storage hydro unit in the day-ahead electricity market?

The integration of large amounts of wind energy in power systems raises important operation issues such as the balance between power demand and generation. The pumped storage hydro (PSH) units are seen as one solution for this issue, avoiding the need for wind power curtailments. However, the behavior of a PSH unit might differ considerably when it operates in a liberalized market with some degree of market power. In this regard, a new approach for the optimal daily scheduling of a PSH unit in the day-ahead electricity market was developed and presented in this paper, in which the market power is modeled by a residual inverse demand function with a variable elasticity. The results obtained show that increasing degrees of market power of the PSH unit correspond to decreasing levels of storage and, therefore, the capacity to integrate wind power is considerably reduced under these circumstances.

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.

Conceptual analogy for modelling entrapped air action in hydraulic systems

Hydraulic systems are dynamically susceptible in the presence of entrapped air pockets, leading to amplified transient reactions. In order to model the dynamic action of an entrapped air pocket in a confined system, a heuristic mathematical formulation based on a conceptual analogy to a mechanical spring-damper system is proposed. The formulation is based on the polytropic relationship of an ideal gas and includes an additional term, which encompasses the combined damping effects associated with the thermodynamic deviations from the theoretical transformation, as well as those arising from the transient vorticity developed in both fluid domains (air and water). These effects represent the key factors that account for flow energy dissipation and pressure damping. Model validation was completed via numerical simulation of experimental measurements.

A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.