Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

Remuneration Structure Definition for Distributed Generation Units and Demand Response Participants Aggregation

The implementation of competitive electricity markets has changed the consumers’ and distributed generation position power systems operation. The use of distributed generation and the participation in demand response programs, namely in smart grids, bring several advantages for consumers, aggregators, and system operators. The present paper proposes a remuneration structure for aggregated distributed generation and demand response resources. A virtual power player aggregates all the resources. The resources are aggregated in a certain number of clusters, each one corresponding to a distinct tariff group, according to the economic impact of the resulting remuneration tariff. The determined tariffs are intended to be used for several months. The aggregator can define the periodicity of the tariffs definition. The case study in this paper includes 218 consumers, and 66 distributed generation units.

Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.

Optimization of Generation and Aggregated Consumption Shifting for Demand Response Programs Definition

The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.

Study of Load Curves Concerning the Influence of Socioeconomic and Cultural Issues

The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

Smart meters as a tool for energy efficiency

Gradually smart grids and smart meters are closer to the home consumers. Several countries has developed studies focused in the impacts arising from the introduction of these technologies and one of the main advantages are related to energy efficiency, observed through the awareness of the population on behalf of a more efficient consumption. These benefits are felt directly by consumers through the savings on electricity bills and also by the concessionaires through the minimization of losses in transmission and distribution, system stability, smaller loading during peak hours, among others. In this article two projects that demonstrate the potential energy savings through smart meters and smart grids are presented. The first performed in Korea, focusing on the installation of smart meters and the impact of use of user interfaces. The second performed in Portugal, focusing on the control of loads in a residence with distributed generation.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Distributed Intelligent Management of Microgrids using a Multi-Agent Simulation Platform

Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.

Resource Scheduling in Residential Microgrids Considering Energy Selling to External Players

The operation of distribution networks has been facing changes with the implementation of smart grids and microgrids, and the increasing use of distributed generation. The specific case of distribution networks that accommodate residential buildings, small commerce, and distributed generation as the case of storage and PV generation lead to the concept of microgrids, in the cases that the network is able to operate in islanding mode. The microgrid operator in this context is able to manage the consumption and generation resources, also including demand response programs, obtaining profits from selling electricity to the main network. The present paper proposes a methodology for the energy resource scheduling considering power flow issues and the energy buying and selling from/to the main network in each bus of the microgrid. The case study uses a real distribution network with 25 bus, residential and commercial consumers, PV generation, and storage.

Early physiological and biochemical responses of rice seedlings to low concentration of microcystin-LR

Microcystin-leucine and arginine (microcystin- LR) is a cyanotoxin produced by cyanobacteria like Microcystis aeruginosa, and it’s considered a threat to water quality, agriculture, and human health. Rice (Oryzasativa) is a plant of great importance in human food consumption and economy, with extensive use around the world. It is therefore important to assess the possible effects of using water contaminated with microcystin-LR to irrigate rice crops, in order to ensure a safe, high quality product to consumers. In this study, 12 and 20-day-old plants were exposed during 2 or 7 days to a M. aeruginosa extract containing environmentally relevant microcystin-LR concentrations, 0.26–78 lg/L. Fresh and dry weight of roots and leaves, chlorophyll fluorescence, glutathione S-transferase and glutathione peroxidase activities, and protein identification by mass spectrometry through two-dimensional gel electrophoresis from root and leaf tissues, were evaluated in order to gauge the plant’s physiological condition and biochemical response after toxin exposure. Results obtained from plant biomass, chlorophyll fluorescence, and enzyme activity assays showed no significant differences between control and treatment groups. How- ever, proteomics data indicates that plants respond to M. aeruginosa extract containing environmentally relevant microcystin-LR concentrations by changing their metabolism, responding differently to different toxin concentrations. Biological processes most affected were related to protein folding and stress response, protein biosynthesis, cell signalling and gene expression regulation, and energy and carbohydrate metabolism which may denote a toxic effect induced by M. aeruginosa extract and microcystin- LR. Theimplications of the metabolic alterations in plant physiology and growth require further elucidation.

Gestão de Recursos Energéticos nas SmartGrids

A sustentabilidade do sistema energético é crucial para o desenvolvimento económico e social das sociedades presentes e futuras. Para garantir o bom funcionamento dos sistemas de energia actua-se, tipicamente, sobre a produção e sobre as redes de transporte e de distribuição. No entanto, a integração crescente de produção distribuída, principalmente nas redes de distribuição de média e de baixa tensão, a liberalização dos mercados energéticos, o desenvolvimento de mecanismos de armazenamento de energia, o desenvolvimento de sistemas automatizados de controlo de cargas e os avanços tecnológicos das infra-estruturas de comunicação impõem o desenvolvimento de novos métodos de gestão e controlo dos sistemas de energia. O contributo deste trabalho é o desenvolvimento de uma metodologia de gestão de recursos energéticos num contexto de SmartGrids, considerando uma entidade designada por VPP que gere um conjunto de instalações (unidades produtoras, consumidores e unidades de armazenamento) e, em alguns casos, tem ao seu cuidado a gestão de uma parte da rede eléctrica. Os métodos desenvolvidos contemplam a penetração intensiva de produção distribuída, o aparecimento de programas de Demand Response e o desenvolvimento de novos sistemas de armazenamento. São ainda propostos níveis de controlo e de tomada de decisão hierarquizados e geridos por entidades que actuem num ambiente de cooperação mas também de concorrência entre si. A metodologia proposta foi desenvolvida recorrendo a técnicas determinísticas, nomeadamente, à programação não linear inteira mista, tendo sido consideradas três funções objectivo distintas (custos mínimos, emissões mínimas e cortes de carga mínimos), originando, posteriormente, uma função objectivo global, o que permitiu determinar os óptimos de Pareto. São ainda determinados os valores dos custos marginais locais em cada barramento e consideradas as incertezas dos dados de entrada, nomeadamente, produção e consumo. Assim, o VPP tem ao seu dispor um conjunto de soluções que lhe permitirão tomar decisões mais fundamentadas e de acordo com o seu perfil de actuação. São apresentados dois casos de estudo. O primeiro utiliza uma rede de distribuição de 32 barramentos publicada por Baran & Wu. O segundo caso de estudo utiliza uma rede de distribuição de 114 barramentos adaptada da rede de 123 barramentos do IEEE.

Modelização do despacho económico de Gás Natural

Com as variações e instabilidade dos preços do petróleo, assim como as políticas europeias para adoção de estratégias para o desenvolvimento sustentável, têm levado à procura de forma crescente de novas tecnologias e fontes de energia alternativas. Neste contexto, tem-se assistido a políticas energéticas que estimulam o aumento da produção e a utilização do gás natural, visto que é considerado uma fonte de energia limpa. O crescimento do mercado do gás natural implica um reforço significativo das redes de transporte deste combustível, quer ao nível do armazenamento e fornecimento, quer ao nível dos gasodutos e da sua gestão. O investimento em gasodutos de transporte implica grandes investimentos, que poderiam não ser remunerados da forma esperada, sendo um dos motivos para que exista em Portugal cinco distritos se veem privados deste tipo de infraestruturas. O transporte de gás natural acarreta custos elevados para os consumidores, tanto maiores quanto maior forem as quantidades de gás transacionadas e quanto maior for o percurso pelo gás natural percorrido. Assim assume especial importância a realização de um despacho de gás natural: quais as cargas que cada unidade de fornecimento de gás irá alimentar, qual a quantidade de gás natural que cada UFGs deve injetar na rede, qual o menor percurso possível para o fazer, o tipo de transporte que será utilizado? Estas questões são abordadas na presente dissertação, por forma a minimizar a função custo de transporte, diminuindo assim as perdas na rede de alta pressão e os custos de transporte que serão suportados pelos consumidores. A rede de testes adotada foi a rede nacional de transporte, constituída por 18 nós de consumos, e os tipos de transporte considerados, foram o transporte por gasoduto físico e o transporte através de gasoduto virtual – rotas de transporte rodoviário de gás natural liquefeito. Foram criados diversos cenários, baseados em períodos de inverno e verão, os diferentes cenários abrangeram de forma distinta as variáveis de forma a analisar os impactos que estas variáveis teriam no custo relativo ao transporte de gás natural. Para dar suporte ao modelo de despacho económico, foi desenvolvida uma aplicação computacional – Despacho_GN com o objetivo de despachar as quantidades de gás natural que cada UFG deveria injetar na rede, assim como apresentar os custos acumulados relativos ao transporte. Com o apoio desta aplicação foram testados diversos cenários, sendo apresentados os respectivos resultados. A metodologia elaborada para a criação de um despacho através da aplicação “Despacho_GN” demonstrou ser eficiente na obtenção das soluções, mostrando ser suficientemente rápida para realizar as simulações em poucos segundos. A dissertação proporciona uma contribuição para a exploração de problemas relacionados com o despacho de gás natural, e sugere perspectivas futuras de investigação e desenvolvimento.

Avaliação das práticas de Segurança Alimentar em Mercados Municipais

Dissertação de Mestrado em Gestão Integrada da Qualidade, Ambiente e Segurança