ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

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.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

A new approach for multi-agent coalition formation and management in the scope of electricity markets

This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.

Multi-agent negotiation for coalition formation and management in electricity markets

Negotiation is a fundamental tool for reaching understandings that allow each involved party to gain an advantage for themselves by the end of the process. In recent years, with the increasing of compe-titiveness in most sectors, negotiation procedures become present in practically all of them. One particular environment in which the competitiveness has been increasing exponentially is the electricity markets sector. This work is directed to the study of electricity markets’ partici-pating entities interaction, namely in what concerns the formation, management and operation of aggregating entities – Virtual Power Players (VPPs). VPPs are responsible for managing coalitions of market players with small market negotiating influence, which take strategic advantage in entering such aggregations, to increase their negotiating power. This chapter presents a negotiation methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using MASCEM, taking advantage of its ability to provide the means to model and simulate VPPs. VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself.

Multilevel negotiation in smart grids for VPP management of distributed resources

A multilevel negotiation mechanism for operating smart grids and negotiating in electricity markets considers the advantages of virtual power player management.

Technical and economic resources management in smart grids using heuristic optimization methods

Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response

Linking better shiftwork arrangements with safety and health management systems

OBJECTIVE: Various support measures useful for promoting joint change approaches to the improvement of both shiftworking arrangements and safety and health management systems were reviewed. A particular focus was placed on enterprise-level risk reduction measures linking working hours and management systems. METHODS: Voluntary industry-based guidelines on night and shift work for department stores and the chemical, automobile and electrical equipment industries were examined. Survey results that had led to the compilation of practicable measures to be included in these guidelines were also examined. The common support measures were then compared with ergonomic checkpoints for plant maintenance work involving irregular nightshifts. On the basis of this analysis, a new night and shift work checklist was designed. RESULTS: Both the guidelines and the plant maintenance work checkpoints were found to commonly cover multiple issues including work schedules and various job-related risks. This close link between shiftwork arrangements and risk management was important as shiftworkers in these industries considered teamwork and welfare services to be essential for managing risks associated with night and shift work. Four areas found suitable for participatory improvement by managers and workers were work schedules, ergonomic work tasks, work environment and training. The checklist designed to facilitate participatory change processes covered all these areas. CONCLUSIONS: The checklist developed to describe feasible workplace actions was suitable for integration with comprehensive safety and health management systems and offered valuable opportunities for improving working time arrangements and job content together.

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.

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.

Desenvolvimento do sistema de protecção, monitorização e gestão de baterias de iões de lítio do tipo LiFePO4 para aplicação em veículos eléctricos

A mobilidade é considerada um dos factores chave na sustentabilidade e desenvolvimento de qualquer economia. Em Portugal essa realidade não é diferente. Em 2011 verifica-se que 41% do consumo global de combustíveis pertence ao sector rodoviário [1] o que evidencia a sua relevância na economia do país. No que concerne aos veículos de tracção eléctrica, começaram a surgir nos finais do séc. XIX, e no início do séc. XX nos Estados Unidos da América representavam 38% dos veículos [2]. Diversos factores económicos e tecnológicos conduziram a um crescente desinteresse por parte da indústria em investir na produção deste tipo de veículos. Contudo com a introdução de baterias de iões de lítio em veículos de tracção eléctrica, torna-os viáveis e competitivos. Neste trabalho é proposto o desenvolvimento de um sistema de gestão de baterias de iões de lítio do tipo LiFePO4 para aplicação em veículos eléctricos. O sistema deverá assegurar a protecção das baterias e indicar o estado de carga das mesmas. Este sistema permitirá uma optimização no uso deste género de baterias, proporcionará uma melhor utilização, aumentando a sua vida útil. O sistema irá ser aplicado e testado experimentalmente no veículo eléctrico ecológico (Veeco). No âmbito do projecto Veeco foi projectado e construído um banco de ensaios utilizado na análise do comportamento das baterias, e determinar quais os requisitos necessários para o sistema de gestão desenvolvido. Foi também projectado e realizado um sistema de aquisição e processamento de dados que permite obter informações acerca da bateria, dados que estarão disponíveis no interface Homem-máquina do Veeco.

Lean thinking: Glass Wall Management

Sendo os desperdícios “Waste” associados à atividade industrial em Portugal e nos mercados globais e os seus custos inerentes, uma das maiores preocupações a todos os níveis de gestão empresarial, a filosofia “Lean” nasce como ajuda e encaminhamento na solução desta problemática. O conceito “Lean”, no que se refere à indústria, desde sempre e até aos dias de hoje, tem uma enorme ênfase, com a adoção deste conceito.Verificam-se bons resultados ao nível da redução de custos, melhoria da qualidade geral dos artigos produzidos, no controlo da produção em geral e é uma poderosa ferramenta no estreitamento da relação entre os diferentes intervenientes da cadeia de valor de determinado produto, sobretudo com fornecedores e com clientes. Com “Lean Management” e “Glass Wall Management”, em ambientes onde as empresas mais avançadas estão a procurar melhorar a sua competitividade através de uma gestão transparente (“Glass Wall Management”), a partir da qual, “toda informação relevante é compartilhada de maneira a que todos entendam a situação”(Suzaki, K, 1993), ganha cada vez mais importância a existência de uma estrutura organizacional que permita esta transparência e a consequente maturidade das empresas. Neste trabalho foram descritos alguns processos de gestão transparente desenvolvidos nos últimos dois anos numa PME portuguesa, aprofundando o processo de gestão transparente vigente e as ferramentas que ajudam a empresa e que na sua globalidade poderão ser extrapoladas a outras PME Portuguesas de modo que a informação importante e relevante seja partilhada por todos os intervenientes na estrutura empresarial, sendo entendida e desenvolvida por todos através de Edições e Revisões aos documentos mais importantes da empresa. Neste estudo foram contactadas vinte e uma PME’S portuguesas de tipologia de produção MTO (Make to Order) do sector dos estofos/mobiliário, e solicitado o preenchimento de um Questionário, tendo como fim em vista, a verificação do uso desta metodologia “Glass Wall Management” à escala empresarial portuguesa e a interpretação do Conceito Geral “Lean” como filosofia de redução de materiais, tempos e custos.

International mobility in the Pharmacy degree at the school of allied health sciences of Oporto

Background: The Erasmus program is a subprogram of the Lifelong Learning program, exclusive for Higher Education that promotes (among other initiatives), the mobility of students(studies, training or internships). The mobility of students of higher education seeks to improve the quality and development of future professionals, providing a multidisciplinary and multicultural experience. Setting: Academic Pharmacy/Pharmacy Technicians Methods: We conducted a descriptive and transversal study on the implementation of the mobility program and analyze the results, which involved applying a survey to students. Results: Since 2009/2010, the Pharmacy Degree at ESTSP has established 7 SMs protocols resulting in an average mobility of 5 students IN and 7 Students OUT. We have also endeavoured in SMp Protocols for extracurricular training with an average of 3 students OUT. The application process is normally open during the year before the mobility period. For most of the students involved, this was a first time opportunity to be in a foreign country and more than 70% choose the mobility program because it is seen as a possibility to improve their curriculum, for personal development or even to pursue employment opportunities abroad. The mobility for teachers is also encouraged. Conclusions: The exchange of experiences and training, acquired during cooperation activities should be an element of continuous dynamics and institutional affirmation. Initiatives such as the ERASMUS Program contribute to the educational and scientific enrichment, and promote international competitiveness among Higher Education Institutions.