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Contextual and environmental awareness laboratory for energy consumption management

Contextual and environmental awareness laboratory for energy...

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Clemson University Power Systems Conference (PSC)

作者： Luis Gomes Filipe Fernandes Pedro Faria Marco Silva Zita Vale Carlos Ramos GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (IPP) Porto Portugal

The recent changes on power systems paradigm requires the active participation of small and medium players in energy management. With an electricity price fluctuation these players must manage the consumption. Lowering costs and ensuring adequate user comfort levels. Demand response can improve the power system management and bring benefits for the small and medium players. The work presented in this paper, which is developed aiming the smart grid context, can also be used in the current power system paradigm. The proposed system is the combination of several fields of research, namely multi-agent systems and artificial neural networks. This system is physically implemented in our laboratories and it is used daily by researchers. The physical implementation gives the system an improvement in the proof of concept, distancing itself from the conventional systems. This paper presents a case study illustrating the simulation of real-time pricing in a laboratory.

关键词： Buildings Optimization Smart grids Artificial neural networks Hardware Sockets Switches

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Resource scheduling in residential microgrids considering energy selling to external players

Resource scheduling in residential microgrids considering en...

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Clemson University Power Systems Conference (PSC)

作者： Bruno Canizes Marco Silva Pedro Faria Sergio Ramos Zita Vale GECAD – Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (IPP) Porto Portugal

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.

关键词： Microgrids Buildings Energy resources Load management Mathematical model Discharges (electric) Load flow

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Definition of distinct consumer modelling approaches for the participation in Demand Response programs considering distributed generation

Definition of distinct consumer modelling approaches for the...

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IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America)

作者： Fábio Pereira Pedro Faria Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

The increasing use of Distributed Generation (DG) resources, as well as the introduction of Demand Response (DR) resources has motivated significant changes in the context of competitive electricity markets and smart grids. The methodology proposed in this paper aims to allow scheduling the DG and DR programs resources, considering the implementation of distinct approaches for DR programs remuneration, such as, Steps, Quadratic, Constant, Linear and Elastic. This methodology can be used by a Virtual Power Player (VPP) that aggregates and manages small size consumption resources, enabling them to participate in DR programs. Distinct levels of energy/price from external suppliers are considered in the case study that accommodates 4 external suppliers, 66 DG units, and 218 consumers, classified into 6 types of consumers. For each context the aggregator is able to discuss on the adequate remuneration approach.

关键词： Remuneration Biological system modeling Optimal scheduling Distributed power generation Smart grids Indexes Elasticity

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Pan-European Electricity Market Simulation Considering the European Power Network Capacities

Pan-European Electricity Market Simulation Considering the E...

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International Workshop on Database and Expert Systems Applications

作者： Tiago Pinto Hugo Silva Zita Vale Gabriel Santos Isabel Praça GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (ISEP/IPP) Porto Portugal

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European electricity market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. However, physical constraints, such as the grid limited capacity, are major setbacks, which make the full European market unification a more distant goal. This paper presents a study that aims at analyzing the capability of the existing European transmission network in accommodating a full unification of the European electricity markets. This study considers the real European transmission network capacities, supporting a unified Pan-European electricity market scenario, which is simulated using the Multi-Agent System for Competitive Electricity Markets.

关键词： Europe Electricity supply industry Adaptation models Wind power generation Power grids Investment Data models

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Data Mining Approach for decision support in Real Data Based Smart Grid Scenario

Data Mining Approach for Decision Support in Real Data Based...

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International Workshop on Database and Expert Systems Applications

作者： Catarina Ribeiro Tiago Pinto Marco Silva Sérgio Ramos Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (ISEP/IPP) Porto Portugal

The increasing use of renewable energy sources and distributed generation brought several changes to the power system operation, with huge implications to the competitive electricity markets. With the eminent implementation of microgrids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a new type of player, which allows aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players` benefits. The contribution of this paper is a clustering methodology regarding the remuneration and tariff of VPP. It proposes a model to implement fair and strategic remuneration and tariff methodologies, using a clustering algorithm, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision making process is found, according to the players characteristics. The proposed clustering methodology has been tested in a real distribution network with 16 bus, including residential and commercial consumers, PV generation and storage units.

关键词： Context Electricity supply industry Remuneration Smart grids Clustering algorithms Analytical models Contracts

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Definition of the demand response events duration using differential search algorithm for aggregated consumption shifting and generation scheduling

Definition of the demand response events duration using diff...

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International Conference on Intelligent Systems Applications to Power Systems (ISAP)

作者： Pedro Faria João Soares Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

An adequate integration of demand response programs requires the definition of distinct models covering a wide diversity of operation scenarios. In this paper, the proposed methodology addresses the definition of demand response programs considering the demand shifting between periods, in scenarios of multi-period demand response events. The optimization problem refers to the minimization of the operation costs for a Virtual Power Player in the energy resources schedule. Differential search algorithm has been used in order to obtain the solutions for the optimization problem in a large set of operation scenarios. The case study illustrates the use of the proposed methodology to support the decisions concerning the duration of each demand response event and considering the consumption shifting modeling as constraints of the optimization problem.

关键词： Optimization Mathematical model Schedules Load management Context Minimization Organisms

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Two-stage stochastic day-ahead optimal resource scheduling in a distribution network with intensive use of distributed energy resources

Two-stage stochastic day-ahead optimal resource scheduling i...

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IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America)

作者： Tiago Sousa Mohammad Ali Fotouhi Ghazvini Hugo Morais Rui Castro Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Portugal GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Lyngby Denmark INESC-ID / IST Instituto Superior Técnico University of Lisbon Lisbon Portugal

The integration of renewable sources and electric vehicles will introduce new uncertainties to the optimal resource scheduling, namely at the distribution level. These uncertainties are mainly originated by the power generated by renewables sources and by the electric vehicles charge requirements. This paper proposes a two-state stochastic programming approach to solve the day-ahead optimal resource scheduling problem. The case study considers a 33-bus distribution network with 66 distributed generation units and 1000 electric vehicles.

关键词： Stochastic processes Uncertainty Nickel Batteries Programming Load flow

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Racing based approach for Metaheuristics parameter tuning

Racing based approach for Metaheuristics parameter tuning

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Iberian Conference on Information Systems and Technologies (CISTI)

作者： Ivo Pereira Ana Madureira GECAD - Knowledge Engineering and Decision Support Research Center School of Engineering from Polytechnic of Porto (ISEP/IPP) Porto Portugal

Metaheuristics are very useful to achieve good solutions in reasonable execution times. Sometimes they even obtain optimal solutions. However, to achieve near-optimal solutions, the appropriate tuning of parameters is required. This paper presents a Racing based learning module proposal for an autonomous parameter tuning of Metaheuristics. After a literature review on Metaheuristics parameter tuning and Racing approaches, the learning module is presented. A computational study for the resolution of the Scheduling problem is also presented. Comparing the preliminary obtained results with previous published results allow to conclude about the effectiveness and efficiency of this proposal.

关键词： Tuning Processor scheduling Job shop scheduling Optimization Bibliographies Genetic algorithms

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Selection constructive based hyper-heuristic for dynamic scheduling

Selection constructive based hyper-heuristic for dynamic sch...

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Iberian Conference on Information Systems and Technologies (CISTI)

作者： S. Gomes A. Madureira B. Cunha GECAD - Knowledge Engineering and Decision Support Research Center School of Engineering from Polytechnic of Porto (ISEP/IPP) Porto Portugal

Manufacturing environments require a real-time adaptation and optimization method to dynamically and intelligently maintain the current scheduling plan feasible. This way, the organization keeps clients satisfied and achieves its objectives (costs are minimized and profits maximized). This paper proposes an optimization approach - Selection Constructive based Hyper-heuristic for Dynamic Scheduling - to deal with these dynamic events, with the main goal of maintaining the current scheduling plan feasible and robust as possible. The development of this dynamic adaptation approach is inspired on evolutionary computation and hyper-heuristics. Our empirical results show that a selection constructive hyper-heuristic could be advantageous on solving dynamic adaptation optimization problems.

关键词： Dynamic scheduling Job shop scheduling Optimization Genetic algorithms Processor scheduling Evolutionary computation

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VPP Energy Resources Management considering Emissions: The case of northern Portugal 2020 to 2050

VPP Energy Resources Management considering Emissions: The c...

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IEEE Symposium Series on Computational Intelligence

作者： Joao Soares Nuno Borges Cristina Lobo Zita Vale GECAD - Knowledge Engineering and Decision-Support Research Centre Polytechnic of Porto (ISEP/IPP)

ISBN: (纸本)9781479975617

In SGs context, Distributed Generation (DG) based on renewable sources represents an alternative paradigm of energy supply and the opportunity for significant reduction in CO_2 emissions. However, strict emissions regulations might impact profit seeking Virtual Power Plants (VPP) operation. This paper addresses energy management at distribution level and evaluates if electricity emissions are worth to be considered in different time horizons. A realistic case study is developed for a chosen area of the northern region of Portugal, namely one part of the distribution grid from Vila Real managed by a VPP, with estimated penetration of Electric Vehicles (EV), several Distributed Generation (DG), Demand Response (DR) and Energy Storage Systems (ESS). The considered characteristics of the case study took into account several studies and the forecasts made in the literature. For 2030 it is expected an average CO_2 grid emission of 50 kgCO_2/MWh in Portugal. The repository-based multi-objective Particle Swarm Optimization (MOPSO) is used to tackle the developed optimization problem. Three scenarios are evaluated for the profit seeking VPP in 2020, 2030 and 2050 perspectives.

关键词： Energy Resources Management Multi-objective Particle Swarm Optimization Virtual Power Plant Smart Grid

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