2018
Authors
Villar, J; Bessa, R; Matos, M;
Publication
ELECTRIC POWER SYSTEMS RESEARCH
Abstract
This paper reviews flexibility products and flexibility markets, currently being discussed or designed to help in the operation of power systems under their evolving environment. This evolution is characterized by the increase of renewable generation and distributed energy resources (including distributed generation, self-consumption, demand response and electric vehicles). The paper is an attempt to review and classify flexibility products considering its main attributes such as scope, purpose, location or provider, and to summarize some of the main approaches to flexibility markets designs and implementations. Main current literature gaps and most promising research lines for future work are also identified.
2019
Authors
Iria, JP; Soares, FJ; Matos, MA;
Publication
IEEE TRANSACTIONS ON SMART GRID
Abstract
This paper addresses the participation of an aggregator of small prosumersin the energy and tertiary reserve markets. A two-stage stochastic optimization model is proposed to exploit the load and generation flexibility of the prosumers. The aim is to define energy and tertiary reserve bids to minimize the net cost of the aggregator buying and selling energy in the day-ahead and real-time markets, as well as to maximize the revenue of selling tertiary reserve during the real-time stage. Scenario-based stochastic programming is used to deal with the uncertainties of photovoltaic power generation, electricity demand, outdoor temperature, end-users' behavior, and preferences. A case study of 1000 small prosumers from MIBEL is used to compare the proposed strategy to two other strategies. The numerical results show that the proposed strategy reduces the bidding net cost of the aggregator by 48% when compared to an inflexible strategy typically used by retailers.
2017
Authors
Iria, JP; Soares, FJ; Matos, MA;
Publication
2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING
Abstract
This paper addresses the bidding problem faced by an aggregator of small prosumers, when participating in the day ahead energy market. A two-stage stochastic optimization model is proposed to support the aggregator in the definition of optimal and robust demand and supply bids. Stochastic programing is used to deal with uncertainty of end-users' behavior, outdoor temperature, electricity demand and PV generation. The proposed approach was compared to other benchmark strategy, using a case study of 1000 prosumers from the Iberian market.
2013
Authors
Martins, JC; Da Silva, JR; Santos, CA; Branco, FC; Nuno Fidalgo, J; Matos, MA; Couto, MJ;
Publication
IET Conference Publications
Abstract
In re-regulated markets, the maximization of profits creates the tendency to postpone investments in the network infrastructure, with negative effects on losses. In order to oppose this tendency, several countries adopt regulation directives that reward the distributors if losses are reduced and penalize them if losses increase. This is the case of Portugal which adopted loss penalty/reward scheme may be found in [1]. Given the current framework, EDP Distribuição (EDP Group), Portugal, a Distribution System Operator (DSO), has established a loss reduction program, which includes line reinforcement investments, among other actions. The main idea is to make the best investments in HV and MV network lines, considering the trade-off between benefits and costs. The ideal scenario would be, of course, to analyse all HV and MV networks and simulate possible reinforcement alternatives. However, the large number of MV feeders (about 4,000) makes this alternative unworkable. Thus, the first phase consists of developing a procedure to rank MV networks according to their potential to reduce losses. The highest scored networks are then analysed using a power system simulator. This analysis takes into account the different reinforcement alternatives and evaluates the investments costs and the saved energy over a period of 30 years - The economic time span usually considered by EDP Distribuição for this kind of operation. For the HV case, all networks were analysed. This paper synthetizes the main results obtained in these studies.
2018
Authors
Iria, J; Soares, F; Matos, M;
Publication
APPLIED ENERGY
Abstract
This paper addresses the problem faced by an aggregator of small prosumers, when participating in the energy market. The aggregator exploits the flexibility of prosumers' appliances, in order to reduce its market net costs. Two optimization procedures are proposed. A two-stage stochastic optimization model to support the aggregator in the definition of demand and supply bids. The aim is to minimize the net cost of the aggregator buying and selling energy at day-ahead and real-time market stages. Scenario-based stochastic programing is used to deal with the uncertainty of electricity demand, end-users' behavior, outdoor temperature and renewable generation. The second optimization is a model predictive control method to set the operation of flexible loads in real-time. A case study of 1000 small prosumers from the Iberian market is used to compare four day-ahead bidding strategies and two real-time control strategies, as well as the performance of combined day-ahead and real-time strategies. The numerical results show that the proposed strategies allow the aggregator to reduce the net cost by 14% compared to a benchmark typically used by retailers (inflexible strategy).
2013
Authors
Barin, A; Canha, LN; Abaide, AD; Magnago, KF; Matos, MA; Orling, RB;
Publication
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Abstract
The aim of this work is to demonstrate a novel fuzzy-based expert system for selecting renewable energy technologies (RET). Fuzzy multi-rules and fuzzy multi-sets are used to evaluate the main operational characteristics of six types of RET fuelled by biogas from municipal solid waste (MSW) landfills. The construction of the fuzzy multi-rules and fuzzy multi-sets is based on the following method: Mamdani controller using the Max-Min (inference process) and Center of Gravity (defuzzification process). Several criteria are used for the investigation: costs, efficiency, cogeneration, life-cycle and environmental impacts. The fuzzy-based expert system considers three different settings with two different constraints: costs and environmental impacts. One of the most relevant aspects presented by this work is about the previous criteria rank. It was created according to the different relevance observed among the attributes. The purpose of the proposed arrangement is to facilitate the understanding of the methodology and to increase the possibility of incorporating the decision makers' preferences on the decision-aid process. These aspects are essential to strengthen the final decision.
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