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- Decision making for sustainable aggregation of clean energy in day-ahead market: uncertainty and riskPublication . Gomes, Isaías; Melicio, Rui; Mendes, Victor; Pousinho, H. M. I.This paper addresses a strategy for decision-making of sustainable aggregation for clean energy participating in a day-ahead electricity market. The clean energy consists of wind turbines, photovoltaic arrays and energy storage, contributing to a better resilience of the system. The power delivered by a wind turbine or by a photovoltaic array is most certainly in deviation from the value associated with the bid accepted at a closing of a day-ahead electricity market. The deviation is due to the unpredicted variable nature of the respective sources of energy, leading to uncertainty and may imply a risk of loss of profit. So, uncertainty must be considered, and the addressed strategy considers uncertainty by scenarios of historical data and risk by the conditional value at risk. The strategy is a unified approach based on a risk-constrained and a two-stage stochastic optimization problem rewritten as a mixed-integer linear programming problem. A case study is presented to illustrate the main result and drive conclusions.
- Optimization of wind power producer participation in electricity markets with energy storage in a way of energy 4.0Publication . Gomes, Isaías; Pousinho, Hugo M. I.; Melicio, Rui; Mendes, VictorThis paper proposes a problem formulation to aid as a support information management system of a wind power producer having energy storage devices and participating in electricity markets. Energy storage can play an important role in the reduction of uncertainties faced by a wind power producer. Excess of conversion of wind energy into electric energy can be stored and then released at favorable hours. Energy storage provides capability for arbitrage and increases the revenue of the wind power producers participating in electricity markets. The formulation models the wind power and the market prices as stochastic processes represented by a set of convenient scenarios. The problem is solved by a powerful stochastic mixed integer linear programming problem. A case study using data from the Iberian Electricity Market is presented to show the aid of the formulation.
- Comparison between inflexible and flexible charging of electric vehicles—a study from the perspective of an aggregatorPublication . Gomes, Isaías; Melicio, Rui; Mendes, VictorThis paper is about the problem of the management of an aggregator of electric vehicles participating in an electricity market environment. The problem consists in the maximization of the expected profit through a formulation given by a stochastic programming problem to consider the uncertainty faced by the aggregator. This uncertainty is due to the day-ahead market prices and the driving requirements of the owners of the vehicles. Depending on the consent of the owners, inflexible charging to flexible charging is considered. Thus, the aggregator can propose different profiles and charging periods to the owners of electric vehicles. Qualitatively, as expected, the more flexible the vehicle owners, the higher the expected profit. The formulation, however, offers more to the aggregator and provides the ability to quantify the influence of consent of favorable driving requirements in the expected profit, allowing the aggregator to consider rewarding the owners of vehicles with more flexibility. Case studies addressed are for comparison of the influence of owners having inflexibility, partial flexibility, or flexibility in the expected profit of the aggregator.
- Dust effect impact on PV in an aggregation with wind and thermal powersPublication . Gomes, Isaías; Melicio, Rui; Mendes, VictorThis paper is about the dust effect impact on photovoltaic systems on the profit of an electricity market agent acting as an aggregator of photovoltaic power, wind power, thermal power, and an energy storage system. Energy storage ensures arbitrage and smoothing of the variability of photovoltaic power and wind power. The market agent intends to derive bids for submission in a day-ahead market, having consideration of the dust effect impact on the photovoltaic power. A formulation is proposed for a support decision system by a profit-based unit commitment problem solved by a stochastic programming approach, considering the operating characteristics of the virtual power plant. The photovoltaic power, wind power, and market price uncertainties are input data derived from scenarios of historical data. Case studies addressed show the advantages of the stochastic programming approach and insights concerned with the integration of uncertainties within the modeling for the schedule of the energy storage system and the dust effect impact on profit.
- Aggregation platform for Wind-PV-Thermal technology in electricity marketPublication . Gomes, Isaías; Laia, R.; Pousinho, H. M. I.; Melicio, Rui; Mendes, VictorThis paper addresses a stochastic Wind-PV- Thermal commitment to improve the bidding process of an aggregator in an electricity day-ahead market. The data for the wind and solar powers and for the market prices are given by a set of scenarios. Thermal units modeling includes start-up costs, variables costs and bounds due to constraints of technical operation, such as: ramp up/down limits and minimum up/down time limits. The modeling is carried out in order to develop a management aggregation procedure based in a stochastic programming approach formulated as a mixed integer linear mathematical programming problem. A case study is addressed with market price from the Iberian Peninsula and comparison between disaggregated and aggregated bids is discussed to address the main conclusions.