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- Decision making for sustainable aggregation of clean energy in day-ahead market: uncertainty and riskPublication . Gomes, IsaĆas; 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.
- Wind power with energy storage arbitrage in day-ahead market by a stochastic MILP approachPublication . Gomes, IsaĆas; MelĆcio, R.; Mendes, Victor; Pousinho, H. M. I.This paper is about a support information management system for a wind power (WP) producer having an energy storage system (ESS) and participating in a day-ahead electricity market. Energy storage can play not only a leading role in mitigation of the effect of uncertainty faced by a WP producer, but also allow for conversion of wind energy into electric energy to be stored and then released at favourable hours. This storage provides capability for arbitrage, allowing an increase on profit of a WP producer, but must be supported by a convenient problem formulation. The formulation proposed for the support information management system is based on an approach of stochasticity written as a mixed integer linear programming problem. WP and market prices are considered as stochastic processes represented by a set of scenarios. The charging/discharging of the ESS are considered dependent on scenarios of market prices and on scenarios of WP. The effectiveness of the proposed formulation is tested by comparison of case studies using data from the Iberian Electricity Market. The comparison is in favour of the proposed consideration of stochasticity.
- Optimization of wind power producer participation in electricity markets with energy storage in a way of energy 4.0Publication . Gomes, IsaĆas; 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 vehiclesāa study from the perspective of an aggregatorPublication . Gomes, IsaĆas; 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.
- A novel microgrid support management system based on stochastic mixed-integer linear programmingPublication . Gomes, IsaĆas; MelĆcio, R.; Mendes, VictorThis paper focuses on a support management system for the management and operation planning of a microgrid by the new electricity market agent, the microgrid aggregator. The aggregator performs the management of microturbines, wind and photovoltaic systems, energy storage, electric vehicles, and usage of energy aiming at having the best participation in the market. Nowadays, the electricity market participation entails making decisions aided by a support and information system, which is an important part of a microgrid support management system. The microgrid support management system developed in this paper has a formulation based on a stochastic mixed-integer linear programming problem that depends on knowledge of the stochastic processes that describe the uncertain parameters. A set of plausible scenarios computed by Kernel Density Estimation sets the characterization of the random variables. But as commonly happen, a scenario reduction is necessary to avoid the need to have significant computational requirements due to the high degree of uncertainty. The scenario reduction carried out is a two-tier procedure, following a K-means clustering technique and a fast backward scenario reduction method. The case studies reveal the performance of the microgrid and validate the methodology basis conceived for the microgrid support management system.
- Dust effect impact on PV in an aggregation with wind and thermal powersPublication . Gomes, IsaĆas; 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, IsaĆas; 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.
- Assessing the value of demand response in microgridsPublication . Gomes, IsaĆas; MelĆcio, Rui; Mendes, VictorThis paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the eco nomic participation of the aggregating agent of the microgrid bidding in an electricity day-ahead market. The aggregating agent must manage microturbines, wind systems, photovoltaic systems, energy storage systems, and loads, facing load uncertainty and further uncertainties due to the use of renewable sources of energy and participation in the day-ahead market. These uncertainties can not be removed from the decision making, and, therefore, require proper formulation, and the proposed approach customizes a stochastic programming problem for this operation. Case studies show that under these uncertainties and the shifting of demand to convenient periods, there are opportunities to make decisions that lead to significant enhancements of the expected profit. These enhancements are due to better bidding in the day-ahead market and shifting energy consumption in periods of favorable market prices for exporting energy. Through the case studies it is concluded that the proposed approach is useful for the operation of a microgrid.
- Planning of aircraft fleet maintenance teamsPublication . Pereira, Duarte P.; Gomes, IsaĆas; MelĆcio, Rui; Mendes, VictorThis paper addresses a support information system for the planning of aircraft mainte nance teams, assisting maintenance managers in delivering an aircraft on time. The developed planning of aircraft maintenance teams is a computer application based on a mathematical pro gramming problem written as a minimization one. The initial decision variables are positive inte ger variables specifying the allocation of available technicians by skills to maintenance teams. The objective function is a nonlinear function balancing the time spent and costs incurred with aircraft fleet maintenance. The data involve techniciansā skills, hours of work to perform maintenance tasks, costs related to facilities, and the aircraft downtime cost. The realism of this planning entails random possibilities associated with maintenance workload data, and the inference by a procedure of Monte Carlo simulation provides a proper set of workloads, instead of going through all the possibilities. The based formalization is a nonlinear integer programming problem, converted into an equivalent pure linear integer programming problem, using a transformation from initial posi tive integer variables to Boolean ones. A case study addresses the use of this support information system to plan a team for aircraft maintenance of three lines under the uncertainty of workloads, and a discussion of results shows the serviceableness of the proposed support information system.