Browsing by Author "Pousinho, H. M. I."
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- 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.
- Bidding and optimization strategies for wind-PV systems in electricity markets assisted by CPSPublication . Gomes, I. L. R.; Pousinho, H. M. I.; Melício, R.; Mendes, VictorThe variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy assisted by a cyber-physical system for supporting management decisions to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a stochastic linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modelled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market. (C) 2016 The Authors. Published by Elsevier Ltd.
- Bidding decision of wind-thermal GenCo in day-ahead marketPublication . Laia, R.; Pousinho, H. M. I.; Melício, R.; Mendes, VictorThis paper deals with the self-scheduling problem of a price-taker having wind and thermal power production and assisted by a cyber-physical system for supporting management decisions in a day-ahead electric energy market. The self-scheduling is regarded as a stochastic mixed-integer linear programming problem. Uncertainties on electricity price and wind power are considered through a set of scenarios. Thermal units are modelled by start-up and variable costs, furthermore constraints are considered, such as: ramp up/down and minimum up/down time limits. The stochastic mixed-integer linear programming problem allows a decision support for strategies advantaging from an effective wind and thermal mixed bidding. A case study is presented using data from the Iberian electricity market. (C) 2016 Published by Elsevier Ltd.
- Bidding strategy of wind-thermal energy producersPublication . Laia, R.; Pousinho, H. M. I.; Melício, R.; Mendes, VictorThis paper presents a stochastic mixed-integer linear programming approach for solving the selfscheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An effi- cient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.
- 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.
- Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead marketPublication . Gomes, Isaias L. R.; Pousinho, H. M. I.; Melicio, Rui; Mendes, VictorThis paper presents an optimal bid submission in a day-ahead electricity market for the problem of joint operation of wind with photovoltaic power systems having an energy storage device. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is one of the main characteristics of this submission. The problem is formulated as a two-stage stochastic programming problem. The optimal bids and the energy flow in the batteries are the first-stage variables and the energy deviation is the second stage variable of the problem. Energy storage is a way to harness renewable energy conversion, allowing the store and discharge of energy at conveniently market prices. A case study with data from the Iberian day-ahead electricity market is presented and a comparison between joint and disjoint operations is discussed.
- Wind power with energy storage arbitrage in day-ahead market by a stochastic MILP approachPublication . Gomes, Isaías; Melício, 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.