摘要
Uncertainties in wind power forecasting,dayahead and imbalance prices for the next day possess a great deal of risks for the profit of generation companies participating in a day-ahead electricity market.Generation companies are exposed to imbalance penalties in the balancing market for unordered mismatches between associated day-ahead power schedule and real-time generation.Coordination of wind and thermal power plants alleviates the risks raised from wind uncertainties.This paper proposes a novel optimal coordination strategy by balancing wind power forecasting deviations with thermal units in the Turkish day-ahead electricity market.The main focus of this study is to provide an optimal trade-off between the expected profit and the risk under wind uncertainty through conditional value at risk(CVa R)methodology.Coordination problem is formulated as a two-stage mixed-integer stochastic programming problem,where scenario-based wind power approach is used to handle the stochasticity of the wind power.Dynamic programming approach is utilized to attain the commitment status of thermal units.Profitability of the coordination with different day-ahead bidding strategies and trade-off between expected profit and CVa R are examined with comparative scenario studies.
Uncertainties in wind power forecasting, dayahead and imbalance prices for the next day possess a great deal of risks for the profit of generation companies participating in a day-ahead electricity market. Generation companies are exposed to imbalance penalties in the balancing market for unordered mismatches between associated day-ahead power schedule and real-time generation. Coordination of wind and thermal power plants alleviates the risks raised from wind uncertainties. This paper proposes a novel optimal coordination strategy by balancing wind power forecasting deviations with thermal units in the Turkish day-ahead electricity market. The main focus of this study is to provide an optimal trade-off between the expected profit and the risk under wind uncertainty through conditional value at risk(CVa R)methodology. Coordination problem is formulated as a two-stage mixed-integer stochastic programming problem,where scenario-based wind power approach is used to handle the stochasticity of the wind power. Dynamic programming approach is utilized to attain the commitment status of thermal units. Profitability of the coordination with different day-ahead bidding strategies and trade-off between expected profit and CVa R are examined with comparative scenario studies.
基金
the project"Intelligent system for trading on wholesale electricity market"(SMARTRADE),co-financed by the European Regional Development Fund(ERDF),through the Competitiveness Operational Programme(COP)2014-2020,priority axis 1–Research,technological development and innovation(RD&I)to support economic competitiveness and business development,Action 1.1.4–Attracting high-level personnel from abroad in order to enhance the RD capacity,contract ID P_37_418,no.62/05.09.2016,beneficiary The Bucharest University of Economic Studies.
