Long-term storage(LTS)can provide various services to address seasonal fluctuations in variable renewable energy by reducing energy curtailment.However,long-term unit commitment(UC)with LTS involves mixed-integer prog...Long-term storage(LTS)can provide various services to address seasonal fluctuations in variable renewable energy by reducing energy curtailment.However,long-term unit commitment(UC)with LTS involves mixed-integer programming with large-scale coupling constraints between consecutive intervals(state-of-charge(SOC)constraint of LTS,ramping rate,and minimum up/down time constraints of thermal units),resulting in a significant computational burden.Herein,an iterative-based fast solution method is proposed to solve the long-term UC with LTS.First,the UC with coupling constraints is split into several sub problems that can be solved in parallel.Second,the solutions of the sub problems are adjusted to obtain a feasible solution that satisfies the coupling constraints.Third,a decoupling method for long-term time-series coupling constraints is proposed to determine the global optimization of the SOC of the LTS.The price-arbitrage model of the LTS determines the SOC boundary of the LTS for each sub problem.Finally,the sub problem with the SOC boundary of the LTS is iteratively solved independently.The proposed method was verified using a modified IEEE 24-bus system.The results showed that the computation time of the unit combination problem can be reduced by 97.8%,with a relative error of 3.62%.展开更多
As the intermittency of wind power is a growing concern in the day-ahead economic dispatch,this paper proposes a day-ahead economic dispatch method considering extreme scenarios of wind power by using an uncertainty s...As the intermittency of wind power is a growing concern in the day-ahead economic dispatch,this paper proposes a day-ahead economic dispatch method considering extreme scenarios of wind power by using an uncertainty set.The uncertainty set inspired by robust optimization is used to describe wind power intermittency in this paper.Four extreme scenarios based on the uncertainty set are formulated to represent the worst cases of wind power fluctuation.An economic dispatch method considering the costs of both load shedding and wind curtailment is proposed.The economic dispatch model can be easily solved by a quadratic programming method owing to the introduction of four extreme scenarios and the uncertainty set of wind power.Simulation is done using the IEEE 30-bus system and the results verify the effectiveness of the proposed method.展开更多
基金Supported by the Specific Research Project of Guangxi for Research Bases and Talents (2022AC21257)。
文摘Long-term storage(LTS)can provide various services to address seasonal fluctuations in variable renewable energy by reducing energy curtailment.However,long-term unit commitment(UC)with LTS involves mixed-integer programming with large-scale coupling constraints between consecutive intervals(state-of-charge(SOC)constraint of LTS,ramping rate,and minimum up/down time constraints of thermal units),resulting in a significant computational burden.Herein,an iterative-based fast solution method is proposed to solve the long-term UC with LTS.First,the UC with coupling constraints is split into several sub problems that can be solved in parallel.Second,the solutions of the sub problems are adjusted to obtain a feasible solution that satisfies the coupling constraints.Third,a decoupling method for long-term time-series coupling constraints is proposed to determine the global optimization of the SOC of the LTS.The price-arbitrage model of the LTS determines the SOC boundary of the LTS for each sub problem.Finally,the sub problem with the SOC boundary of the LTS is iteratively solved independently.The proposed method was verified using a modified IEEE 24-bus system.The results showed that the computation time of the unit combination problem can be reduced by 97.8%,with a relative error of 3.62%.
基金This work was supported in part by the National Key R&D Program of China under Grant 2016YFB0900100the Hubei Natural Science Foundation of China under Grant 2018CFA080.
文摘As the intermittency of wind power is a growing concern in the day-ahead economic dispatch,this paper proposes a day-ahead economic dispatch method considering extreme scenarios of wind power by using an uncertainty set.The uncertainty set inspired by robust optimization is used to describe wind power intermittency in this paper.Four extreme scenarios based on the uncertainty set are formulated to represent the worst cases of wind power fluctuation.An economic dispatch method considering the costs of both load shedding and wind curtailment is proposed.The economic dispatch model can be easily solved by a quadratic programming method owing to the introduction of four extreme scenarios and the uncertainty set of wind power.Simulation is done using the IEEE 30-bus system and the results verify the effectiveness of the proposed method.
