The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is propos...The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is proposed in a scenario-based stochastic programming framework.The structure of the IES consists of electricity,natural gas,and heating networks which are all included in the model.Operational constraints for IES incorporating multi-type energy storage devices are also considered.The constraints of the electricity network,natural gas network and heating network are formulated,and non-linear constraints are linearized.The calculation method for the correlation of wind speed between wind farms based on historical data is proposed.Uncertainties of correlated wind power were represented by creating multiple representative scenarios with different probabilities,and this was done using the Latin hyper-cube sampling(LHS)method.The stochastic scheduling model is formulated as a mixed integer linear programming(MILP)problem with the objective function of minimizing the total expected operation cost.Numerical results on a modified PJM 5-bus electricity system with a seven-node natural gas system and a six-node heating system validate the proposed model.The results demonstrate that multi-type energy storage devices can help reduce wind power curtailments and improve the operational flexibility of IES.展开更多
The rapid increase in renewable energy integration brings with it a series of uncertainty to the transmission and distribution systems.In general,large-scale wind and solar power integration always cause short-term mi...The rapid increase in renewable energy integration brings with it a series of uncertainty to the transmission and distribution systems.In general,large-scale wind and solar power integration always cause short-term mismatch between generation and load demand because of their intermittent nature.The traditional way of dealing with this problem is to increase the spinning reserve,which is quite costly.In recent years,it has been proposed that part of the load can be controlled dynamically for frequency regulation with little impact on customers’living comfort.This paper proposes a hybrid dynamic demand control(DDC)strategy for the primary and secondary frequency regulation.In particular,the loads can not only arrest the sudden frequency drop,but also bring the frequency closer to the nominal value.With the proposed control strategy,the demand side can provide a fast and smooth frequency regulation service,thereby replacing some generation reserve to achieve a lower expense.展开更多
基金This paper was supported in part by National Natural Science Foundation of China(Grant No.51677022,51607033,and 51607034)National Key Research and Development Program of China(2017YFB0903400)+1 种基金Integrated Energy System Innovation Team of Jilin Province(20180519015JH)and International Clean Energy Talent Programme(iCET)of China Scholarship Council.
文摘The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is proposed in a scenario-based stochastic programming framework.The structure of the IES consists of electricity,natural gas,and heating networks which are all included in the model.Operational constraints for IES incorporating multi-type energy storage devices are also considered.The constraints of the electricity network,natural gas network and heating network are formulated,and non-linear constraints are linearized.The calculation method for the correlation of wind speed between wind farms based on historical data is proposed.Uncertainties of correlated wind power were represented by creating multiple representative scenarios with different probabilities,and this was done using the Latin hyper-cube sampling(LHS)method.The stochastic scheduling model is formulated as a mixed integer linear programming(MILP)problem with the objective function of minimizing the total expected operation cost.Numerical results on a modified PJM 5-bus electricity system with a seven-node natural gas system and a six-node heating system validate the proposed model.The results demonstrate that multi-type energy storage devices can help reduce wind power curtailments and improve the operational flexibility of IES.
基金supported by the Engineering Research Center Program of the National Science Foundationthe Department of Energy of USA under NSF Award Number EEC-1041877the CURENT Industry Partnership Program.
文摘The rapid increase in renewable energy integration brings with it a series of uncertainty to the transmission and distribution systems.In general,large-scale wind and solar power integration always cause short-term mismatch between generation and load demand because of their intermittent nature.The traditional way of dealing with this problem is to increase the spinning reserve,which is quite costly.In recent years,it has been proposed that part of the load can be controlled dynamically for frequency regulation with little impact on customers’living comfort.This paper proposes a hybrid dynamic demand control(DDC)strategy for the primary and secondary frequency regulation.In particular,the loads can not only arrest the sudden frequency drop,but also bring the frequency closer to the nominal value.With the proposed control strategy,the demand side can provide a fast and smooth frequency regulation service,thereby replacing some generation reserve to achieve a lower expense.