Electrical parking lots(EPLs)play a vital role in the current energy system to achieve the decarbonization goal.This paper proposes a novel structure for integrating EPLs into a multi-carrier energy system(MCES)using ...Electrical parking lots(EPLs)play a vital role in the current energy system to achieve the decarbonization goal.This paper proposes a novel structure for integrating EPLs into a multi-carrier energy system(MCES)using a Stackelberg game theory approach.The bi-level optimization is used to model the Stackelberg game.Within this bi-level optimization model,the MCES operator minimizes the MCES cost by participating in the upstream energy market at the upper level,and the EPL operators maximize their profits by participating in the local energy market between the MCES operator and themselves at the lower level.At the upper level,the MCES operator faces uncertainties in the wind and PV systems.The bi-level multi-objective information gap decision theory(MO-IGDT)is employed to address uncertainties at the upper level of the Stackelberg game problem,resulting in a nested bi-level optimization model.The nested bi-level optimization problem is converted into a mixed-integer linear programming(MILP)optimization problem using Karush–Kuhn–Tucker(KKT)conditions.The main research assumptions pertain to EPLs’privacy and the KKT-based approach.The results demonstrate that increasing the incentive/penalty price for self-sufficiency programs from 0.0$/%to 0.2$/%,with a 50%self-sufficiency target,can reduce MCES operation costs by 10.19%.展开更多
This paper addresses the planning problem of residential micro combined heat and power (micro-CHP) systems (including micro-generation units, auxiliary boilers, and thermal storage tanks) considering the associated te...This paper addresses the planning problem of residential micro combined heat and power (micro-CHP) systems (including micro-generation units, auxiliary boilers, and thermal storage tanks) considering the associated technical and economic factors. Since the accurate values of the thermal and electrical loads of this system cannot be exactly predicted for the planning horizon, the thermal and electrical load uncertainties are modeled using a two-stage adaptive robust optimization method based on a polyhedral uncertainty set. A solution method, which is composed of column-and-constraint generation (C&CG) algorithm and block coordinate descent (BCD) method, is proposed to efficiently solve this adaptive robust optimization model. Numerical results from a practical case study show the effective performance of the proposed adaptive robust model for residential micro-CHP planning and its solution method.展开更多
基金supported by the first Cycle of ARG Grant No.ARG01-0504-230073,from the Qatar Research,Development and Innovation(QRDI)Council,Qatar.The findings herein reflect the work,and are solely the responsibility,of the authors.The authors also gratefully acknowledge support from Qatar University.
文摘Electrical parking lots(EPLs)play a vital role in the current energy system to achieve the decarbonization goal.This paper proposes a novel structure for integrating EPLs into a multi-carrier energy system(MCES)using a Stackelberg game theory approach.The bi-level optimization is used to model the Stackelberg game.Within this bi-level optimization model,the MCES operator minimizes the MCES cost by participating in the upstream energy market at the upper level,and the EPL operators maximize their profits by participating in the local energy market between the MCES operator and themselves at the lower level.At the upper level,the MCES operator faces uncertainties in the wind and PV systems.The bi-level multi-objective information gap decision theory(MO-IGDT)is employed to address uncertainties at the upper level of the Stackelberg game problem,resulting in a nested bi-level optimization model.The nested bi-level optimization problem is converted into a mixed-integer linear programming(MILP)optimization problem using Karush–Kuhn–Tucker(KKT)conditions.The main research assumptions pertain to EPLs’privacy and the KKT-based approach.The results demonstrate that increasing the incentive/penalty price for self-sufficiency programs from 0.0$/%to 0.2$/%,with a 50%self-sufficiency target,can reduce MCES operation costs by 10.19%.
文摘This paper addresses the planning problem of residential micro combined heat and power (micro-CHP) systems (including micro-generation units, auxiliary boilers, and thermal storage tanks) considering the associated technical and economic factors. Since the accurate values of the thermal and electrical loads of this system cannot be exactly predicted for the planning horizon, the thermal and electrical load uncertainties are modeled using a two-stage adaptive robust optimization method based on a polyhedral uncertainty set. A solution method, which is composed of column-and-constraint generation (C&CG) algorithm and block coordinate descent (BCD) method, is proposed to efficiently solve this adaptive robust optimization model. Numerical results from a practical case study show the effective performance of the proposed adaptive robust model for residential micro-CHP planning and its solution method.
