Coordination between the transmission system operator (TSO) and distribution system operators (DSOs) is a promising solution to problems related to the high penetration of distributed energy resources (DERs). This article presents a coordinated framework for multiperiod economic dispatch of transmission and distribution systems to minimize the total daily operation cost of the power system as a whole. The proposed scheme includes TSO and DSOs subproblems which are solved in a decentralized way by using a fast and efficient method, named as accelerated augmented Lagrangian method. TSO's and DSOs' subproblems are formulated based on linearized and second-order cone programming based relationships as a two-stage robust model to address the uncertainties of renewable DERs. The proposed framework has been studied on two test power systems including IEEE 14-bus integrated with three IEEE 69-bus and IEEE 118-bus integrated with thirty IEEE 69-bus test systems. Simulation results confirm the efficiency and effectivity of the proposed framework in terms of economic benefits, technical aspects such as power losses, and congestion management compared with the independent operation of transmission and distribution systems. If compared with a centralized approach and other decentralized methods, computational advantages are also confirmed, such as achieving the optimal solution with reasonable accuracy and time.
A Comprehensive and Efficient Decentralized Framework for Coordinated Multiperiod Economic Dispatch of Transmission and Distribution Systems
Siano P.
2021-01-01
Abstract
Coordination between the transmission system operator (TSO) and distribution system operators (DSOs) is a promising solution to problems related to the high penetration of distributed energy resources (DERs). This article presents a coordinated framework for multiperiod economic dispatch of transmission and distribution systems to minimize the total daily operation cost of the power system as a whole. The proposed scheme includes TSO and DSOs subproblems which are solved in a decentralized way by using a fast and efficient method, named as accelerated augmented Lagrangian method. TSO's and DSOs' subproblems are formulated based on linearized and second-order cone programming based relationships as a two-stage robust model to address the uncertainties of renewable DERs. The proposed framework has been studied on two test power systems including IEEE 14-bus integrated with three IEEE 69-bus and IEEE 118-bus integrated with thirty IEEE 69-bus test systems. Simulation results confirm the efficiency and effectivity of the proposed framework in terms of economic benefits, technical aspects such as power losses, and congestion management compared with the independent operation of transmission and distribution systems. If compared with a centralized approach and other decentralized methods, computational advantages are also confirmed, such as achieving the optimal solution with reasonable accuracy and time.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
