Decentralized Data-Driven Load Restoration in Cou-pled Transmission and Distribution System with Wind Power
Abstract : This paper proposes a new decentralized data-driven load res-toration (DDLR) scheme for transmission and distribution (TD) systems with high penetration of wind power. Robust DDLR models are constructed in order to handle uncertainties and ensure the feasibility of decentralized schemes. The Wasserstein metric is used to describe the ambiguity sets of probability distributions in order to build the complete DDLR model and realize computationally tractable formulation. A data-driven model-nested analytical target cascading (DATC) algorithm is developed to obtain the final load restoration result by iteratively solving small-scale mathematical models. The proposed DDLR scheme provides load restoration results with adjustable robustness, and performance efficiency is independent from the amount of data. The DDLR scheme makes full use of the available data while respecting information privacy requirements of independently operated systems, and ensures the feasibility of the decentralized load restoration strategy even in the worst-case condition. The effectiveness of the proposed method is validated using a small-scale TDS and a large-scale system with the IEEE 118-bus TS and thirty IEEE-33 DSs, showing high computational efficiency and superior restoration performance.
? In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations.
? Therefore, ESN needs active network management techniques. For this, the existing MG should undergo a digital transition.
? The existing SG framework is combined with multiple design scenarios and varies based on the operational area or the deployed application.
? This helps to motivate fervor and resources (both technical and capital) toward modernizing the existing electric grid infrastructure.
? The proposed decentralized restoration scheme achieves independent decision-making of the TSO and DSOs in the coupled TS-DS system, and solves the non-convergence problem of the decentralized optimization method.
? According to the North American Electric Reliability Council (NERC) reports, about 72% of the restoration process was delayed due to coordination problems between different entities in the power system.
? The coordination of the TS-DS system has been studied in unit commitment , risk assessment and economic dispatch problem
• The HPG plants work by using the power of falling water (usually in the dam) to turn a water turbine connected to a generator, which produces electricity.
• HPG is considered one of the RE technologies because the water cycle is endless and can be reused for power generation and serve other purposes.
• In the traditional approach, technicians go physically to power equipment/systems to collect data and consumer’s terminal to take readings on a periodical basis for system monitoring and billing purposes.
• SG is a collection of existing and emerging technologies working together to monitor and manage the ESN properly.
? The better performance depends on the efficient matching of power supply and demand by the coordination in the TS-DS system.
? That means although decisions are made in a decentralized way, the overall system performance target can still be achieved.
? Therefore, the result is infeasible although the objective values ATC2_F is better than the centralized optimization. In summary, the TL_ATC method not only has better convergence performance but also improves the restoration strategy by a 28.08 MW increase of the objective function value.
? Even though a positive assumption (DGs have the largest output) is made in the conventional restoration method, the coordinated one still has better performance.
|