Decentralized stochastic optimization based planning of integrated transmission and distribution networks with distributed generation penetration

Jia Liu, Haozhong Cheng, Pingliang Zeng, Liangzhong Yao, Ce Shang and Yuan Tian

Applied Energy, 2018, vol. 220, issue C, 800-813

Abstract: In a current power system, numbers of distribution networks are physically connected to a transmission network at different boundary buses. As the planning solution of one network significantly influences the decisions made by planners of other networks, the transmission and distribution networks should coordinate and cooperate with each other to design the entire power system in a secure and economic manner. Inspired by decentralized and hierarchical optimization theories, this paper proposes a coordinated decision-making framework to determine the planning scheme and scenario based generation schedule for integrated transmission and distribution networks (ITDNs) with the penetration of distributed generations (DGs). A stochastic bi-level hierarchy is presented to decompose the centralized optimal planning of ITDNs. The obtained subproblems for independent transmission and distribution networks are formulated and relaxed to convex models. An improved iterative solution procedure is developed by exploiting the cascaded structure of the problems. Theoretical analysis and numerical results demonstrate the convergence properties of the decentralized optimization algorithm. The proposed coordinated planning framework outperforms conventional independent methods by decreasing expansion investment and improving DG accommodation.

Keywords: Transmission network; Distributed generation; Decentralized optimization; Stochastic planning; Distribution (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.apenergy.2018.03.016

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