Sizing energy storage to reduce renewable power curtailment considering network power flows: a distributionally robust optimisation approach

Zhongjie Guo; Wei Wei; Laijun Chen; Rui Xie; Shengwei Mei

Sizing energy storage to reduce renewable power curtailment considering network power flows: a distributionally robust optimisation approach

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Author(s): Zhongjie Guo¹ ; Wei Wei¹ ; Laijun Chen¹ ; Rui Xie¹ ; Shengwei Mei¹
- Affiliations: 1: State Key Laboratory of Power Systems, Department of Electrical Engineering , Tsinghua University , 100084 Beijing , People's Republic of China
Source: Volume 14, Issue 16, 07 December 2020, p. 3273 – 3280
DOI: 10.1049/iet-rpg.2020.0354 , Print ISSN 1752-1416, Online ISSN 1752-1424

Received 23/03/2020, Accepted 08/07/2020, Revised 23/05/2020, Published 21/07/2020

The limited reserve of fossil fuels and public awareness of environmental issues prompt the rapid development of renewable energy generation. However, the centralised utilisation of renewable energy in bulk power systems is impeded mainly by its volatile nature and transmission congestion, leading to the spillage of renewable power. The energy storage unit is expected to be a promising measure to smooth the output of renewable plants and reduce the curtailment rate. This study addresses the energy storage sizing problem in bulk power systems. To capture the operating status of the power system more accurately, the authors use a dedicated power flow model which involves voltage and reactive power. The uncertainty of renewable generation is described via inexact probability distributions encapsulated in a data-driven Wasserstein-metric based ambiguity set, based on which the renewable energy curtailment rate is formulated as a distributionally robust chance constraint. The objective is to minimise the total investment cost, and the optimal sizing problem gives rise to a distributionally robust chance-constrained program, and is reformulated as a tractable linear program via conservative approximation. Case studies conducted on the modified IEEE 30-bus and 118-bus systems demonstrate the effectiveness and performance of the proposed approach.

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Sizing energy storage to reduce renewable power curtailment considering network power flows: a distributionally robust optimisation approach

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