Multi-Timescale Three-Phase Unbalanced Distribution System Operation With Variable Renewable Generations

Journal Article · Tue Jul 31 00:00:00 EDT 2018 · IEEE Transactions on Smart Grid

DOI:https://doi.org/10.1109/TSG.2018.2861736· OSTI ID:1467101

Gu, Yi ^[1]; Jiang, Huaiguang ^[2]; Zhang, Jun Jason ^[3]; Zhang, Yingchen ^[2]; Wu, Hongyu ^[4]; Muljadi, Eduard ^[2]

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1. Univ. of Denver, CO (United States)
2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
3. Univ. of Denver, CO (United States); Qingdao Academy of Intelligent Industries (China)
4. Kansas State Univ., Manhattan, KS (United States)

This paper proposes a multi-timescale operational approach for a three-phase unbalanced distribution system, which contains hourly scheduling at substation level and minutes power flow operation at feeder level. In the substation scheduling model, the objective is to minimize the system cost with variable renewable generations. The given error distribution model of renewable generation is formulated as a chance constraint, and derived into a deterministic form by Gaussian mixture model (GMM) with genetic algorithm-based expectation-maximization (GAEM). In the feeder scheduling model, the system cost is further reduced with the optimal power flow (OPF) at a timescale of minutes. Considering the nonconvexity of the three-phase unbalanced OPF problem in distribution systems, the semidefinite programming (SDP) is used to relax the problem into a convex problem, and a distributed computation approach is built based on alternating direction method of multiplier (ADMM). The IEEE 123-bus distribution system, DU (University of Denver) campus distribution system, and the IEEE 8500-bus distribution system are used as the test bench for the proposed approach. And the numerical results demonstrate the effectiveness and validity of the proposed method.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE)
• Grant/Contract Number: AC36-08GO28308
• OSTI ID: 1467101
• Report Number(s): NREL/JA--5D00-72247
• Journal Information: IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 4 Vol. 10; ISSN 1949-3053
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
Gaussian mixture model
alternating direction method of multiplier
chance constraint
distribution system
expectation-maximization
optimal power flow
semidefinite programming