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Title: Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks

Journal Article · · IEEE Transactions on Power Systems
 [1];  [1];  [2]
  1. The Univ. of Texas at San Antonio, San Antonio, TX (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)

This study develops a tractable formulation for optimal placement and sizing of inverter-based renewable systems in multi-phase distribution networks. The goal of the formulation is to minimize the cost of inverter installation, average power import, and average distributed generation curtailment. Threephase and single-phase inverter models are presented that preserve the underlying mappings between renewable uncertainty to power injection. The uncertainty of distributed generators (DGs) and loads are characterized by a finite set of scenarios. Linear multi-phase power flow approximations are used in conjunction with scenario reduction techniques to arrive at a tractable twostage stochastic formulation for optimal DG placement and sizing. First-stage decisions are locations for DG deployment and capacity sizes, and second-stage decisions include DG real power curtailment, reactive power support, as well as feeder voltage profile. The resulting formulation is a mixed-integer second-order cone program and can be solved efficiently either by existing optimization solvers or by relaxing the binary variables to the [0,1] interval. Simulation studies on standard multi-phase IEEE test feeders promise that optimal stochastic planning of DGs reduces costs during validation, compared to a scheme where uncertainty is only represented by its average value.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1476708
Report Number(s):
NREL/JA-5D00-70143
Journal Information:
IEEE Transactions on Power Systems, Vol. 34, Issue 2; ISSN 0885-8950
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 18 works
Citation information provided by
Web of Science

Cited By (2)

Optimal allocation of distributed generations using hybrid technique with fuzzy logic controller radial distribution system journal January 2020
Stochastic Planning of Distributed PV Generation journal January 2019

Figures / Tables (7)