Published September 2018 | Version v1
Journal article

Coordinated DG-Tie planning in distribution networks based on temporal scenarios

  • 1. College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, 610065 (China)
  • 2. State Grid Sichuan Economic Research Institute, Chengdu, 610041 (China)
  • 3. School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, 610039 (China)

Description

Highlights: • A two-stage planning model is established. • A joint probability method is presented to handle uncertainties. • Temporal scenarios are formed for planning. • Economic, reliability and environmental benefits are assessed. Optimal planning of distributed generation (DG) in distribution networks is key for improving energy utilization efficiency and system operation benefits. Considering the uncertainties and temporal correlations of DG output and load demand, a multi-scenario chance-constrained economic model for DG planning is established in this paper. The model considers the comprehensive benefits of environmental, reliability and other aspects, as well as the active curtailment management of DGs. Thereafter, the model is extended to the coordinated planning of both DGs and tie lines, which is formulated as a multi-objective model. An improved genetic algorithm based solving strategy integrated with game multi-objective decision method is proposed. The feasibility and effectiveness of the proposed models are verified on the IEEE 33-bus distribution system. The impacts of natural resource distribution, confidence level, unit environmental cost and other parameters are investigated as well. The case studies also prove the integration of complementary DG generation could help improve the maximum capacity of DG and indicate the environmental benefit is the vital incentive to introduce DG into the distribution network.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.energy.2018.06.159

Additional details

Identifiers

DOI
10.1016/j.energy.2018.06.159;
PII
S0360544218312246;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
159
Journal Page Range
p. 774-785
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53000725
Subject category
S24: POWER TRANSMISSION AND DISTRIBUTION;
Descriptors DEI
COST; ECONOMIC IMPACT; ELECTRONIC EQUIPMENT; ENERGY CONSUMPTION; ENERGY DEMAND; ENERGY EFFICIENCY; ENVIRONMENTAL IMPACTS; GENETIC ALGORITHMS; MANAGEMENT; PLANNING; POWER DISTRIBUTION SYSTEMS; PROBABILITY; RELIABILITY; TIME DEPENDENCE
Descriptors DEC
ALGORITHMS; DEMAND; EFFICIENCY; EQUIPMENT; MATHEMATICAL LOGIC

Optional Information

Copyright
Copyright (c) 2018 Elsevier Ltd. All rights reserved.