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Multi-Objective Planning of Multi-Type Distributed Generation Considering Timing Characteristics and Environmental Benefits

Author

Listed:
  • Yajing Gao

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jianpeng Liu

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jin Yang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Haifeng Liang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jiancheng Zhang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

Abstract

This paper presents a novel approach to multi-type distributed generation (DG) planning based on the analysis of investment and income brought by grid-connected DG. Firstly, the timing characteristics of loads and DG outputs, as well as the environmental benefits of DG are analyzed. Then, on the basis of the classification of daily load sequences, the typical daily load sequence and the typical daily output sequence of DG per unit capacity can be computed. The proposed planning model takes the location, capacity and types of DG into account as optimization variables. An improved adaptive genetic algorithm is proposed to solve the model. Case studies have been carried out on the IEEE 14-node distribution system to verify the feasibility and effectiveness of the proposed method and model.

Suggested Citation

  • Yajing Gao & Jianpeng Liu & Jin Yang & Haifeng Liang & Jiancheng Zhang, 2014. "Multi-Objective Planning of Multi-Type Distributed Generation Considering Timing Characteristics and Environmental Benefits," Energies, MDPI, vol. 7(10), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:10:p:6242-6257:d:40799
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    Citations

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    Cited by:

    1. Kumar Mahesh & Perumal Nallagownden & Irraivan Elamvazuthi, 2016. "Advanced Pareto Front Non-Dominated Sorting Multi-Objective Particle Swarm Optimization for Optimal Placement and Sizing of Distributed Generation," Energies, MDPI, vol. 9(12), pages 1-23, November.
    2. Yajing Gao & Huaxin Cheng & Jing Zhu & Haifeng Liang & Peng Li, 2016. "The Optimal Dispatch of a Power System Containing Virtual Power Plants under Fog and Haze Weather," Sustainability, MDPI, vol. 8(1), pages 1-22, January.
    3. Qingwu Gong & Jiazhi Lei & Jun Ye, 2016. "Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Cost of Operation Risk," Energies, MDPI, vol. 9(1), pages 1-18, January.
    4. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
    5. Hou, Hui & Xu, Tao & Wu, Xixiu & Wang, Huan & Tang, Aihong & Chen, Yangyang, 2020. "Optimal capacity configuration of the wind-photovoltaic-storage hybrid power system based on gravity energy storage system," Applied Energy, Elsevier, vol. 271(C).
    6. Melchiorre Casisi & Stefano Costanzo & Piero Pinamonti & Mauro Reini, 2018. "Two-Level Evolutionary Multi-objective Optimization of a District Heating System with Distributed Cogeneration," Energies, MDPI, vol. 12(1), pages 1-23, December.
    7. Xiangang Peng & Lixiang Lin & Weiqin Zheng & Yi Liu, 2015. "Crisscross Optimization Algorithm and Monte Carlo Simulation for Solving Optimal Distributed Generation Allocation Problem," Energies, MDPI, vol. 8(12), pages 1-19, December.
    8. Mariaud, Arthur & Acha, Salvador & Ekins-Daukes, Ned & Shah, Nilay & Markides, Christos N., 2017. "Integrated optimisation of photovoltaic and battery storage systems for UK commercial buildings," Applied Energy, Elsevier, vol. 199(C), pages 466-478.
    9. Ashraf Ramadan & Mohamed Ebeed & Salah Kamel & Almoataz Y. Abdelaziz & Hassan Haes Alhelou, 2021. "Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    10. Yongchun Yang & Xiaodan Wang & Jingjing Luo & Jie Duan & Yajing Gao & Hong Li & Xiangning Xiao, 2017. "Multi-Objective Coordinated Planning of Distributed Generation and AC/DC Hybrid Distribution Networks Based on a Multi-Scenario Technique Considering Timing Characteristics," Energies, MDPI, vol. 10(12), pages 1-29, December.
    11. Hong Li & Xiaodan Wang & Jie Duan & Feifan Chen & Yajing Gao, 2018. "Locating Optimization of an Integrated Energy Supply Centre in a Typical New District Based on the Load Density," Energies, MDPI, vol. 11(4), pages 1-22, April.
    12. Wu, Xuewei & Zhang, Bin & Nielsen, Mads Pagh & Chen, Zhe, 2024. "Multi-stage planning of integrated electricity-gas-heating system in the context of carbon emission reduction," Applied Energy, Elsevier, vol. 358(C).
    13. Theo, Wai Lip & Lim, Jeng Shiun & Wan Alwi, Sharifah Rafidah & Mohammad Rozali, Nor Erniza & Ho, Wai Shin & Abdul-Manan, Zainuddin, 2016. "An MILP model for cost-optimal planning of an on-grid hybrid power system for an eco-industrial park," Energy, Elsevier, vol. 116(P2), pages 1423-1441.
    14. José Raúl Castro & Maarouf Saad & Serge Lefebvre & Dalal Asber & Laurent Lenoir, 2016. "Coordinated Voltage Control in Distribution Network with the Presence of DGs and Variable Loads Using Pareto and Fuzzy Logic," Energies, MDPI, vol. 9(2), pages 1-16, February.
    15. Yajing Gao & Wenhai Yang & Jing Zhu & Jiafeng Ren & Peng Li, 2017. "Evaluating the Effect of Distributed Generation on Power Supply Capacity in Active Distribution System Based on Sensitivity Analysis," Energies, MDPI, vol. 10(10), pages 1-14, September.

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