Bi-objective Mixed Optimal Planning for Distributed Energy Storage System of Active Distribution System

In this paper, a novel $bi$-objective mixed optimal planning method for distributed energy storage system in active distribution network is designed to take account of both feasibility and comprehensiveness planning. The direct and indirect objects of optimal planning are respectively designed to represent the effect and cost of distributed energy storage system. Above two optimal objects are integrated through dimensionless processing. The weights of two optimal objects are determined through the combination of relative comparison method and entropy method. Based on historical data, simulation on IEEE −33 nodes radial distribution network is set up and analyzed by using LINGO and MATPOWER. The simulation results demonstrate the effectiveness of the proposed method.

[1]  Reza Hemmati,et al.  Two-level planning for coordination of energy storage systems and wind-solar-diesel units in active distribution networks , 2018 .

[2]  Merlinde Kay,et al.  Battery energy storage system size determination in renewable energy systems: A review , 2018, Renewable and Sustainable Energy Reviews.

[3]  Pierluigi Mancarella,et al.  Challenges and trends of energy storage expansion planning for flexibility provision in low-carbon power systems – a review , 2017 .

[4]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[5]  Mohammad Rasol Jannesar,et al.  Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration , 2018, Applied Energy.

[6]  Azam Entezariharsini,et al.  Power fluctuation smoothing and loss reduction in grid integrated with thermal-wind-solar-storage units , 2018 .

[7]  Yujie Xu,et al.  A hybrid energy storage system with optimized operating strategy for mitigating wind power fluctuations , 2018, Renewable Energy.

[8]  Hemanshu R. Pota,et al.  Active power management in a low-voltage islanded microgrid , 2018 .

[9]  R. Hemmati,et al.  Maximizing DISCO profit in active distribution networks by optimal planning of energy storage systems and distributed generators , 2017 .

[10]  Felix F. Wu,et al.  Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing , 1989, IEEE Power Engineering Review.

[11]  Yongming Han,et al.  Review: Multi-objective optimization methods and application in energy saving , 2017 .

[12]  Hedayat Saboori,et al.  Reliability improvement in radial electrical distribution network by optimal planning of energy storage systems , 2015 .

[13]  Marcus Gallagher,et al.  Multiple community energy storage planning in distribution networks using a cost-benefit analysis , 2017 .

[14]  Seyyed Mohammad Sadegh Ghiasi,et al.  Energy storage planning in electric power distribution networks – A state-of-the-art review , 2017 .

[15]  Nikos D. Hatziargyriou,et al.  Optimal operation of smart distribution networks: A review of models, methods and future research , 2016 .

[16]  Daryoush Habibi,et al.  Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality , 2018, Renewable and Sustainable Energy Reviews.

[17]  Amin Mahmoudi,et al.  Optimal sizing of energy storage system , 2019, Variability, Scalability and Stability of Microgrids.

[18]  Antonio Vicino,et al.  Optimal sizing of energy storage systems under uncertain demand and generation , 2018, Applied Energy.

[19]  Mehdi Ehsan,et al.  A scenario-based planning framework for energy storage systems with the main goal of mitigating wind curtailment issue , 2019, International Journal of Electrical Power & Energy Systems.

[20]  Fabrizio Giulio Luca Pilo,et al.  Distribution energy storage investment prioritization with a real coded multi-objective Genetic Algorithm , 2018, Electric Power Systems Research.

[21]  A.S.N. Huda,et al.  Large-scale integration of distributed generation into distribution networks: Study objectives, review of models and computational tools , 2017 .

[22]  Xiaojuan Han,et al.  Economic evaluation of batteries planning in energy storage power stations for load shifting , 2015 .