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Demand Response with Volt/Var Optimization for unbalanced active distribution systems

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  • Vijayan, Vineeth
  • Mohapatra, Abheejeet
  • Singh, S.N.

Abstract

The strong mutual influence of Demand Response (DR) and Volt/Var Optimization (VVO) on each other has largely been ignored in most of the previous schemes. Those research studies, which collectively consider DR and VVO, deal with minimal devices. Further, rescheduling of loads participating in DR and phase-specific operations of voltage control devices, such as Capacitor Banks (CBs), Voltage Regulators (VRs), On-Load Tap Changer (OLTC), and inverters of the solar photovoltaic sources, in an active three-phase distribution system significantly cause the unbalance levels. Hence, a comprehensive formulation, which considers DR to reduce peak load, VVO to minimize loss, and unbalance minimization using elastic loads, inverters, OLTC, VRs, and CBs, is proposed in this paper for three-phase unbalanced active distribution systems. Most previous studies deal with the cost while integrating DR and VVO, favoring real power rescheduling. In this research, rescheduling of kVA loads, affecting VVO devices’ operations, is adopted. A load factor-based load shifting index is proposed and utilized for this purpose. The proposed formulation aims to minimize the substation transformer’s current unbalance levels that seem to increase while limiting bus voltage unbalance factors. The proposed scheme is solved using the multi-objective particle swarm optimization and is tested on the modified IEEE 13-bus and IEEE 123-bus test systems. Compared with the Conservation Voltage Reduction (CVR) based method, the obtained results reveal that the proposed formulation minimizes peak load, loss, and unbalances more effectively while managing voltage rise or drop issues more efficiently without source or load curtailments.

Suggested Citation

  • Vijayan, Vineeth & Mohapatra, Abheejeet & Singh, S.N., 2021. "Demand Response with Volt/Var Optimization for unbalanced active distribution systems," Applied Energy, Elsevier, vol. 300(C).
  • Handle: RePEc:eee:appene:v:300:y:2021:i:c:s0306261921007674
    DOI: 10.1016/j.apenergy.2021.117361
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    References listed on IDEAS

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    1. Chaminda Bandara, W.G. & Godaliyadda, G.M.R.I. & Ekanayake, M.P.B. & Ekanayake, J.B., 2020. "Coordinated photovoltaic re-phasing: A novel method to maximize renewable energy integration in low voltage networks by mitigating network unbalances," Applied Energy, Elsevier, vol. 280(C).
    2. Mak, Davye & Choi, Dae-Hyun, 2020. "Optimization framework for coordinated operation of home energy management system and Volt-VAR optimization in unbalanced active distribution networks considering uncertainties," Applied Energy, Elsevier, vol. 276(C).
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    Cited by:

    1. Mauro Jurado & Eduardo Salazar & Mauricio Samper & Rodolfo Rosés & Diego Ojeda Esteybar, 2023. "Day-Ahead Operational Planning for DisCos Based on Demand Response Flexibility and Volt/Var Control," Energies, MDPI, vol. 16(20), pages 1-20, October.
    2. Jeon, Soi & Choi, Dae-Hyun, 2022. "Joint optimization of Volt/VAR control and mobile energy storage system scheduling in active power distribution networks under PV prediction uncertainty," Applied Energy, Elsevier, vol. 310(C).
    3. Masoud Hamedi & Hossein Shayeghi & Seyedjalal Seyedshenava & Amin Safari & Abdollah Younesi & Nicu Bizon & Vasile-Gabriel Iana, 2023. "Developing an Integration of Smart-Inverter-Based Hosting-Capacity Enhancement in Dynamic Expansion Planning of PV-Penetrated LV Distribution Networks," Sustainability, MDPI, vol. 15(14), pages 1-27, July.
    4. Daiva Stanelyte & Neringa Radziukyniene & Virginijus Radziukynas, 2022. "Overview of Demand-Response Services: A Review," Energies, MDPI, vol. 15(5), pages 1-31, February.
    5. Liu, Youquan & Li, Huazhen & Zhu, Jiawei & Lin, Yishuai & Lei, Weidong, 2023. "Multi-objective optimal scheduling of household appliances for demand side management using a hybrid heuristic algorithm," Energy, Elsevier, vol. 262(PA).

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