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Dual-Objective MPC of Community Energy Storage in LV Distribution Feeders with Rooftop Solar PV
Abstract
The technical challenges of large-scale integration of rooftop solar PV systems is a major concern for distribution network service providers (DNSPs) due to bidirectional power flow and voltage regulation issues. Energy storage devices have the potential to mitigate these adverse effects by storing excess energy during the day and providing peak shaving support at peak load. This paper presents a two-level dual-objective model predictive control (MPC) based algorithm to control DNSP owned community energy storage devices in LV residential distribution feeders. The proposed control method considers the feed-in tariff, spot price of energy and storage system operational costs. Both the economics of the system and voltage regulation are addressed. The individual modes of operation are activated by a high-level controller and a low-level controller provides the optimized charging/discharging rates according to the predefined objective cost functions. A case study 300m 4-wire LV feeder from NSW, Australia is used to demonstrate the efficacy of the proposed control method through a time series power flow simulation.
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“These include on-load tap-changing transformers (OLTCs) and voltage regulators, coordinated control of smart PV inverters, capacitor banks, distribution-level energy storage and flexible AC transmission devices such as static synchronous compensators (STATCOMs) [5,8,12,13].”
From Voltage Regulation in Rooftop PV-Rich Distribution Networks: A Review and Detailed Case Study (2026) · cites this paper as [13]
In the citing paper
“Recent studies have demonstrated the potential of community energy storage with optimization-based control to simultaneously improve voltage profiles and feeder economics [8,13]”
From Voltage Regulation in Rooftop PV-Rich Distribution Networks: A Review and Detailed Case Study (2026) · cites this paper as [13]
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Voltage Regulation in Rooftop PV-Rich Distribution Networks: A Review and Detailed Case Study
Rahman, O., Elphick, S., & Robinson, D. A. (2026) · Electronics · doi:10.3390/electronics15051074 · Cited by 3
Self-citationComparative Study of Voltage Regulation Techniques in PV Rich LV Feeders
Rahman, O., Elphick, S., & Robinson, D. A. (2024) · 2024 21st International Conference on Harmonics and Quality of Power (ICHQP) · doi:10.1109/ichqp61174.2024.10768784 · Cited by 1
Self-citation
Metadata
- Authors
- Rahman, O., Robinson, D. A., Elphick, S., & Perera, S.
- Affiliations
- University of Wollongong (AU)
- Venue
- 2021 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia)
- Publisher
- IEEE
- Published
- 2021-12-05
- Pages
- 1-5
- OpenAlex
- W4214505611
- Cited by
- 3
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1
- FWCI
- 0.39
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia) (publishedVersion)
- Research Online (University of Wollongong) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
- Keywords
- community energy storage, model predictive control, dual-objective optimization, rooftop solar, low-voltage feeders, voltage regulation, peak shaving, bidirectional power flow, feed-in tariffs, two-level control
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- CoChat. (2026). Citation check: Dual-Objective MPC of Community Energy Storage in LV Distribution Feeders with Rooftop Solar PV. https://app.cochat.ai/papers/10.1109/isgtasia49270.2021.9715615
- The paper
- Rahman, O., Robinson, D. A., Elphick, S., & Perera, S. (2021). Dual-Objective MPC of Community Energy Storage in LV Distribution Feeders with Rooftop Solar PV. 2021 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia). https://doi.org/10.1109/isgtasia49270.2021.9715615