Comparison of economic model predictive control and rule-based control for residential energy storage systems
Open accessAbstract
This study quantifies the benefits of implementing model predictive control on residential solar PV and energy storage systems considering a time‐of‐use demand tariff, feed‐in tariff and varying PV system sizes and battery life‐cycle costs. The control system analysed makes use of economic model predictive control (EMPC) whereby the objective function is directly tied to the economics of the system. Using residential load and PV data from an Australian distribution network service provider, the EMPC controller is compared to a rule‐based controller, highlighting the benefits of EMPC in regards to annual economic performance and battery energy throughput. The EMPC algorithm is then tested using 10 residential customers at the low voltage feeder level showing the capacity for the EMPC controller to shift peak demand and flatten the aggregated load profile of 30 residential customers.
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Fixed rules for ES control cannot anticipate future changes in load or PV generation and offer only a limited scope to enforce operating limits such as state-of-charge and inverter ratings.
“Fixed rules, such as charging when the voltage exceeds a threshold or discharging when it falls below another, cannot anticipate future changes in load or PV generation and offer only a limited scope to enforce operating limits such as state-of-charge and inverter ratings [84].”
From Voltage Regulation in Rooftop PV-Rich Distribution Networks: A Review and Detailed Case Study (2026) · cites this paper as [84]
Section 5.3 describes the rule-based controller as conditional charging and discharging based on current excess PV or household load, while Section 5.1 says the EMPC predicts future PV generation and load. Section 3.3.3 specifies state-of-charge and charging-power limits for EMPC, but the copy does not establish that fixed rules have only limited ability to enforce such limits. It also does not describe the cited rule-based controller as using voltage thresholds or discuss inverter ratings in this comparison. (LLM, conf=0.84)
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Research works printed but not linked: 14
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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 · see citing works
Self-citation
- Authors
- Banfield, B., Robinson, D. A., & Agalgaonkar, A. P.
- Affiliations
- University of Wollongong (AU)
- Corresponding author
- Banfield, Brendan
- Venue
- IET Smart Grid
- Published
- 2020-10
- Volume
- 3
- Issue
- 5
- Pages
- 722-729
- ISSN
- 2515-2947 (ISSN-L)
- OpenAlex
- W3091886603
- Cited by
- 17
- References
- 0
- Citations by year
- 2026: 6 · 2025: 2 · 2024: 1 · 2022: 4 · 2021: 3 · 2020: 1
- FWCI
- 0.69
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- IET Smart Grid (publishedVersion, cc-by)
- Research Online (University of Wollongong) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion)
- Funders
- Australian Government
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- economic model predictive control, rule-based control, residential energy storage, photovoltaic systems, battery energy storage, feed-in tariffs, peak demand shifting, load profile flattening, low-voltage feeders, energy cost reduction
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