A multi-objective stochastic optimization framework for government-run community energy storage systems auctions

This paper proposes a multi-objective stochastic optimization framework that can be used by governments to run auctions and select the best community energy storage system (CESS) projects to support. The framework enables CESS providers and energy community members to equitably benefit from the economic value generated by CESSs. The auction accepts offers from competing CESS providers that constitute the data of the CESS location, size, install time, technology, provider, investment cost, and energy trading price. The auction is run by a government agency which selects CESS projects that maximize the economic benefits and distribute them equitably among CESS providers and community members. The multi-objective stochastic optimization accounts for the multi-year uncertainties of photovoltaic (PV) generation, real and reactive energy consumption, energy trading prices, and PV installations. We exploit the Monte Carlo simulation and scenario trees to model the aforementioned uncertainties. The K-Means clustering method is used to reduce the number of scenarios, and thereby, lessen the computational burden of the optimization problem. Our experiments on an Australian low-voltage network with a community of prosumers and consumers demonstrate that government financial support can accelerate the installation of CESSs and enhance their business viability. This can be achieved by boosting the economic benefits shared between CESS providers and communities and ensuring these benefits are distributed equitably. Also, our experiments show that the economic benefits of all stakeholders are further improved with a high growth of the number of PV installations, and a slight reduction of energy import and export prices over the planning period. • A multi-objective stochastic optimization framework to manage CESS installation. • Government-run auctions to select the best CESS projects to financially support. • Communities and CESS providers can equitably benefit from the CESS installation.

Authors

Publication Details

Journal
Journal of Energy Storage
Published
2025-07-16
DOI
https://doi.org/10.1016/j.est.2025.117614
Citations
2
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
1.46
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article

A multi-objective stochastic optimization framework for government-run community energy storage systems auctions

José Iria, Chathurika P. Mediwaththe, K.B.J. Anuradha
2 citations
Journal of Energy Storage
Smart Grid Energy Management
1.46
article

A multi-objective stochastic optimization framework for government-run community energy storage systems auctions

José Iria, Chathurika P. Mediwaththe, K.B.J. Anuradha
article en
2 citations

Abstract

This paper proposes a multi-objective stochastic optimization framework that can be used by governments to run auctions and select the best community energy storage system (CESS) projects to support. The framework enables CESS providers and energy community members to equitably benefit from the economic value generated by CESSs. The auction accepts offers from competing CESS providers that constitute the data of the CESS location, size, install time, technology, provider, investment cost, and energy trading price. The auction is run by a government agency which selects CESS projects that maximize the economic benefits and distribute them equitably among CESS providers and community members. The multi-objective stochastic optimization accounts for the multi-year uncertainties of photovoltaic (PV) generation, real and reactive energy consumption, energy trading prices, and PV installations. We exploit the Monte Carlo simulation and scenario trees to model the aforementioned uncertainties. The K-Means clustering method is used to reduce the number of scenarios, and thereby, lessen the computational burden of the optimization problem. Our experiments on an Australian low-voltage network with a community of prosumers and consumers demonstrate that government financial support can accelerate the installation of CESSs and enhance their business viability. This can be achieved by boosting the economic benefits shared between CESS providers and communities and ensuring these benefits are distributed equitably. Also, our experiments show that the economic benefits of all stakeholders are further improved with a high growth of the number of PV installations, and a slight reduction of energy import and export prices over the planning period. • A multi-objective stochastic optimization framework to manage CESS installation. • Government-run auctions to select the best CESS projects to financially support. • Communities and CESS providers can equitably benefit from the CESS installation.

Journal of Energy StorageVol. 132
Affordable and clean energy
Openalex Percentile: Top 16%
Smart Grid Energy Management
1.46
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