# Market Strategy Evaluation for Prosumers in Local Electricity Markets

arXiv: https://arxiv.org/abs/2607.18272 · HTML: https://mlsanity.com/paper/2607.18272/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 30 references that are in the map.
- First posted on arXiv 12 Jun 2026.

## Builds on (most cited first, 1 of 1)

- [Systematic Comparison of Software Agents and Digital Twins: Differences, Similarities, and Synergies in Industrial Production](https://mlsanity.com/paper/2307.08421/) (2023)

## Abstract (arXiv)

Prosumers equipped with distributed generation and flexible loads form autonomous cyber-physical energy systems that control local resources and participate in local energy markets with minimal human intervention. This work develops and evaluates an agent-based simulation platform in which agents, representing prosumer households with photovoltaic systems, battery storage systems, electric vehicles, and heat pumps, participate in a uniform-price double-sided call auction. The effect of individual bidding strategies on community-level efficiency and prosumer-level financial outcomes is incompletely understood, particularly when prosumers with heterogeneous portfolios interact in one market. Four market strategies of increasing complexity are compared: a zero-intelligence constrained baseline, a boundary-price strategy, an extended storage cascade, and a market-adaptive pricing strategy. The simulation is conducted on a community of 33 prosumers at 15-minute resolution, spanning summer, winter, and spring to characterize seasonal variation. Results show that rule-based resource control substantially reduces community energy expenditure: the extended storage cascade achieves a total cost of 39.06 EUR compared to 62.38 EUR under the zero-intelligence baseline, a reduction of 37.4 %. The market-adaptive strategy yields the highest aggregate community financial gain through local energy market participation (14.40 EUR vs. 10.28 EUR for the baseline, a gain of 40.1 %) under summer conditions. Strategy effectiveness depends on both portfolio composition and seasonal supply conditions, requiring joint evaluation of resource control and pricing decisions.