ORCID
- Dharmesh Dabhi: 0000-0002-8065-9969
Abstract
The increased penetration of renewables in power distribution networks has motivated significant interest in local energy systems. One of the main goals of local energy markets is to promote the participation of small consumers in energy transactions. Such transactions in local energy markets can be modeled as a bi-level optimization problem in which players (e.g., consumers, prosumers, or producers) at the upper level try to maximize their profits, whereas a market mechanism at the lower level maximizes the energy transacted. However, the strategic bidding in local energy markets is a complex NP-hard problem, due to its inherently nonlinear and discontinued characteristics. Thus, this article proposes the application of a hybridized Cross Entropy Covariance Matrix Adaptation Evolution Strategy (CE-CMAES) to tackle such a complex bi-level problem. The proposed CE-CMAES uses cross entropy for global exploration of search space and covariance matrix adaptation evolution strategy for local exploitation. The CE-CMAES prevents premature convergence while efficiently exploring the search space, thanks to its adaptive step-size mechanism. The performance of the algorithm is tested through simulation in a practical distribution system with renewable energy penetration. The comparative analysis shows that CE-CMAES achieves superior results concerning overall cost, mean fitness, and Ranking Index (i.e., a metric used in the competition for evaluation) compared with state-of-the-art algorithms. Wilcoxon Signed-Rank Statistical test is also applied, demonstrating that CE-CMAES results are statistically different and superior from the other tested algorithms.
Keywords
Cross-Entropy Method, bi-level problem, covariance matrix, local energy marketoptimal bidding
DOI Link
Publication Date
2022-07-01
Publication Title
Energies
Volume
15
Issue
13
Deposit Date
2026-07-15
Funding
Funding: This work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276). The authors acknowledge the work facilities and equipment provided by GECAD research center (UIDB/00760/2020 and UIDP/00760/2020) and grant CEECIND/02814/2017.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional Links
Recommended Citation
Dabhi, Dharmesh; Pandya, Kartik; Soares, Joao; Lezama, Fernando; and Vale, Zita, "Cross Entropy Covariance Matrix Adaptation Evolution Strategy for Solving the Bi-Level Bidding Optimization Problem in Local Energy Markets" (2022). Research Outputs: 2025-Present. 12.
https://arrow.tudublin.ie/engschelero/12