Bidding in local electricity markets with cascading wholesale market integration

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.

show abstract

“…i:NP a is updated by taking the sum of consecutive steps of distributed mean m as per Equation (21).…”

Section: Cmaes Methodsmentioning

confidence: 99%

“…Later on, ref. [21] proposed the use of ACO, HyDE-DF, vortex search (VS), and estimate distribution algorithm (EDA) to solve a small variation of the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Cross Entropy Covariance Matrix Adaptation Evolution Strategy for Solving the Bi-Level Bidding Optimization Problem in Local Energy Markets

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…When considering imbalances of the local system, the interface to the wholesale system can be provided by either the LEM operator itself or by the market participants' utilities and aggregators [22]. The backup trading through aggregators has been assumed in [28], whereas in [16,29] the local market is assumed to be coupled to the wholesale market through the LEM operator. The results in [22] and [21] show a convergence of local market prices to wholesale prices even with game-theoretic models.…”

Section: Analysis Of Lem Economicsmentioning

confidence: 99%

How will local energy markets influence the pan-European day-ahead market and transmission systems? A case study for local markets in France and Germany

et al. 2022

View full text Add to dashboard Cite

“…The Federal Energy Regulatory Commission (FERC) that regulates most of the electrical grid in the U.S. issued Order 2222 in September 2020 to mandate the inclusion of distributed energy resource (DER) aggregations of 100kW or more in wholesale energy markets (Cano, 2020). Various strategies for DER wholesale energy market integration have been proposed by the scientific community to improve cost and interoperability (Lezama et al, 2021), transparency and security (Khoshjahan et al, 2021), and market pricing and settlement (Wang et al, 2015), but residual challenges in reliability, telemetry and governance have delayed FERC Order 2222 compliance for several independent system operators (Trivedi et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

A Transdisciplinary Blueprint for Energy Markets Modelled after Mycorrhizal Networks

Gould

Day²,

Reichard³

et al. 2023

tjes

View full text Add to dashboard Cite

The resource distribution strategies of trees and plants in the forest are applied here as inspiration for the development of a blueprint for transactive, hybrid solar and storage microgrids. We used the Biomimicry Institute’s Biomimicry Spiral and their toolbox as a design methodology to inform the structural and functional characteristics of this peer-to-peer microgrid energy market and propose its utility in addressing some of the challenges associated with grid integration of distributed energy resources (DERs). We reviewed literature from the ecological domain on mycorrhizal networks and biological market theory to extract key insights into the possible structure and function of a transactive energy market modeled after the mutualism between trees and mycorrhizae. Our process revealed insights into how overlapping, virtual energy markets might grow, contract, adapt, and evolve through a dynamic network-based protocol to compete and survive in rapidly changing environments. We conclude with a discussion of the promise and limitations involved in translating the derived conceptual blueprints into a cyber-physical system and its potential for deployment in the real world as a novel energy market infrastructure.

show abstract

Bidding in local electricity markets with cascading wholesale market integration

Cited by 31 publications

References 28 publications

Cross Entropy Covariance Matrix Adaptation Evolution Strategy for Solving the Bi-Level Bidding Optimization Problem in Local Energy Markets

Cross Entropy Covariance Matrix Adaptation Evolution Strategy for Solving the Bi-Level Bidding Optimization Problem in Local Energy Markets

How will local energy markets influence the pan-European day-ahead market and transmission systems? A case study for local markets in France and Germany

A Transdisciplinary Blueprint for Energy Markets Modelled after Mycorrhizal Networks

Contact Info

Product

Resources

About