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Special Issue "Optimal Scheduling of Flexible Resources in Modern Energy Markets"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "C: Energy Economics and Policy".

Deadline for manuscript submissions: 30 September 2022 | Viewed by 1094

Special Issue Editors

Dr. Saber Talari
E-Mail Website
Guest Editor
Faculty of Management, Economics, and Social Sciences, University of Cologne, 50923 Cologne, Germany
Interests: energy markets; stochastic optimization; demand side management; renewable resources
Prof. Dr. Wolfgang Ketter
E-Mail Website
Guest Editor
Faculty of Management, Economics, and Social Sciences, University of Cologne, 50923 Cologne, Germany
Interests: artificial intelligence; energy economics; machine learning; shared mobility; sustainability

Special Issue Information

Dear Colleagues,

As the number of distributed energy resources (DERs) (e.g., energy storage systems, PVs, wind generators, heat pumps, and electric vehicles) is sharply rising, especially in distribution energy networks, the network is facing more challenges such as congestion in addition to voltage and frequency distortion. Since DERs together with demand response programs can play a role as flexibility resources, operators can leverage these potentials to overcome the growing network challenges.

In order to coordinate flexible resources, a proper market can be established such that the resources’ owners/operators are incentivized to participate and share their asset flexibility with the network operator.

Within modern markets, where flexibility/energy is coordinated among providers, the design varies from centralized to decentralized operation, and the clearing algorithm can also differ, e.g., varying from zonal pricing to nodal pricing. Hence, the optimization method that is applied to various market designs for providing an efficient market will also differ.

This Special Issue invites the submission of high-quality research papers presenting novel ideas covering a wide range of topics in association with the optimal scheduling of flexible resources in the energy market, including local flexibility market, distributed energy resources, peer-to-peer trading, distributed optimization, decentralized optimization, congestion management, optimal power flow, demand response, and stochasticity.

Dr. Saber Talari
Prof. Dr. Wolfgang Ketter
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • congestion management
  • distributed energy resources
  • demand response
  • distributed and decentralized optimization
  • optimal power flow
  • local flexibility market
  • market mechanism design
  • peer-to-peer trading
  • stochasticity

Published Papers (1 paper)

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Research

Article
Evaluation of Hierarchical, Multi-Agent, Community-Based, Local Energy Markets Based on Key Performance Indicators
Energies 2022, 15(10), 3575; https://doi.org/10.3390/en15103575 - 13 May 2022
Viewed by 718
Abstract
In recent years, local energy markets (LEMs) have been introduced to empower end-customers within energy communities at the distribution level of the power system, in order to be able to trade their energy locally in a competitive and fair environment. However, there is [...] Read more.
In recent years, local energy markets (LEMs) have been introduced to empower end-customers within energy communities at the distribution level of the power system, in order to be able to trade their energy locally in a competitive and fair environment. However, there is still some challenge with regard to the most efficient approach in organising the LEMs for the electricity exchange between consumers and prosumers while ensuring that they are responsible for their electricity-related choices, and concerning which LEM model is suitable for which prosumer or consumer type. This paper presents a hierarchical model for the organisation of agent-based local energy markets. According to the proposed model, prosumers and consumers are enabled to transact electricity within the local energy community and with the grid in a coordinated manner to ensure technical and economic benefits for the LEM’s agents. The model is implemented in a software tool called Grid Singularity Exchange (GSyE), and it is verified in a real German energy community case study. The simulation results demonstrate that trading electricity within the LEM offers economic and technical benefits compared to transacting with the up-stream grid. This can further lead to the decarbonization of the power system sector. Furthermore, we propose two models for LEMs consisting of multi-layer and single-layer hierarchical agent-based structures. According to our study, the multi-layer hierarchical model is more profitable for household prosumers as compared to trading within the single-layer hierarchical LEM. However, the single-layer LEM is more be beneficial for industrial prosumers. Full article
(This article belongs to the Special Issue Optimal Scheduling of Flexible Resources in Modern Energy Markets)
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