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Energies
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Demand Response Management in Electricity Markets
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Demand Response Management in Electricity Markets

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 5488

Special Issue Editors

Dr. Miadreza Shafie-khah

E-Mail Website
Guest Editor
School of Technology and Innovations, University of Vaasa, 65200 Vaasa, Finland
Interests: smart grid; demand response; electric vehicle; power system; electricity market
Special Issues, Collections and Topics in MDPI journals
Dr. Mohammad Ali Fotouhi Ghazvini

E-Mail Website
Guest Editor
Division of Electric Power Engineering, Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden
Interests: power system operation and control; electricity market; integrated energy systems; energy management; smart grid

Special Issue Information

Dear Colleagues,

Sustainable development and climate change mitigation are two of the main challenges facing the energy sector. Energy consumption is intrinsically dependent on fossil fuels since they serve a significant portion of energy demand, whether through electricity generation, transportation, or other sectors. Therefore, to achieve the environmental goals stipulated by worldwide governments, increased integration of renewable energy resources (RESs) in electricity generation is crucial. However, RESs have uncertainty and volatility associated with their primary sources, e.g., wind speed and solar radiation. This leads to a loss of flexibility in the power system and eventually reduces reliability and security. Among different options to supply the flexibility, demand response (DR) and electricity markets are two economical options that can provide flexibility with the lowest costs. The increasing penetration of energy-intensive loads, such as electric vehicles and heat pumps, that are controllable enables the demand side to provide flexibility for the grid. Developing models in the planning, operation, and control of demand-side resources should enhance the flexibility of the energy systems and satisfy the consumers. Besides, energy policies and energy market regulations should enable DR strategies in industries, energy communities, and small-scale energy systems such as buildings and homes. This Special Issue aims at encouraging researchers and industries to report their solutions for the design of the system structure as well as of operational and control models for DR management in electricity markets and ancillary services.

Dr. Miadreza Shafie-khah
Dr. Mohammad Ali Fotouhi Ghazvini
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 2600 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

  • demand response
  • demand-side management
  • demand-side response
  • control
  • operation
  • planning
  • management
  • electricity market
  • energy market
  • ancillary service
  • market structure
  • peer-to-peer
  • flexibility

Published Papers (2 papers)

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Research

22 pages, 2725 KiB  
Article
On Optimistic and Pessimistic Bilevel Optimization Models for Demand Response Management
by Tamás Kis, András Kovács and Csaba Mészáros
Energies 2021, 14(8), 2095; https://0-doi-org.brum.beds.ac.uk/10.3390/en14082095 - 09 Apr 2021
Cited by 5 | Viewed by 2148
Abstract
This paper investigates bilevel optimization models for demand response management, and highlights the often overlooked consequences of a common modeling assumption in the field. That is, the overwhelming majority of existing research deals with the so-called optimistic variant of the problem where, in [...] Read more.
This paper investigates bilevel optimization models for demand response management, and highlights the often overlooked consequences of a common modeling assumption in the field. That is, the overwhelming majority of existing research deals with the so-called optimistic variant of the problem where, in case of multiple optimal consumption schedules for a consumer (follower), the consumer chooses an optimal schedule that is the most favorable for the electricity retailer (leader). However, this assumption is usually illegitimate in practice; as a result, consumers may easily deviate from their expected behavior during realization, and the retailer suffers significant losses. One way out is to solve the pessimistic variant instead, where the retailer prepares for the least favorable optimal responses from the consumers. The main contribution of the paper is an exact procedure for solving the pessimistic variant of the problem. First, key properties of optimal solutions are formally proven and efficiently solvable special cases are identified. Then, a detailed investigation of the optimistic and pessimistic variants of the problem is presented. It is demonstrated that the set of optimal consumption schedules typically contains various responses that are equal for the follower, but bring radically different profits for the leader. The main procedure for solving the pessimistic variant reduces the problem to solving the optimistic variant with slightly perturbed problem data. A numerical case study shows that the optimistic solution may perform poorly in practice, while the pessimistic solution gives very close to the highest profit that can be achieved theoretically. To the best of the authors’ knowledge, this paper is the first to propose an exact solution approach for the pessimistic variant of the problem. Full article
(This article belongs to the Special Issue Demand Response Management in Electricity Markets)
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12 pages, 2597 KiB  
Article
Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach
by Eunjung Lee, Keon Baek and Jinho Kim
Energies 2020, 13(23), 6355; https://0-doi-org.brum.beds.ac.uk/10.3390/en13236355 - 02 Dec 2020
Cited by 14 | Viewed by 2452
Abstract
The rapid increase in renewable energy resources has resulted in the increasing need for a demand flexibility program (DFP) from industrial load resources as a solution to oversupply and peak load spikes. However, to reasonably estimate the DR potential flexibility, the load characteristics [...] Read more.
The rapid increase in renewable energy resources has resulted in the increasing need for a demand flexibility program (DFP) from industrial load resources as a solution to oversupply and peak load spikes. However, to reasonably estimate the DR potential flexibility, the load characteristics must be analyzed and potential assessment formulas must be validated. Thus, in this study, a novel method is proposed to evaluate the DR potential flexibility of industrial loads according to a process of related load-characteristic data analysis. The proposed potential-estimation model considers frequency, consistency, and DR event operation scores during designated ramp-up and ramp-down time intervals separately. A case study was conducted by considering typical cement industry process with actual power-consumption data analysis for demonstrating the test system. The results confirm that load reduction of more than half of the usual power consumption is possible if a potential score is about 0.27 in cement industry cases. Thus, the proposed method can be used as an indicator to determine how an industrial load is adequate for obtaining a DFP while suggesting meaningful implications through industrial load-resource data analysis. Full article
(This article belongs to the Special Issue Demand Response Management in Electricity Markets)
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