Optimal Operation and Control of Low-Carbon Energy Systems on the Demand Side
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".
Deadline for manuscript submissions: 20 March 2025 | Viewed by 377
Special Issue Editors
Interests: renewable energy; power system control
Special Issues, Collections and Topics in MDPI journals
Interests: application of artificial intelligence in power system; optimization and control of new power system
Interests: peer-to-peer energy market; hybrid energy market; stability constraints; distributionally robust optimization in power system
Interests: resilience of distribution systems; optimized control; intelligent information processing
Interests: modeling, optimization, and control of flexible loads (especially district cooling system); storage systems for providing frequency regulation; operating reserves and peak-shaving services in smart
Special Issue Information
Dear Colleagues,
The transition towards sustainable energy systems on the demand side is critical for reducing greenhouse gas emissions and enhancing grid efficiency. This Special Issue, titled "Optimal Operation and Control of Low-Carbon Energy Systems on the Demand Side", explores innovative approaches and technologies used to meet these challenges. Key areas of focus include advanced demand response techniques, smart grid technologies, IoT integration, and energy storage systems. Real-time data and advanced analytics enable dynamic energy management, optimizing consumption patterns and reducing reliance on high-carbon sources. Electric vehicles (EVs) and peer-to-peer (P2P) energy trading further contribute to effective demand-side energy management. Supportive regulatory and policy frameworks are essential for the widespread adoption and optimization of these systems, fostering a more efficient and sustainable energy market.
We are pleased to invite you to contribute one paper to this Special Issue.
This Special Issue will present the latest research and developments in the optimal operation and control of low-carbon energy systems focusing on the demand side. We aim to provide a platform for sharing innovative strategies, technologies, and methodologies that enhance the efficiency, reliability, and sustainability of energy systems while minimizing carbon footprints. We request contributions that address theoretical, computational, and experimental advancements in the following areas:
- Demand Response and Load Management: Advanced demand response techniques, load shifting strategies, and peak load management to optimize energy usage and reduce carbon emissions;
- Smart Grids and IoT Integration: Integration of smart grid technologies and IoT devices for the intelligent monitoring, control, and optimization of energy systems on the demand side;
- Energy Storage Systems: Innovations in battery technologies and virtual energy storage and their roles in stabilizing low-carbon energy systems;
- Renewable Energy Utilization: Effective methods for integrating solar, wind, and other renewable sources into demand-side energy networks to enhance sustainability;
- Energy Efficiency Measures: Development of energy-efficient appliances, smart building energy management systems, and optimization algorithms to reduce overall energy consumption;
- Electric Vehicles (EVs): Impacts of EVs on demand-side energy systems, including smart charging and vehicle-to-grid (V2G) technologies and their potential for carbon reduction.
- Peer-to-Peer (P2P) Energy Trading: Implementation of P2P energy trading platforms, leveraging of blockchain technology, and development of market mechanisms to promote decentralized low-carbon energy exchanges;
- Microgrids and Distributed Energy Resources (DERs): Design, control, and operation of microgrids incorporating DERs to enhance local energy resilience and reduce carbon footprints;
- Regulatory and Policy Frameworks: Analysis of policies, regulations, and incentives that support the deployment and optimization of low-carbon energy systems on the demand side;
- Data Analytics and Machine Learning: Application of big data analytics, machine learning, and artificial intelligence for optimizing the operation and control of low-carbon energy systems.
Prof. Dr. Qingshan Xu
Dr. Yu Huang
Dr. Yuanxing Xia
Dr. Yi Su
Dr. Peipei Yu
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
- smart grids
- energy storage
- renewable energy integration
- energy efficiency
- electric vehicles
- peer-to-peer energy trading
- microgrids
- distributed energy resources
- low-carbon energy policy
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