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Low-Carbon Integrated Energy System with Renewable Generations: Characterization, Modelling, and Optimization

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

Deadline for manuscript submissions: 30 April 2024 | Viewed by 4504

Special Issue Editors


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Guest Editor
Centre for Green Technology, School of Civil and Environmental Engineering, University of Technology, Sydney, NSW 2007, Australia
Interests: internal combustion engines; spray combustion; computational fluid dynamics; vehicle emissions; air quality; renewable energy
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Guest Editor
School of Automation, Chongqing Normal University, Chongqing, China
Interests: distributed optimization; smart grid; nash game

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Guest Editor
Department of Chemical Engineering, Imperial College London, London, UK
Interests: heat and mass transfer; thermodynamics; low carbon technologies and utilization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Refrigeration and Cryogenic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: computational fluid dynamics; numerical simulation; heat transfer; flood modelling; pressure; multiphase flow modeling

Special Issue Information

Dear Colleagues,

The contradiction between economic development and the environment has become a major concern globally. Carbon emission reduction is critical to achieving sustainable economic development. As a major carbon emitter, the carbon-emission problem of the energy system cannot be ignored. The traditional energy system, with deep integrations of advanced information and energy-conversion technologies, has evolved into an integrated energy system in which multiple energy sources interact and respond to each other. It can achieve a complementary and mutually beneficial operation mode, leading to a significant reduction in carbon emissions. Therefore, it is necessary to conduct detailed modeling and optimization research on integrated energy systems with renewable generations.

As the main root of the greenhouse effect, carbon emission is a long-existing and critical problem. Especially in the integrated energy system, carbon emission is coupled temporally and spatially due to the complementarity of multi-energy resources, leading to arduousness in controlling its low-carbon operation. To achieve the environment-friendly operation of the integrated energy system with renewable generations, the key is to analyze the characterization of carbon migration and establish an accurate carbon-matching mechanism, which requires system-level modeling, characterizing, and controlling. This research topic aims to deepen our understanding of characterization and modeling of carbon emission in an integrated energy system by the aid of various optimization methods. Specifically, we focus on system-level modeling, distributed optimization, and industrial-level optimization of integrated energy systems with renewable generations driven by artificial intelligence.

This Special Issue aims to provide a platform for researchers to share their latest studies on low-carbon integrated energy systems, with a special focus on modeling and optimization methods. Specific themes of this Special Issue include but are not limited to:

  • Low-carbon economic dispatch for integrated energy systems with renewable generations.
  • Carbon-tracking and carbon-migration mechanisms for integrated energy systems with renewable generations.
  • Environmental assessment indicators for integrated energy systems with renewable generations.
  • Distributed optimization method for the low-carbon operation of the integrated energy system with renewable generations.
  • Optimization of the integrated energy system based on artificial intelligence with renewable generations.

Dr. Yuhan Huang
Dr. Wenting Lin
Dr. Xuehui Wang
Dr. Jianye Chen
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

  • low carbon
  • integrated energy system
  • electricity–gas coupling
  • distributed optimization

Published Papers (3 papers)

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Research

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18 pages, 3999 KiB  
Article
Deep-Reinforcement-Learning-Based Low-Carbon Economic Dispatch for Community-Integrated Energy System under Multiple Uncertainties
by Mingshan Mo, Xinrui Xiong, Yunlong Wu and Zuyao Yu
Energies 2023, 16(22), 7669; https://doi.org/10.3390/en16227669 - 20 Nov 2023
Viewed by 650
Abstract
A community-integrated energy system under a multiple-uncertainty low-carbon economic dispatch model based on the deep reinforcement learning method is developed to promote electricity low carbonization and complementary utilization of community-integrated energy. A demand response model based on users’ willingness is proposed for the [...] Read more.
A community-integrated energy system under a multiple-uncertainty low-carbon economic dispatch model based on the deep reinforcement learning method is developed to promote electricity low carbonization and complementary utilization of community-integrated energy. A demand response model based on users’ willingness is proposed for the uncertainty of users’ demand response behavior; a training scenario set of a reinforcement learning agent is generated with a Latin hypercube sampling method for the uncertainties of power, load, temperature, and electric vehicle trips. Based on the proposed demand response model, low-carbon economic dispatch of the community-integrated energy system under multiple uncertainties is achieved by training the agent to interact with the environment in the training scenario set and reach convergence after 250 training rounds. The simulation results show that the reinforcement learning agent achieves low-carbon economic dispatch under 5%, 10%, and 15% renewable energy/load fluctuation scenarios, temperature fluctuation scenarios, and uncertain scenarios of the number of trips, time periods, and mileage of electric vehicles, with good generalization performance under uncertain scenarios. Full article
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23 pages, 3104 KiB  
Article
Low-Carbon Economic Optimization of Integrated Energy System Considering Refined Utilization of Hydrogen Energy and Generalized Energy Storage
by Zifa Liu and Chengchen Li
Energies 2023, 16(15), 5700; https://doi.org/10.3390/en16155700 - 30 Jul 2023
Cited by 2 | Viewed by 1156
Abstract
In order to improve the level of new energy consumption in the system and utilize the clean and efficient characteristics of hydrogen energy, an integrated energy system (IES) scheduling model considering refined utilization of hydrogen energy and generalized energy storage is proposed. Firstly, [...] Read more.
In order to improve the level of new energy consumption in the system and utilize the clean and efficient characteristics of hydrogen energy, an integrated energy system (IES) scheduling model considering refined utilization of hydrogen energy and generalized energy storage is proposed. Firstly, the two-stage hydrogen energy utilization model of power-to-gas (P2G) is finely modeled, and the waste heat of the P2G methanation reaction is innovatively coupled with the Kalina cycle to improve the thermoelectric decoupling capability of the combined heat and power (CHP) unit. Secondly, integrated demand response, electric vehicles, and hydrogen-containing multi-source energy storage equipment are used as generalized energy storage resources to cut peaks and fill valleys. Then, on the basis of considering the ladder-type carbon trading mechanism, the IES conventional operation model is constructed with the minimum operating cost of the system as the objective function. Furthermore, considering the source-load uncertainty of IES operation, a multi-energy complementary optimal scheduling model of hydrogen-containing IES based on conditional value-at-risk was established. Through simulation analysis, it can be seen that the proposed model takes into account both economic and environmental benefits and improves the system’s ability to “peak cutting and valley filling” and measure risk levels. Full article
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Review

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23 pages, 542 KiB  
Review
Nuclear-Driven Integrated Energy Systems: A State-of-the-Art Review
by Athanasios Ioannis Arvanitidis, Vivek Agarwal and Miltiadis Alamaniotis
Energies 2023, 16(11), 4293; https://doi.org/10.3390/en16114293 - 24 May 2023
Cited by 2 | Viewed by 1929
Abstract
Because of the growing concerns regarding climate change and energy sustainability, a transition toward a modern energy sector that reduces environmental effects while promoting social and economic growth has gained traction in recent years. Sustainable energy solutions, which include renewable and low-carbon sources [...] Read more.
Because of the growing concerns regarding climate change and energy sustainability, a transition toward a modern energy sector that reduces environmental effects while promoting social and economic growth has gained traction in recent years. Sustainable energy solutions, which include renewable and low-carbon sources such as nuclear energy and natural gas, could minimize emissions of greenhouse gases, enhance air and water quality, and encourage energy independence. Yet, the shift to a sustainable energy industry is fraught with difficulties, including governmental and regulatory obstacles, technological and economic limits, and societal acceptability hurdles. Addressing these issues would necessitate the development of long-term, durable, and cost-effective energy systems containing nuclear energy and associated with the generation of both electricity and other by-products required by industry. Integrated energy systems (IES) are a novel way to maximize the use of various energy resources and technologies in order to deliver dependable, efficient, and sustainable energy services. IES entail the integration of various energy systems, such as electricity, heating, cooling, and transportation, in respect to energy sustainability and a system’s resilience and flexibility. Their development and implementation require the cooperation of several parties, including energy providers and policymakers. This study provides a state-of-the-art literature review of the most creative nuclear-driven hybrid energy system applications and methodologies, from which the research challenges and prospects for effective IES implementation emerge. Full article
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