Special Issues

Low-Carbon Situational Awareness and Dispatch Decision of New-Type Power System Operation

Submission Deadline: 31 December 2025 View: 432 Submit to Special Issue

Guest Editors

Prof. Dr. Xiaoshun Zhang

Email: zhangxiaoshun@mail.neu.edu.cn

Affiliation: Foshan Graduate School of Innovation, Northeastern University, Foshan, 528311, China

Homepage:

Research Interests: low-carbon power system operation, artificial intelligence for energy system

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Dr. Xiang Gao

Email: gaoxiang@szpu.edu.cn

Affiliation: Industrial Training Center, Shenzhen Polytechnic University, Shenzhen, 518000, China

Homepage:

Research Interests: electricity market bidding strategies, game theory, multi-agent reinforcement learning

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Dr. Junbin Chen

Email: junbinchen@stu.edu.cn

Affiliation: College of Engineering, Shantou University, 243 Daxue Road, Jinping District, Shantou City, Guangdong Province, Shantou, 515063, China

Homepage:

Research Interests: optimization of power system operation, artificial intelligence (AI), hybrid augmented intelligence (HAI)

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Summary

In 2018, the Intergovernmental Panel on Climate Change (IPCC) released a special report on global warming of 1.5C, highlighting the urgent need for sustainable development. The report emphasized that limiting temperature rise to 1.5C is achievable if global net anthropogenic CO emissions are cut by approximately 45% by 2030 compared to 2010 levels, followed by achieving net-zero emissions around 2050. Facing this critical challenge, numerous nations have pledged to attain carbon neutrality by mid-century. For instance, the European Union aims to achieve this goal by 2050, while China has committed to doing so before 2060. Given their status as the largest sources of emissions, energy-related sectorsparticularly the power industrywill be pivotal in driving the transition toward carbon neutrality.


This Special Issue aims to highlight the state-of-art techniques for low-carbon situational awareness and dispatch decision of new-type power system operation.


Topics of interest of this Special Issue include, but are not limited to:
1. Electric carbon emission measurement, monitoring, and prediction;
2. Carbon reduction potential assessment and decision aid of flexible loads;
3. Coordination strategies of source-net-load-storage resources;
4. Low-carbon dispatch and control of new-type power system;
5. Energy saving and carbon emission reduction of advanced generation techniques;
6. Low-carbon situational awareness of power grid and micro-grid;
7. Integrated carbon and electricity trading market and strategy;
8. New device and policy for electricity carbon emission;
9. Zero-carbon techniques for industrial, science and technology parks.


Keywords

new-type power system, low-carbon operation, zero-carbon, situational awareness, dispatch decision

Published Papers


  • Open Access

    ARTICLE

    Robust Load Frequency Control in Hybrid Power Systems Using QOSCA-Tuned PID with EV Loads

    Pralay Roy, Pabitra Kumar Biswas, Chiranjit Sain, Taha Selim Ustun
    Energy Engineering, Vol.122, No.10, pp. 4035-4060, 2025, DOI:10.32604/ee.2025.068989
    (This article belongs to the Special Issue: Low-Carbon Situational Awareness and Dispatch Decision of New-Type Power System Operation)
    Abstract This study presents the use of an innovative population-based algorithm called the Sine Cosine Algorithm and its metaheuristic form, Quasi Oppositional Sine Cosine Algorithm, to automatic generation control of a multiple-source-based interconnected power system that consists of thermal, gas, and hydro power plants. The Proportional-Integral-Derivative controller, which is utilized for automated generation control in an interconnected hybrid power system with a DC link connecting two regions, has been tuned using the proposed optimization technique. An Electric Vehicle is taken into consideration only as an electrical load. The Quasi Oppositional Sine Cosine method’s performance and efficacy… More >

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