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Optimizing Power Demand-Side Resources for Grid Security, Energy Efficiency, and Environmental Sustainability

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F3: Power Electronics".

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 4186

Special Issue Editors

School of Electrical and Power Engineering, Hohai University, Nanjing, China
Interests: new energy power system stability analysis and control; power demand side resource transaction analysis and optimization; complex power system elasticity analysis and control; power cyber-physical
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Guest Editor
School of Electrical Engineering, Southwest Minzu University, Chengdu, China
Interests: modeling and control of power electronic systems; protection and control of distribution network

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Guest Editor
School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China
Interests: power electronic power system stability analysis and control; transportation energy Internet; new form of urban power grid optimal operation and control technology; new form of urban power grid fault protection technology; new form of urban power grid fault characteristics analysis; new energy active control to improve power system stability technology

Special Issue Information

Dear Colleagues,

The power system, a critical infrastructure sustaining societal life and economic operations, confronts increasingly formidable challenges in the current global energy landscape. The confluence of burgeoning power demand, antiquated structures within traditional power systems, and an imperative for environmentally sustainable energy underscores the multifaceted pressures on the power industry. Against this backdrop, a nuanced exploration into the modeling, operational optimization, and trading strategies of power demand-side resources emerges as an imperative for fostering the sustainable evolution of power systems.

Primarily, the traditional configuration of power systems grapples with challenges pertaining to grid security, particularly in the face of recurrent extreme weather events and unforeseen emergencies. Strengthening the system's resilience is imperative to ensure steadfast operation across diverse environmental conditions. Subsequently, inefficiencies and suboptimal energy utilization pose significant challenges within the power system, leading to wastage under high or imbalanced loads. The development of optimization models becomes pivotal in enhancing energy efficiency and effecting a more judicious distribution of energy resources. Furthermore, in response to the escalating demand for sustainability, there is a pressing societal need for environmentally friendly and renewable energy sources. The prevalent reliance of traditional power systems on fossil fuels underscores the considerable room for improvement in environmental considerations. Finally, the somewhat rigid trading mechanisms in the power market face challenges in adapting to dynamic shifts in demand. Introducing more adaptive and flexible trading mechanisms designed to incentivize the participation of demand-side resources is a critical imperative.

Consequently, a comprehensive investigation into the modeling, operational optimization, and trading strategies of power demand-side resources assumes paramount practical significance in addressing contemporary power systems' challenges. This research contributes to augmenting the power system's overall efficacy and strategically supports the power industry's trajectory toward a more secure, efficient, and environmentally sustainable future.

This research topic encompasses, but is not confined to, the following domains:

  1. Modeling methodologies for power demand-side resources with a focus on grid security.
  2. Applications of intelligent appliances in enhancing grid security, efficiency, and environmental sustainability.
  3. Development of flexible load optimization models to augment grid security and energy utilization efficiency.
  4. Real-time operational strategies for environmentally conscious applications in power demand-side resources.
  5. Control mechanisms for power demand-side resources ensuring grid security amidst seasonal variations.
  6. Integration strategies for power demand-side resources aligned with renewable energy and environmental sustainability.
  7. Engagement of demand-side response in power market trading mechanisms to enhance energy utilization efficiency.
  8. Utilization of big data and artificial intelligence in optimizing demand-side resources.
  9. Flexibility and environmental consciousness in the application of intelligent control methods within power demand-side operations.
  10. Advancements in energy efficiency and environmental sustainability through pricing and incentive mechanisms on power demand-side.

Dr. Yingjun Wu
Dr. Yao Wang
Prof. Dr. Kai Liao
Guest Editors

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Keywords

  • demand-side resources
  • grid security
  • energy efficiency
  • environmental sustainability

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Published Papers (3 papers)

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Research

19 pages, 1736 KiB  
Article
Multiple-Indicator Filtering-Based Information Interaction Evaluation Method of Automatic Distribution Master Station for Grid Security
by Peng Li, Jinyuan Shi, Ruifeng Zhao, Jiangang Lu, Kailin Wang and Wenxin Guo
Energies 2024, 17(14), 3552; https://doi.org/10.3390/en17143552 - 19 Jul 2024
Viewed by 834
Abstract
Automatic distribution master stations (ADMSs) are software platforms that can be used to monitor energy supply and consumption of power demand-side resources as well as to guarantee grid security. They play a vital role in maintaining the optimal performance and stability of electrical [...] Read more.
Automatic distribution master stations (ADMSs) are software platforms that can be used to monitor energy supply and consumption of power demand-side resources as well as to guarantee grid security. They play a vital role in maintaining the optimal performance and stability of electrical power systems. However, the stability of ADMSs is usually determined by the performance of the information interaction, which includes various challenges and complexities. Therefore, an efficient multiple-indicator filtering-based information interaction evaluation method for the ADMS is proposed in this paper. The proposed method first utilizes the principal component analysis (PCA) to filter the indicators of the ADMS. Then, the data envelopment method and the analytic network process (ANP) are employed to remove the invalid indicators and to determine the indicator weights. In this regard, the secondary screening of the indicators is completed, the effective indicators are obtained, and the accuracy of the evaluation system is improved. Results of the simulation show that the proposed method works well when evaluating information interaction performance, and it offers satisfactory performance evaluation of ADMSs. Full article
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19 pages, 3146 KiB  
Article
Promoting Decarbonization in China: Revealing the Impact of Various Energy Policies on the Power Sector Based on a Coupled Model
by Minwei Liu, Lang Tang, Jincan Zeng, Guori Huang, Xi Liu, Shangheng Yao, Gengsheng He, Nan Shang, Hai Tao, Songyan Ren and Peng Wang
Energies 2024, 17(13), 3234; https://doi.org/10.3390/en17133234 - 1 Jul 2024
Cited by 2 | Viewed by 1411
Abstract
The carbon emissions of the power industry account for over 50% of China’s total carbon emissions, so achieving carbon peak and carbon neutrality in the power sector is crucial. This study aims to simulate the impacts of three energy policies—carbon constraints, the development [...] Read more.
The carbon emissions of the power industry account for over 50% of China’s total carbon emissions, so achieving carbon peak and carbon neutrality in the power sector is crucial. This study aims to simulate the impacts of three energy policies—carbon constraints, the development of a high proportion of renewable energy, and carbon trading—on China’s energy transition, economic development, and the power sector’s energy mix. Through the construction of a dynamic computable general equilibrium (CGE) model for China and its integration with the SWITCH-China electricity model, the impact of diverse energy policies on China’s energy transition, economic progress, and the power mix within the electricity industry has been simulated. The integration of the SWITCH-China model can address the limitations of the CGE model in providing a detailed understanding of the specific intricacies of the electricity sector. The results indicate that increasing the stringency of carbon restrictions compels a reduction in fossil energy use, controlling the output of coal-fired power units, and thereby reducing carbon emissions. The development of a high proportion of renewable energy enhances the cleanliness of the power sector’s generation structure, further promoting the national energy transition. Implementing a carbon trading policy, where the entire industry shares the burden of carbon reduction costs, can effectively mitigate the economic losses of the power sector. Finally, the policies to further enhance the implementation of carbon trading policies, strengthen effective governmental regulation, and escalate the deployment of renewable energy sources are recommended. Full article
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23 pages, 1789 KiB  
Article
Active Planning for Virtual Microgrids with Demand-Side and Distributed Energy Resources
by Lechuan Piao, Fei Xue, Shaofeng Lu, Lin Jiang, Bing Han and Xu Xu
Energies 2024, 17(10), 2391; https://doi.org/10.3390/en17102391 - 16 May 2024
Viewed by 1413
Abstract
In this paper, the notion of a cohesive and self-sufficient grid is proposed. Based on a cohesive and self-sufficient virtual microgrid, an active distribution network is optimally planned, and an optimal configuration of demand-side resources, distributed generations, and energy storage systems are generated. [...] Read more.
In this paper, the notion of a cohesive and self-sufficient grid is proposed. Based on a cohesive and self-sufficient virtual microgrid, an active distribution network is optimally planned, and an optimal configuration of demand-side resources, distributed generations, and energy storage systems are generated. To cope with stochastic uncertainty from forecast error in wind speed and load, flexibility reserves are needed. In this paper, the supply relation between flexibility and uncertainty is quantified and integrated in an innovative index which is defined as cohesion. The optimization objectives are a minimized operational cost and system net-ability cohesion as well as self-sufficiency, which is defined as the abilities both to supply local load and to deal with potential uncertainty. After testing the optimal configuration in the PG&E 69 bus system, it is found that with a more cohesive VM partition, the self-sufficiency of VMs is also increased. Also, a case study on uncertainty-caused system imbalance is carried out to show how flexibility resources are utilized in real-time operational balance. Full article
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