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Power Interaction Control Methods among Main Grid, Charging Station and...
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Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 10513

Special Issue Editors

Prof. Dr. Qiuye Sun

E-Mail Website
Guest Editor
School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Interests: energy Internet; dynamic stability analysis; distributed control; new energy grid-connected operation control; artificial intelligence in energy systems; multi-type energy conversion devices
Dr. Rui Wang

E-Mail Website
Guest Editor
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Interests: electric vehicles; stability analysis; distributed control; solar energy consumption; power system
Special Issues, Collections and Topics in MDPI journals
Dr. Zhengmao Li

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: optimal planning and operation of multi-energy systems; resilience in multi-energy systems; uncertainties handling in multi-energy systems; stochastic/robust optimization; multi-energy ship; optimization methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Energy and the environment are important guarantees for the development of the world economy, but the fossil energy crisis and environmental pollution problems such as haze are becoming more and more serious. These are concerns for various countries and governments, while the rapid increase of car ownership leads to increased energy consumption and further environmental pollution problems. New energy vehicles represented by electric vehicles, on the other hand, are one way to effectively address environmental pollution and fossil energy consumption. However, the biggest obstacle to the development of electric vehicles is the series of problems caused by their batteries. Therefore, the charging method of electric vehicles is becoming an increasingly hot topic, and there are still many challenges and difficulties in the field of electric vehicles that need to be further researched and overcome. This research project will bring together researchers from different fields and specialties, such as electrical engineering, energy power, control engineering, traffic engineering, etc., to help address these important issue.

Topics of interest include, but are not limited to, the following:

  • Charging methods of electric vehicles
  • Vehicle–station–grid interaction control for electric vehicles
  • The power interaction control between the main grid and electric vehicles
  • The power interaction between the grid and vehicle stations
  • The power interaction between the vehicle station and electric vehicles
  • The power interaction between electric vehicles

Prof. Dr. Qiuye Sun
Dr. Rui Wang
Dr. Zhengmao Li
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. Processes is an international peer-reviewed open access monthly 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 2400 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

  • electric vehicles
  • charging method
  • power interaction control
  • distributed generators
  • vehicle–station–grid interaction
  • mutual energy exchange

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Published Papers (7 papers)

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Research

17 pages, 1433 KiB  
Article
Information Gap Decision Theory-Based Robust Economic Dispatch Strategy Considering the Uncertainty of Electric Vehicles
by Yongqing Guo, Junhui Yu, Yan Yang and Hengrui Ma
Processes 2024, 12(7), 1397; https://doi.org/10.3390/pr12071397 - 4 Jul 2024
Viewed by 663
Abstract
With the development of renewable energy power systems, electric vehicles, as an important carrier of green transportation, are gradually having an impact on the power grid load curve due to their charging behavior. However, the significant influx of electric vehicles (EVs) and distributed [...] Read more.
With the development of renewable energy power systems, electric vehicles, as an important carrier of green transportation, are gradually having an impact on the power grid load curve due to their charging behavior. However, the significant influx of electric vehicles (EVs) and distributed power sources has led to multiple uncertainties, increasing the difficulty in making grid scheduling decisions. Traditional robust scheduling strategies tend to be overly conservative, resulting in poor economic performance. Therefore, this paper proposes a robust and economic dispatch strategy for park power grids based on the information gap decision theory (IGDT). Firstly, based on the probabilistic characteristics of the spatial and temporal distribution of EVs charging, the Monte Carlo method is used to generate typical electricity usage scenarios for EVs. Simultaneously, an economic dispatch model for the park power grid is established with the objective of minimizing operating costs. Taking into account the uncertainty of renewable energy output, simulation analysis is conducted through the IGDT model. Finally, through the verification of the improved IEEE-33 node test system and comparison with other methods, the proposed approach in this paper can reduce decision conservatism and effectively reconcile the contradiction. Through analysis, the proposed method in this paper can reduce the total operational cost of the system by up to 3.2%, with a computational efficiency of only 8.9% of the traditional stochastic optimization time. Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
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15 pages, 2290 KiB  
Article
Low-Carbon Economic Dispatch of Electricity and Cooling Energy System
by Yubo Wang, Ling Hao, Libin Zheng, Lei Chen, Fei Xu, Qun Chen and Yong Min
Processes 2023, 11(9), 2787; https://doi.org/10.3390/pr11092787 - 18 Sep 2023
Cited by 1 | Viewed by 1007
Abstract
In response to the issue of the hydropower consumption of run-of-river hydropower stations in Southwest China, the district cooling system can provide regulation capacity for hydropower utilization and suppress fluctuations caused by the uncertainty of hydropower. The innovative method is to utilize the [...] Read more.
In response to the issue of the hydropower consumption of run-of-river hydropower stations in Southwest China, the district cooling system can provide regulation capacity for hydropower utilization and suppress fluctuations caused by the uncertainty of hydropower. The innovative method is to utilize the thermal characteristics of pipelines and buildings, as well as the thermal comfort elasticity to shift the cooling and electricity loads, which helps to consume the surplus hydroelectric power generation. Taking the minimum total cost of coal consumption in thermal power units, hydropower abandonment penalty, and the carbon trading cost as the objective function, models were established for power supply balance constraints, heat transport constraints, and unit output constraints. The hybrid integer linear programming algorithm was used to achieve the low-carbon economic dispatch of the electric-cooling system. The calculation examples indicate that compared to the traditional real-time balance of cooling supply, the comprehensive consideration of thermal characteristics in a cooling system and flexible thermal comfort have a better operational performance. The carbon trading cost, coal consumption cost, and abandoned hydropower rate of a typical day was reduced by 4.25% (approximately CNY 7.55 × 104), 4.47% (approximately CNY 22.23 × 104), and 3.66%, respectively. Therefore, the electric-cooling dispatch model considering the thermal characteristics in cooling networks, building thermal inertia, and thermal comfort elasticity is more conducive to the hydropower utilization of run-of-river stations. Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
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13 pages, 824 KiB  
Article
NN-Based Parallel Model Predictive Control for a Quadrotor UAV
by Jun Qi, Jiru Chu, Zhao Xu, Cong Huang and Minglei Zhu
Processes 2023, 11(6), 1706; https://doi.org/10.3390/pr11061706 - 2 Jun 2023
Viewed by 1603
Abstract
A novel neural network (NN)-based parallel model predictive control (PMPC) method is proposed to deal with the tracking problem of the quadrotor unmanned aerial vehicles (Q-UAVs) system in this article. It is well known that the dynamics of Q-UAVs are changeable while the [...] Read more.
A novel neural network (NN)-based parallel model predictive control (PMPC) method is proposed to deal with the tracking problem of the quadrotor unmanned aerial vehicles (Q-UAVs) system in this article. It is well known that the dynamics of Q-UAVs are changeable while the system is operating in some specific environments. In this case, traditional NN-based MPC methods are not applicable because their model networks are pre-trained and kept constant throughout the process. To solve this problem, we propose the PMPC algorithm, which introduces parallel control structure and experience pool replay technology into the MPC method. In this algorithm, an NN-based artificial system runs in parallel with the UAV system to reconstruct its dynamics model. Furthermore, the experience replay technology is used to maintain the accuracy of the reconstructed model, so as to ensure the effectiveness of the model prediction algorithm. Furthermore, a convergence proof of the artificial system is also given in this paper. Finally, numerical results and analysis are given to demonstrate the effectiveness of the PMPC algorithm. Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
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25 pages, 5244 KiB  
Article
Low-Carbon Optimal Scheduling Model for Peak Shaving Resources in Multi-Energy Power Systems Considering Large-Scale Access for Electric Vehicles
by Kang Dai, Kun Zhang, Jicheng Li, Liang Liu, Zhe Chen and Peng Sun
Processes 2023, 11(5), 1532; https://doi.org/10.3390/pr11051532 - 17 May 2023
Cited by 2 | Viewed by 1222
Abstract
Aiming at the synergy between a system’s carbon emission reduction demand and the economy of peak shaving operation in the process of optimizing the flexible resource peaking unit portfolio of a multi-energy power system containing large-scale electric vehicles, this paper proposes a low-carbon [...] Read more.
Aiming at the synergy between a system’s carbon emission reduction demand and the economy of peak shaving operation in the process of optimizing the flexible resource peaking unit portfolio of a multi-energy power system containing large-scale electric vehicles, this paper proposes a low-carbon optimal scheduling model for peak shaving resources in multi-energy power systems considering large-scale access for electric vehicles. Firstly, the charging and discharging characteristics of electric vehicles were studied, and a comprehensive cost model for electric vehicles, heat storage, and hydrogen storage was established. At the same time, the carbon emission characteristics of multi-energy power systems and their emission cost models under specific carbon trading mechanisms were established. Secondly, the change characteristics of the system’s carbon emissions were studied, and a carbon emission cost model of multi-energy power was established considering the carbon emission reduction demand of the system. Then, taking the carbon emission of the system and the peak regulating operation costs of traditional units, energy storage, and new energy unit as optimization objectives, the multi-energy power system peak regulation multi-objective optimization scheduling model was established, and NSGA-II was used to solve the scheduling model. Finally, based on a regional power grid data in Northeast China, the improved IEEE 30 node multi-energy power system peak shaving simulation model was built, and the simulation analysis verified the feasibility of the optimal scheduling model proposed in this paper. Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
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19 pages, 2418 KiB  
Article
A Dynamic Partition Model for Multi-Energy Power Grid Energy Balance Considering Electric Vehicle Response Willingness
by Shi Qiu, Kun Zhang, Zhuo Chen, Yiling Ma and Zhe Chen
Processes 2023, 11(5), 1508; https://doi.org/10.3390/pr11051508 - 15 May 2023
Cited by 2 | Viewed by 1322
Abstract
In multi-energy power grids in which electric vehicles (EVs) participate in response, there are significant differences in the power balance between multi-energy supply and load at different time scales and spatial scales. To optimize the energy balance demand of each region, this paper [...] Read more.
In multi-energy power grids in which electric vehicles (EVs) participate in response, there are significant differences in the power balance between multi-energy supply and load at different time scales and spatial scales. To optimize the energy balance demand of each region, this paper proposes a dynamic partition coordination model for power grid energy regulation demand that considers the willingness of electric vehicles to respond and the uncertainties related to sources, loads, and storage. Firstly, the charging and discharging characteristics of multi-energy conversion devices in power grids, as well as the response uncertainties of these devices, are studied, and a source, load, and storage uncertainty model is established. Then, based on the Markov random field theory and the energy prior model, the dynamic partition model and its solution algorithm for the multi-energy power grid are proposed. Finally, a simulation system is established based on the actual operating data of a multi-energy power grid, and the proposed method is simulated and analyzed. The results indicate that the energy balance partition optimization method proposed in this article is effective. The application of the method proposed in this article can fully leverage the regulatory potential of energy conversion equipment, effectively reduce the proportion of traditional energy supply and peak shaving capacity, and improve the utilization rate of renewable energy. Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
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17 pages, 3047 KiB  
Article
Trading Portfolio Strategy Optimization via Mean-Variance Model Considering Multiple Energy Derivatives
by Shaoshan Xu, Jun Shen, Haochen Hua, Fangshu Li, Kun Yu, Zhenxing Li, Xinqiang Gao and Xueqiang Dong
Processes 2023, 11(2), 532; https://doi.org/10.3390/pr11020532 - 9 Feb 2023
Cited by 4 | Viewed by 1876
Abstract
Energy retailers that sell energy at fixed prices are at risk of bankruptcy due to instantaneous fluctuations in wholesale electricity prices. Energy derivatives, e.g., electricity options, can be purchased by energy retailers then sold to customers as one potential risk-mitigation tool. A class [...] Read more.
Energy retailers that sell energy at fixed prices are at risk of bankruptcy due to instantaneous fluctuations in wholesale electricity prices. Energy derivatives, e.g., electricity options, can be purchased by energy retailers then sold to customers as one potential risk-mitigation tool. A class of energy retailers that trade energy derivatives, including the electricity option, the carbon option and the green certificate, is considered in this paper. In terms of energy retailers, a strategy that can maximize the value of the purchased energy derivatives over a period of time and minimize the risk due to the stochastic price fluctuations is developed. Firstly, the dynamic prices of the electricity option as well as the carbon option are described by stochastic differential equations, and the dynamic prices of the green certificate are described by ordinary differential equations. Historical price data are used to obtain the parameters of both stochastic and ordinary differential equations by maximum likelihood estimation. Next, an investment portfolio is established as a mean-variance portfolio selection problem where the retailer maintains the satisfactory asset value and minimizes the risk simultaneously. Then, the problem is transformed into a stochastic optimal control problem which can be solved analytically by using the linear-quadratic method. Finally, the numerical simulations illustrate the feasibility of the proposed method. Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
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11 pages, 3427 KiB  
Article
Research on 3D Path Planning of Quadrotor Based on Improved A* Algorithm
by Wei Zheng, Kaipeng Huang, Chenyang Wang, Yang Liu, Zhiwu Ke, Qianyu Shen and Zhiqiang Qiu
Processes 2023, 11(2), 334; https://doi.org/10.3390/pr11020334 - 19 Jan 2023
Cited by 1 | Viewed by 1840
Abstract
Considering the complexity of the three-dimensional environment and the flexibility of the quadrotor aircraft, using the traditional A* algorithm for global path planning has the disadvantages of less search direction, more expanded nodes, and a longer planning path. Therefore, an improved A* algorithm [...] Read more.
Considering the complexity of the three-dimensional environment and the flexibility of the quadrotor aircraft, using the traditional A* algorithm for global path planning has the disadvantages of less search direction, more expanded nodes, and a longer planning path. Therefore, an improved A* algorithm is proposed, which is improved from two aspects. Firstly, a two-layer extended neighborhood strategy is proposed, which can increase the search direction and make better use of the flexibility of the aircraft. Secondly, the heuristic function is improved to make the heuristic function value closer to the actual planning path distance, which can reduce the expansion nodes and optimize the planning path. Finally, the path planning simulation of the improved A* algorithm is carried out and the results show that the path planned by the improved algorithm is shorter and the expanded nodes are fewer, which can guide the quadrotor to reach the destination better. Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
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