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Advances in Research and Practice of Smart Electric Power Systems
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Advances in Research and Practice of Smart Electric Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 3875

Special Issue Editors

Prof. Dr. Don Hur

E-Mail Website1 Website2
Guest Editor
Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Republic of Korea
Interests: smart/intelligent systems for sustainable energy economy; energy economics and policy; electricity markets; energy security; energy management; energy efficiency; techno-economic analysis for energy projects
Dr. Minhan Yoon

E-Mail Website
Guest Editor
Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Republic of Korea
Interests: inverter based resources; distributed energy resources; DC power system; AI application; intelligent control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are very delighted to announce this call for paper for a Special Issue in the journal Energies (IF 3.2).

With the increasing power demand and the energy transition to a sustainable and decarbonized society, research activities and the adoption of smart electric power systems have been  brought to the fore.

The aim of this Special Issue, Advances in Research and Practice of Smart Electric Power Systems, is to publish studies that reveal a wide range of real-world applications of hardware and software technologies in complex and data-driven power systems with distributed energy resources. The Special Issue aims to foster an extensive exchange of insights between the fields of energy production, transportation, end-uses and utilization for pollution reduction and energy savings, thereby targeting the development of carbon-neutral energy systems and a green energy economy. Original research papers as well as review articles dealing with the most recent developments and innovations for the implementation of robust and flexible power and energy networks would also be welcome.

Specific topics of interest include, but are not restricted to, the following:

  • Computing and communication technologies for smart grids;
  • Hardware and software approaches for smart/intelligent power systems;
  • Power grid planning and operations techniques for flexibility and resilience;
  • Energy efficiency improvement facilities for sustainable energy development;
  • Digital technology applications and services in energy sector.

Prof. Dr. Don Hur
Dr. Minhan Yoon
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

  • computing and communication technologies for smart grids
  • hardware and software approaches for smart/intelligent power systems
  • decentralized energy systems
  • power grid planning and operations techniques for flexibility and resilience
  • automation
  • renewable energy sources
  • energy storage
  • energy management
  • energy efficiency
  • big data analytics applied in power systems
  • application of machine learning and artificial intelligence in power IoT
  • digital technology applications and services in energy sector

Published Papers (5 papers)

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Research

14 pages, 1742 KiB  
Article
Online Optimization of Vehicle-to-Grid Scheduling to Mitigate Battery Aging
by Qingguang Zhang, Mubasher Ikram and Kun Xu
Energies 2024, 17(7), 1681; https://doi.org/10.3390/en17071681 - 1 Apr 2024
Viewed by 597
Abstract
The penetration of electric vehicles (EVs) in vehicle-to-grid (V2G) interaction can effectively assist the grid in achieving frequency regulation and peak load balancing. However, the customer perceives that participating in V2G services would result in the additional cycling of the battery and the [...] Read more.
The penetration of electric vehicles (EVs) in vehicle-to-grid (V2G) interaction can effectively assist the grid in achieving frequency regulation and peak load balancing. However, the customer perceives that participating in V2G services would result in the additional cycling of the battery and the accelerated aging of the EVs’ power battery, which has become a major obstacle to the widespread adoption of V2G services. Most existing methods require long-term cycling data and battery parameters to quantify battery aging, which is not suitable for the V2G scenario with large-scale and short-time intervals. Consequently, the real-time and accurate quantification of battery aging for optimization remains a challenge. This study proposes a charging scheduling method for EVs that can accurately and online quantify battery aging. Firstly, V2G scheduling is formulated as an optimization problem by defining an online sliding window to collect real-time vehicle information on the grid, enabling online optimization. Secondly, battery aging is more accurately quantified by proposing a novel amplitude-based rain-flow cycle counting (MRCC) method, which utilizes the charging information of the battery within a shorter time period. Lastly, an intelligent optimization algorithm is employed to optimize the charging and discharging power of EVs, aiming to minimize grid fluctuations and battery aging. The proposed method is validated using a V2G scenario with 50 EVs with randomly generated behaviors, and the results demonstrate that the proposed online scheduling method not only reduces the EFCC of the battery by 8.4%, but also achieves results close to global optimization. Full article
(This article belongs to the Special Issue Advances in Research and Practice of Smart Electric Power Systems)
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21 pages, 4189 KiB  
Article
Integrated Active and Reactive Power Control Methods for Distributed Energy Resources in Distribution Systems for Enhancing Hosting Capacity
by Phi-Hai Trinh and Il-Yop Chung
Energies 2024, 17(7), 1642; https://doi.org/10.3390/en17071642 - 29 Mar 2024
Viewed by 546
Abstract
Recently, there has been a significant increase in the integration of distributed energy resources (DERs) such as small-scale photovoltaic systems and wind turbines in power distribution systems. When the aggregated outputs of DERs are combined, excessive reverse current may occur in distribution lines, [...] Read more.
Recently, there has been a significant increase in the integration of distributed energy resources (DERs) such as small-scale photovoltaic systems and wind turbines in power distribution systems. When the aggregated outputs of DERs are combined, excessive reverse current may occur in distribution lines, leading to overvoltage issues and exceeding thermal limits of the distribution lines. To address these issues, it is necessary to limit the output of DERs to a certain level, which results in constraining the hosting capacity of DERs in the distribution system. In this paper, coordination control methodologies of DERs are developed and executed to mitigate the overvoltage and overcurrent induced by DERs, thereby increasing the hosting capacity for DERs of the distribution system. This paper proposes three coordinated approaches of active and reactive power control of DERs, namely Var Precedence, Watt Precedence, and Integrated Watt and Var Control. The Var and Watt Precedence prioritizes reactive power for voltage (Q–V) and active power for current (P–I) to address network congestion, thereby enhancing hosting capacity. Conversely, the Integrated Var and Watt Precedence propose a novel algorithm that combines four control indices (Q–V, P–V, Q–I, and P–I) to solve network problems while maximizing hosting capacity. The three proposed methods are based on the sensitivity analysis of voltage and current to the active and reactive power outputs at the DER installation locations on the distribution lines, aiming to minimize DER active power curtailment. Each sensitivity is derived from linearized power equations at the operating points of the distribution system. To minimize the computation burden of iterative computation, each proposed method decouples active and reactive power and proceeds with sequential control in its own unique way, iteratively determining the precise output control of distributed power sources to reduce linearization errors. The three proposed algorithms are verified via case studies, evaluating their performance compared to conventional approaches. The case studies exhibit superior control effectiveness of the proposed DER power control methods compared to conventional methods when issues such as overvoltage and overcurrent occur simultaneously in the distribution line so that the DER hosting capacity of the system can be improved. Full article
(This article belongs to the Special Issue Advances in Research and Practice of Smart Electric Power Systems)
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20 pages, 5454 KiB  
Article
Optimal Trading Volume of Electricity and Capacity of Energy Storage System for Electric Vehicle Charging Station Integrated with Photovoltaic Generator
by Yong Woo Jeong, Kyung-Chang Lee, Chunghun Kim and Woo Young Choi
Energies 2024, 17(4), 936; https://doi.org/10.3390/en17040936 - 17 Feb 2024
Viewed by 660
Abstract
As penetration of EVs in the transportation sector is increasing, the demand for the mandatory installation of charging infrastructure also is increasing. In addition, renewable energy and energy storage systems (ESSs) are being reviewed for use in electric vehicle charging stations (EVCSs). In [...] Read more.
As penetration of EVs in the transportation sector is increasing, the demand for the mandatory installation of charging infrastructure also is increasing. In addition, renewable energy and energy storage systems (ESSs) are being reviewed for use in electric vehicle charging stations (EVCSs). In this paper, we present an optimal electricity trading volume and an optimal installation capacity of ESSs to maximize the daily profit of the EVCSs equipped with solar power generation when the EVCSs are licensed to sell energy to the power supplier during a specific time period. By formulating and solving the optimization problem of the EVCSs, this paper analyzes validation results for the different useful lives of ESSs, the peak power of a PV generator, and weather conditions at the Yangjae Solar Station and the Suseo Station public parking lot, Seoul, Republic of Korea. Furthermore, this paper validates that the daily expected profit of EVCSs with the proposed method outperforms the profit of conventional EVCSs which do not utilize ESSs. Full article
(This article belongs to the Special Issue Advances in Research and Practice of Smart Electric Power Systems)
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17 pages, 3348 KiB  
Article
Automatic Generation Control Ancillary Service Cost-Allocation Methods Based on Causer-Pays Principle in Electricity Market
by Sunkyo Kim, Pyeong-Ik Hwang and Jaewan Suh
Energies 2024, 17(1), 11; https://doi.org/10.3390/en17010011 - 19 Dec 2023
Cited by 1 | Viewed by 832
Abstract
The electric power system is rapidly transforming to address the urgent need for decarbonization and combat climate change. Integration of renewable energy sources into the power grid is accelerating, creating new challenges such as intermittency and uncertainty. To address these challenges, this paper [...] Read more.
The electric power system is rapidly transforming to address the urgent need for decarbonization and combat climate change. Integration of renewable energy sources into the power grid is accelerating, creating new challenges such as intermittency and uncertainty. To address these challenges, this paper proposes a new design of automatic generation control (AGC) ancillary service cost allocation based on the causer-pays rule. The proposed design treats reserves as inventory and aims to minimize them by allocating costs among consumers based on the causative factors for AGC operation. Two cost-allocation methods based on the causer-pays principle are introduced. The first method distributes costs according to the changes in loads causing ancillary service operation, while the second method considers opportunity costs. The case study on the IEEE 39 Bus System demonstrates that the proposed methods incentivize consumers to minimize volatility, resulting in reduced reserve requirements for system operation. In particular, the opportunity cost-based approach encourages loads and variable renewable energy (VRE) to actively reduce volatility, resulting in more efficient power system operation. In conclusion, the novel AGC ancillary service cost allocation methods offer a promising strategy for minimizing spinning reserves, increasing the power system’s efficiency, and incentivizing consumers to actively participate in frequency regulation for a more sustainable and reliable electricity market. Full article
(This article belongs to the Special Issue Advances in Research and Practice of Smart Electric Power Systems)
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27 pages, 2011 KiB  
Article
A Robust Optimization Model of Aggregated Resources Considering Serving Ratio for Providing Reserve Power in the Joint Electricity Market
by Seong-Hyeon Cha, Sun-Hyeok Kwak and Woong Ko
Energies 2023, 16(20), 7061; https://doi.org/10.3390/en16207061 - 12 Oct 2023
Cited by 1 | Viewed by 725
Abstract
As the share of distributed generation increases, so do the opportunities for aggregators to participate in the electricity market. In particular, aggregators participating in both the day-ahead and real-time markets contribute to improving the reliability of the power system. In addition, aggregators seeking [...] Read more.
As the share of distributed generation increases, so do the opportunities for aggregators to participate in the electricity market. In particular, aggregators participating in both the day-ahead and real-time markets contribute to improving the reliability of the power system. In addition, aggregators seeking additional revenue can benefit from providing reserves in a joint electricity market environment. However, aggregated resources with uncertainty are limited because of the uncertain nature of both reserve provision and the amount of reserves they can provide. Therefore, this study proposes a robust optimization model for an aggregator to formulate a strategy for participation in the day-ahead markets and deploys energy control in the real-time operation. The serving ratio reflects the availability of the aggregator’s reserve participation. Both the deployed up/down power and renewable energy in the real-time operation are considered as uncertain parameters to reflect the uncertainty. In the case study, we analyze the profit-maximization strategy of an aggregator that owns renewable energy resources and energy-storage systems under the variation interval for uncertain parameters and the serving ratio. The bidding strategies vary by the variation interval and the serving ratio. Full article
(This article belongs to the Special Issue Advances in Research and Practice of Smart Electric Power Systems)
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