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Energies
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Advanced Techniques for Optimization and Energy Management in Smart Grids
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Advanced Techniques for Optimization and Energy Management in Smart Grids

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: 5 December 2025 | Viewed by 1049

Special Issue Editor

Dr. Hualiang Fang

E-Mail Website
Guest Editor
School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Interests: plug-in electric vehicles; vehicle-to-grid technology; charging

Special Issue Information

Dear Colleagues,

We invite submissions to a Special Issue of Energies centered around the advanced approaches, theoretical models, market models, AI applications, and novel techniques used for the operation and control of smart grids. This power system should be renovated to fulfill social and industrial requests and economic advances. Hence, providing economic, reliable, green, low-carbon, and sustainable energy is a key goal of advanced societies. In order to meet these goals, recent features of smart grid technologies need to have the ability to improve reliability, flexibility, efficiency, and resilience. This Special Issue aims to encourage researchers to address the mentioned challenges.

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

  • The structural system and design concept of smart grids;
  • System reliability, sustainability, flexibility, and resilience;
  • The modeling, planning, and operation of renewable energy resources;
  • Multi-energy complementation;
  • Low-carbon operation and schedule;
  • The intelligent management of EV charging;
  • Smart power consumption, demand side management, and demand response;
  • AI methodologies and applications for the operation and control of smart grids;
  • Business models for different electricity market players;
  • The sizing, placement, and operation of energy storage systems;
  • Smart homes and building energy management;
  • Electricity market, electrical power, and energy systems;
  • The forecasting and schedule of uncertainty in smart grids;
  • Microgrids and microgrid groups. 

Dr. Hualiang Fang
Guest Editor

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

  • reliability
  • flexibility
  • resiliency
  • schedule
  • AI
  • multi-energy complementation
  • low carbon
  • energy storage
  • electricity market

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Related Special Issue

Published Papers (2 papers)

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Research

23 pages, 2784 KiB  
Article
Allocation of Cost of Reliability to Various Customer Sectors in a Standalone Microgrid System
by Sakthivelnathan Nallainathan, Ali Arefi, Christopher Lund and Ali Mehrizi-Sani
Energies 2025, 18(13), 3237; https://doi.org/10.3390/en18133237 - 20 Jun 2025
Viewed by 293
Abstract
Due to the intermittent and uncertain nature of emerging renewable energy sources in the modern power grid, the level of dispatchable power sources has been reduced. The contemporary power system is attempting to address this by investing in energy storage within the context [...] Read more.
Due to the intermittent and uncertain nature of emerging renewable energy sources in the modern power grid, the level of dispatchable power sources has been reduced. The contemporary power system is attempting to address this by investing in energy storage within the context of standalone microgrids (SMGs), which can operate in an island mode and off-grid. While renewable-rich SMGs can facilitate a higher level of renewable energy penetration, they also have more reliability issues compared to conventional power systems due to the intermittency of renewables. When an SMG system needs to be upgraded for reliability improvement, the cost of that reliability improvement should be divided among diverse customer sectors. In this research, we present four distinct approaches along with comprehensive simulation outcomes to address the problem of allocating reliability costs. The central issue in this study revolves around determining whether all consumers should bear an equal share of the reliability improvement costs or if these expenses should be distributed among them differently. When an SMG system requires an upgrade to enhance its reliability, it becomes imperative to allocate the associated costs among various customer sectors as equitably as possible. In our investigation, we model an SMG through a simulation experiment, involving nine distinct customer sectors, and utilize their hourly demand profiles for an entire year. We explore how to distribute the total investment cost of reliability improvement to each customer sector using four distinct methods. The first two methods consider the annual and seasonal peak demands in each industry. The third approach involves an analysis of Loss of Load (LOL) events and determining the hourly load requirements for each sector during these events. In the fourth approach, we employ the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) technique. The annual peak demand approach resulted in the educational sector bearing the highest proportion of the reliability improvement cost, accounting for 21.90% of the total burden. Similarly, the seasonal peak demand approach identified the educational sector as the most significant contributor, though with a reduced share of 15.44%. The normalized average demand during Loss of Load (LOL) events also indicated the same sector as the highest contributor, with 12.34% of the total cost. Lastly, the TOPSIS-based approach assigned a 15.24% reliability cost burden to the educational sector. Although all four approaches consistently identify the educational sector as the most critical in terms of its impact on system reliability, they yield different cost allocations due to variations in the methodology and weighting of demand characteristics. The underlying reasons for these differences, along with the practical implications and applicability of each method, are comprehensively discussed in this research paper. Based on our case study findings, we conclude that the education sector, which contributes more to LOL events, should bear the highest amount of the Cost of Reliability Improvement (CRI), while the hotel and catering sector’s share should be the lowest percentage. This highlights the necessity for varying reliability improvement costs for different consumer sectors. Full article
(This article belongs to the Special Issue Advanced Techniques for Optimization and Energy Management in Smart Grids)
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21 pages, 1302 KiB  
Article
Bounding Case Requirements for Power Grid Protection Against High-Altitude Electromagnetic Pulses
by Connor A. Lehman, Rush D. Robinett III, Wayne W. Weaver and David G. Wilson
Energies 2025, 18(10), 2614; https://doi.org/10.3390/en18102614 - 19 May 2025
Viewed by 372
Abstract
Securing the power grid is of extreme concern to many nations as power infrastructure has become integral to modern life and society. A high-altitude electromagnetic pulse (HEMP) is generated by a nuclear detonation high in the atmosphere, producing a powerful electromagnetic field that [...] Read more.
Securing the power grid is of extreme concern to many nations as power infrastructure has become integral to modern life and society. A high-altitude electromagnetic pulse (HEMP) is generated by a nuclear detonation high in the atmosphere, producing a powerful electromagnetic field that can damage or destroy electronic devices over a wide area. Protecting against HEMP attacks (insults) requires knowledge of the problem’s bounds before the problem can be appropriately solved. This paper presents a collection of analyses to determine the basic requirements for controller placements on a power grid. Two primary analyses are conducted. The first is an inverted controllability analysis in which the HEMP event is treated as an unbounded control input to the system. Considering the HEMP insult as a controller, we can break down controllability to reduce its influence on the system. The analysis indicates that either all but one neutral path to ground must be protected or that all transmission lines should be secured. However, further exploration of the controllability definition suggests that fewer blocking devices are sufficient for effective HEMP mitigation. The second analysis involves observability to identify the minimum number of sensors needed for full-state feedback. The results show that only one state sensor is required to achieve full-state feedback for the system. These requirements suggest that there is room to optimize controller design and placement to minimize total controller count on a power grid to ensure HEMP mitigation. As an example, the Horton et al. system model with 15 transformers and 15 transmission lines is used to provide a baseline comparison for future optimization studies by running all permutations of neutral and transmission line blocking cases. The minimum number of neutral controllers is 8, which is approximately half of the bounding solution of 14. The minimum number of transmission line controllers is 3, which is one-fifth of the bounding solution of 15 and less than half of the required neutral controllers. Full article
(This article belongs to the Special Issue Advanced Techniques for Optimization and Energy Management in Smart Grids)
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