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Optimization Methods for Electricity Market and Smart Grid
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Optimization Methods for Electricity Market and Smart Grid

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

Deadline for manuscript submissions: 30 July 2026 | Viewed by 1808

Special Issue Editor

Prof. Dr. Tao Ding

E-Mail Website
Guest Editor
School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710079, China
Interests: power system economics; power system optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is increasingly difficult to imagine a modern power system without the integration of renewable energy sources such as wind, solar, and other forms of clean energy. The utilization of these resources has expanded beyond traditional sectors into newer applications, including electric vehicles, smart grids, microgrids, and energy storage systems. This expansion has led to significant advancements in the technologies, integration methodologies, forecasting models, and power system management techniques used to accommodate renewable energy, which can usually be characterized by its intermittent and fluctuating nature.

However, the growing integration of renewable energy into power systems presents certain challenges, such as ensuring system stability, electricity quality, and efficient energy utilization. To address these challenges, extensive research has been devoted to energy storage solutions, flexible operations, advanced forecasting, and demand-side management. Moreover, with the increasing complexity of integrating renewable energy sources, there has also been a drive for the development of advanced technologies that enable the real-time monitoring, optimization, and control of power systems.

This Special Issue aims to present and disseminate the most recent advances in the integration of renewable energy into power systems, with a focus on enabling the efficient accommodation, storage, and distribution of clean energy.

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

  • Energy storage technologies for renewable energy integration
  • System flexibility and optimization for high renewable penetration
  • Demand-side management and virtual power plants
  • Advanced forecasting methods for renewable energy
  • Microgrids and distributed energy resources
  • Integration of HVDC and FACTS in renewable energy systems
  • Multi-energy systems and hybrid energy systems
  • Smart grid and cyber–physical systems for renewable integration
  • Energy management and control systems
  • Renewable-friendly power system expansion planning
  • Power system stability and reliability for renewable integration
  • Policy, regulatory, and market mechanisms for renewable energy integration

We look forward to receiving your valuable contributions to this exciting and important area of research.

Prof. Dr. Tao Ding
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 250 words) can be sent to the Editorial Office for assessment.

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

  • power markets
  • optimization methods
  • power system economics
  • power system dispatch
  • power system operation

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Published Papers (3 papers)

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Research

23 pages, 3830 KB  
Article
Comparative Lifecycle Economic Assessment of Shared Energy Storage Under Multi-Service Revenue Scenarios
by Yang Liu, Qishan Xu, Feng Zhang, Weijun Teng and Jinggang Wang
Energies 2026, 19(9), 2177; https://doi.org/10.3390/en19092177 - 30 Apr 2026
Viewed by 243
Abstract
This study develops a lifecycle economic comparison framework for shared energy storage, in which multiple users share a common storage asset through capacity leasing. A multi-service revenue structure, including capacity leasing, spot-market arbitrage, auxiliary frequency regulation, peak shaving, and capacity compensation, is established [...] Read more.
This study develops a lifecycle economic comparison framework for shared energy storage, in which multiple users share a common storage asset through capacity leasing. A multi-service revenue structure, including capacity leasing, spot-market arbitrage, auxiliary frequency regulation, peak shaving, and capacity compensation, is established for comparative evaluation. Case studies are conducted for lithium iron phosphate (LFP) and vanadium redox flow (VRF) batteries across six representative Chinese electricity markets and six standardized revenue-combination scenarios. The results show that, among the scenarios that more closely reflect current operating practices, P3 (capacity compensation + spot market + auxiliary frequency regulation) delivers the highest net present value (NPV). P6 combines all five revenue streams without explicitly modeling service-coupling dispatch constraints, and is therefore treated as a theoretical benchmark rather than an immediately deployable operating mode. Under this benchmark assumption, its calculated NPV is 21.1% and 41.7% higher than that of P3 for the two battery types, respectively. The study also shows that power-related services are more sensitive to rated power, while spot-market and peak-shaving revenues are more dependent on rated capacity. Full article
(This article belongs to the Special Issue Optimization Methods for Electricity Market and Smart Grid)
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31 pages, 3506 KB  
Article
An Exact Spectral Refinement Method for Nonconvex Branch-Flow Feasibility in Active Distribution Networks
by Laite Dang, Ming Ni, Xiaochuan Song, Yi Yuan and Tao Ding
Energies 2026, 19(4), 1009; https://doi.org/10.3390/en19041009 - 14 Feb 2026
Viewed by 365
Abstract
High penetration of distributed photovoltaics (PV) makes hosting-capacity assessment and active distribution network operation challenging, primarily due to the need to accurately restore nonconvex branch-flow equalities rather than relying on relaxations that may produce physically inconsistent solutions. This paper develops an ADMM-coordinated framework [...] Read more.
High penetration of distributed photovoltaics (PV) makes hosting-capacity assessment and active distribution network operation challenging, primarily due to the need to accurately restore nonconvex branch-flow equalities rather than relying on relaxations that may produce physically inconsistent solutions. This paper develops an ADMM-coordinated framework with an exact spectral refinement for QP1QC subproblems, which converts the semidefinite characterization into a tractable one-dimensional refinement over a generalized-eigenvalue-defined interval and enables reliable primal recovery of the original equality constraints. Numerical tests on modified IEEE 33-, 792-, and 1137-bus feeders show that the proposed method substantially improves equality restoration: the normalized mismatch of nonconvex equalities is reduced from 82–108% under SOCP/SDP relaxations to 0.004% on the 33-bus system, and from 94–98% to 0.67% on the 792-bus system; on the 1137-bus system, the mismatch remains 6.4%, still far below the relaxation baselines. Compared with an SDP-based hidden-convex benchmark, the proposed approach preserves essentially the same optimization outcomes while achieving 7–16× lower runtime and converging in 8–13 ADMM iterations. Full article
(This article belongs to the Special Issue Optimization Methods for Electricity Market and Smart Grid)
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19 pages, 5458 KB  
Article
Coordinated Optimal Dispatch of Source–Grid–Load–Storage Based on Dynamic Electricity Price Mechanism
by Xiangdong Meng, Dexin Li, Chenggang Li, Haifeng Zhang, Xinyue Piao and Hui Luan
Energies 2025, 18(23), 6277; https://doi.org/10.3390/en18236277 - 28 Nov 2025
Cited by 1 | Viewed by 822
Abstract
Under the backdrop of the “dual carbon” strategy, the rapid increase in renewable energy penetration has exacerbated challenges such as widening peak–valley load gaps and insufficient grid regulation capacity, highlighting the urgent need to establish a market-oriented collaborative dispatching mechanism. This paper proposes [...] Read more.
Under the backdrop of the “dual carbon” strategy, the rapid increase in renewable energy penetration has exacerbated challenges such as widening peak–valley load gaps and insufficient grid regulation capacity, highlighting the urgent need to establish a market-oriented collaborative dispatching mechanism. This paper proposes a peak-shaving and valley-filling dispatching approach based on a multi-agent system (MAS) to enhance both the regulatory capability and economic efficiency of power grids. A multi-agent collaborative architecture is established on the generation side, where behavioral modeling and interaction simulations of generation, load, and energy storage agents are conducted using the NetLogo platform to emulate dynamic responses under market conditions. On the grid side, dynamic electricity pricing and energy storage control strategies are implemented. An integrated time-of-use electricity pricing mechanism is designed that incorporates environmental pollution factors, supply–demand state factors, and price-smoothing factors to dynamically adjust tariffs. A price-responsive load demand model and a dynamic threshold-based energy storage control strategy are developed to facilitate flexible regulation. On the load side, an optimized dispatch model is formulated with dual objectives of minimizing system operating costs and reducing the standard deviation of the net load profile. The Beetle Antennae Search (BAS) algorithm is employed to solve the model, striking a balance between economic efficiency and stability. Case study results demonstrate that, compared with traditional dispatch methods, the coordinated optimization of the BAS algorithm and the dynamic pricing mechanism proposed in this paper achieves a dual improvement in solution efficiency and economy. This ultimately reduces the system’s peak-to-valley difference by 10.92% and operating costs by 66.2%, proving its effectiveness and superiority in power grids with high renewable energy penetration. Full article
(This article belongs to the Special Issue Optimization Methods for Electricity Market and Smart Grid)
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