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Advances in Stability Control, Optimal Operation and Modeling Analysis of Power System with High-Level Renewable Energy

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 4863

Special Issue Editors

Dr. Bo Zhang

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Interests: distributed power generation; smart grid; active distribution networks; optimal operation; stability control
Special Issues, Collections and Topics in MDPI journals
Dr. Jiaoxin Jia

E-Mail Website
Guest Editor
Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
Interests: virtual synchronous generator; virtual inertia control; primary frequency modulation; modeling and control of RES
Special Issues, Collections and Topics in MDPI journals
Dr. Sen Cui

E-Mail Website
Guest Editor
Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Interests: power electronics control; energy storage system; renewable energy generation; smart grid

Special Issue Information

Dear Colleagues,

The development of renewable energy resources (RES) has become an obvious choice as the world is obligated to support green energy and achieve carbon neutrality. In this context, a high proportion of RES with large capacity access has gradually become a typical feature of new power systems. The RES output has strong volatility/randomness, and the power electronic equipment has weak support. As the proportion of RES continues to increase, the proportion of synchronous generators decreases. The characteristics of low short-circuit ratio and low inertia of the power system become prominent, and the voltage/frequency support strength and stability margin of the power system decrease significantly. Power grid stability problems and power outages occur frequently around the world.

To address the related challenges, this Special Issue aims to provide a forum for all scholars to present their discoveries on technological developments in renewable energy and sustainability. Research areas may include (but are not limited to) the following:

  • Modeling and control of solar, wind, energy storage and emerging generation;
  • Modeling and analysis of renewable energy delivery system;
  • Flexible networking technology of renewable energy system;
  • Sensing technology of voltage spatial-temporal distribution;
  • Virtual inertia and primary frequency modulation control;
  • Inertia identification and evaluation analysis;
  • Volt/var optimal control of active distribution network based on RES;
  • Voltage regulation and power compensation strategy;
  • Inertia optimal configuration power system with high-level RES;
  • Virtual synchronous generator;
  • Energy management and tidal current control.

We look forward to receiving your contributions.

Dr. Bo Zhang
Dr. Jiaoxin Jia
Dr. Sen Cui
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. Sustainability 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 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

  • renewable energy
  • active distribution network
  • distributed energy
  • smart grid
  • energy storage
  • optimal operation
  • stability control

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Published Papers (4 papers)

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Research

17 pages, 3130 KiB  
Article
Short-Term Wind Power Prediction Based on a Modified Stacking Ensemble Learning Algorithm
by Yankun Yang, Yuling Li, Lin Cheng and Shiyou Yang
Sustainability 2024, 16(14), 5960; https://doi.org/10.3390/su16145960 - 12 Jul 2024
Viewed by 974
Abstract
A high proportion of new energy has become a prominent feature of modern power systems. Due to the intermittency, volatility, and strong randomness in wind power generation, an accurate and reliable method for the prediction of wind power is required. This paper proposes [...] Read more.
A high proportion of new energy has become a prominent feature of modern power systems. Due to the intermittency, volatility, and strong randomness in wind power generation, an accurate and reliable method for the prediction of wind power is required. This paper proposes a modified stacking ensemble learning method for short-term wind power predictions to reduce error and improve the generalization performance of traditional single networks in tackling the randomness of wind power. Firstly, the base learners including tree-based models and neural networks are improved based on the Bagging and Boosting algorithms, and a method for determining internal parameters and iterations is provided. Secondly, the linear integration and stacking integration models are combined to obtain deterministic prediction results. Since the modified stacking meta learner can change the weight, it will enhance the strengths of the base learners and optimize the integration of the model prediction to fit the second layer prediction, compared to traditional linear integration models. Finally, a numerical experiment showed that the modified stacking ensemble model had a decrease in MAPE from about 8.3% to 7.5% (an absolute decrease of 0.8%) compared to a single learner for the 15 min look-ahead tests. Changing variables such as the season and predicting the look-ahead time showed satisfactory improvement effects under all the evaluation criteria, and the superiority of the modified stacking ensemble learning method proposed in this paper regarding short-term wind power prediction performance was validated. Full article
(This article belongs to the Special Issue Advances in Stability Control, Optimal Operation and Modeling Analysis of Power System with High-Level Renewable Energy)
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22 pages, 5321 KiB  
Article
Sustainable Development Strategies in Power Systems: Day-Ahead Stochastic Scheduling with Multi-Sources and Customer Directrix Load Demand Response
by Jiacheng Liu, Shan Huang, Qiang Shuai, Tingyun Gu and Houyi Zhang
Sustainability 2024, 16(6), 2589; https://doi.org/10.3390/su16062589 - 21 Mar 2024
Cited by 1 | Viewed by 951
Abstract
Increasing the installed capacity of renewable energy sources (RESs) in the power system is significant for advancing sustainable development. As the proportion of RESs rapidly increases in power systems, the inherent stochasticity and variability of renewable energies significantly reduce the regulatory capacity of [...] Read more.
Increasing the installed capacity of renewable energy sources (RESs) in the power system is significant for advancing sustainable development. As the proportion of RESs rapidly increases in power systems, the inherent stochasticity and variability of renewable energies significantly reduce the regulatory capacity of generation resources. To compensate for the lack of power system flexibility, it is necessary to coordinate the participation of load-side resources in demand response (DR). Therefore, this paper proposes a solution to the diminished flexibility of power systems. It introduces a day-ahead stochastic scheduling model for an integrated thermal-hydro-wind-solar system. This model relies on customer directrix load (CDL) to efficiently absorb RES output. CDL represents an ideal load profile shape. Firstly, the stochastic scenario sets of RES output were modeled using Monte Carlo simulations, and the complementary characteristics between wind and solar output are considered using Copula theory. Then, CDL is introduced into day-ahead scheduling model, which considers relevant demand-side responsive load constraints. Secondly, customer-side DR effectiveness model is proposed to obtain the shaping load profile after DR, based on quantitative customer response effectiveness evaluation metrics. Lastly, system-side stochastic scheduling model of high-proportion RES power system is proposed based on the shaping load profile. Case studies were conducted on a modified IEEE-6 bus system. These studies show that the model effectively addresses the uncertainty of RES. It improves the power system’s regulation capability. Additionally, it promotes the absorption of RES. Full article
(This article belongs to the Special Issue Advances in Stability Control, Optimal Operation and Modeling Analysis of Power System with High-Level Renewable Energy)
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20 pages, 532 KiB  
Article
A Resilient Integrated Resource Planning Framework for Transmission Systems: Analysis and Optimization
by Mukesh Gautam, Timothy McJunkin and Ryan Hruska
Sustainability 2024, 16(6), 2449; https://doi.org/10.3390/su16062449 - 15 Mar 2024
Viewed by 1214
Abstract
This article presents a resilient Integrated Resource Planning (IRP) framework designed for transmission systems, with a specific focus on analyzing and optimizing responses to High-Impact Low-Probability (HILP) events. The framework aims to improve the resilience of transmission networks in the face of extreme [...] Read more.
This article presents a resilient Integrated Resource Planning (IRP) framework designed for transmission systems, with a specific focus on analyzing and optimizing responses to High-Impact Low-Probability (HILP) events. The framework aims to improve the resilience of transmission networks in the face of extreme events by prioritizing the assessment of events with significant consequences. Unlike traditional reliability-based planning methods that average the impact of various outage durations, this work adopts a metric based on the proximity of outage lines to generators to select HILP events. The system’s baseline resilience is evaluated by calculating load curtailment in different parts of the network resulting from HILP outage events. The transmission network is represented as an undirected graph. Graph-theoretic techniques are used to identify islands with or without generators, potentially forming segmented grids or microgrids. This article introduces Expected Load Curtailment (ELC) as a metric to quantify the system’s resilience. The framework allows for the re-evaluation of system resilience by integrating additional generating resources to achieve desired resilience levels. Optimization is performed in the re-evaluation stage to determine the optimal placement of distributed energy resources (DERs) for enhancing resilience, i.e., minimizing ELC. Case studies on the IEEE 24-bus system illustrate the effectiveness of the proposed framework. In the broader context, this resilient IRP framework aligns with energy sustainability goals by promoting robust and resilient transmission networks, as the optimal placement of DERs for resilience enhancement not only strengthens the system’s ability to withstand and recover from disruptions but also contributes to efficient resource utilization, advancing the overarching goal of energy sustainability. Full article
(This article belongs to the Special Issue Advances in Stability Control, Optimal Operation and Modeling Analysis of Power System with High-Level Renewable Energy)
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16 pages, 5421 KiB  
Article
Multiple-Zone Synchronous Voltage Regulation and Loss Reduction Optimization of Distribution Networks Based on a Dual Rotary Phase-Shifting Transformer
by Chen Shao, Xiangwu Yan, Yaohui Yang, Waseem Aslam, Jiaoxin Jia and Jiayao Li
Sustainability 2024, 16(3), 1029; https://doi.org/10.3390/su16031029 - 25 Jan 2024
Viewed by 860
Abstract
For the problem in which accessing a high proportion of renewable energy results in exceeding the limit in distribution network voltage, the existing regulating method experiences difficulty in considering the two-way voltage regulation and loss reduction optimization function. This study proposes a series-type [...] Read more.
For the problem in which accessing a high proportion of renewable energy results in exceeding the limit in distribution network voltage, the existing regulating method experiences difficulty in considering the two-way voltage regulation and loss reduction optimization function. This study proposes a series-type dual rotary phase-shifting transformer (DRPST) based on the principle of phase volume synthesis. This transformer exhibits bidirectional voltage regulation, high reliability, and low cost. First, the topology, operating principle, and equivalent circuit of DRPST are introduced, and its simplified circuit model is established. On the basis of this model, the causes of voltage exceeding the limits are analyzed and the active distribution network model that contains DRPST is constructed. A real-time rolling two-layer optimization strategy based on DRPST is proposed. The inner layer model is solved using the multi-objective particle swarm optimization algorithm with the objective of minimizing voltage deviation and line loss. The optimal compromise solution of the Pareto solution set of the inner layer model is determined using the fuzzy subordinate degree function method. The outer model is based on the optimal compromise solution of the inner model, and the DRPST output rotor angle is controlled without deviation through double closed-loop proportional–integral regulation. Finally, the correctness and effectiveness of the proposed topology and control method are verified via simulation and experimental analysis. Full article
(This article belongs to the Special Issue Advances in Stability Control, Optimal Operation and Modeling Analysis of Power System with High-Level Renewable Energy)
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