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Control of Renewable Energy Sources in Power Systems and Smart Grids

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

Deadline for manuscript submissions: closed (28 November 2023) | Viewed by 8228

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Special Issue Editor

Dr. Yonghao Gui

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Guest Editor

The Electrification and Energy Infrastructures Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Interests: model and control of power electronics; renewable energy integration; digitalization grid; power electronics dominated grid
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To get the low-carbon energy infrastructure, tremendous renewable energy sources are integrated into the modern power grid while reducing conventional fossil power plants. In this transition, the power electronics-based renewable energy system acts as one of the most important role players, which can convert renewable energies to electrical energy. Due to the recent development of power electronics technology and its control, renewable energy supports more efficient, economical, and reliable power than ever before.

Recently, various loads (e.g., electrical vehicle, data center, and motor) have been connected to the grid based on power electronics. With the high-penetration level of power electronics-based renewable energy in the power grid, more and more issues are to be challenged, such as performance deterioration, efficiency decrease, and power quality reduction, as well as instability phenomena. Herein, this Special Issue focuses on recent advances and challenges in power electronics-based renewable energy sources integrated into the power grid.

Dr. Yonghao Gui
Guest Editor

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Keywords

model and control of power electronics
advanced power electronic technologies for renewable energy
analysis of power electronics in power systems
power electronics dominated power grid
renewable energy integration

Published Papers (6 papers)

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Research

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32 pages, 7799 KiB

Open AccessFeature PaperArticle

Improved Active and Reactive Energy Forecasting Using a Stacking Ensemble Approach: Steel Industry Case Study

by Hamza Mubarak, Mohammad J. Sanjari, Sascha Stegen and Abdallah Abdellatif

Energies 2023, 16(21), 7252; https://doi.org/10.3390/en16217252 - 25 Oct 2023

Viewed by 797

Abstract

The prevalence of substantial inductive/capacitive loads within the industrial sectors induces variations in reactive energy levels. The imbalance between active and reactive energy within the network leads to heightened losses, diminished network efficiency, and an associated escalation in operating costs. Therefore, the forecasting of active and reactive energy in the industrial sector confers notable advantages, including cost reduction, heightened operational efficiency, safeguarding of equipment, enhanced energy consumption management, and more effective assimilation of renewable energy sources. Consequently, a range of specialized forecasting methods for different applications have been developed to address these challenges effectively. This research proposes a stacked ensemble methodology, denoted as Stack-XGBoost, leveraging three distinct machine learning (ML) methods: extra trees regressor (ETR), adaptive boosting (AdaBoost), and random forest regressor (RFR), as foundational models. Moreover, the incorporation of an extreme gradient boosting (XGBoost) algorithm as a meta-learner serves to amalgamate the predictions generated by the base models, enhancing the precision of the active/reactive energy consumption forecasting using real time data for steel industry. To assess the efficacy of the proposed model, diverse performance metrics were employed. The results show that the proposed Stack-XGBoost model outperformed other forecasting methods. Additionally, a sensitivity analysis was conducted to assess the robustness of the proposed method against variations in input parameters. Full article

(This article belongs to the Special Issue Control of Renewable Energy Sources in Power Systems and Smart Grids)

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12 pages, 3318 KiB

Open AccessArticle

The Application of Tunable Magnetic Devices in Electrical Power Systems with Adaptive Features

by Michał Gwóźdź

Energies 2023, 16(17), 6135; https://doi.org/10.3390/en16176135 - 23 Aug 2023

Viewed by 685

Abstract

This work is devoted to possible implementation of tunable magnetic devices in electrical systems with adaptive properties. The basic idea, underlying operation of the presented magnetic device, depends on interaction of two (or more) magnetic fluxes in a quasi-linear range of ferromagnetic core characteristics. This is a new approach to the design of such magnetic elements; typically, saturation phenomenon of the ferromagnetic core of an inductor is used to change a value of its inductance. The good examples of adaptive electrical power systems can be devices for improving a quality of electrical energy. When used in compensators of reactive and a distortion power (or a reactive power only), tunable magnetic devices clearly offer wider possibilities for the compensation, compared to solutions, using compensators based on fixed magnetic elements. However, the application of the proposed tunable device in an adaptive compensator is only one example of its possible use in an electrical power area. In this work, the following issues are presented: exemplary solution of the adaptive passive compensator, basics of operation of tunable magnetic device, and test results of the experimental model of an electrical system with such a device. Full article

(This article belongs to the Special Issue Control of Renewable Energy Sources in Power Systems and Smart Grids)

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24 pages, 9525 KiB

Open AccessArticle

Time Series Optimization-Based Characteristic Curve Calculation for Local Reactive Power Control Using Pandapower-PowerModels Interface

by Zheng Liu, Maryam Majidi, Haonan Wang, Denis Mende and Martin Braun

Energies 2023, 16(11), 4385; https://doi.org/10.3390/en16114385 - 29 May 2023

Viewed by 1365

Abstract

Local reactive power control in distribution grids with a high penetration of distributed energy resources (DERs) will be essential in future power system operation. Appropriate control characteristic curves for DERs support stable and efficient distribution grid operation. However, the current practice is to configure local controllers collectively with constant characteristic curves that may not be efficient for volatile grid conditions or the desired targets of grid operators. To address this issue, this paper proposes a time series optimization-based method to calculate control parameters, which enables each DER to be independently controlled by an exclusive characteristic curve for optimizing its reactive power provision. To realize time series reactive power optimizations, the open-source tools pandapower and PowerModels are interconnected functionally. Based on the optimization results, Q(V)- and Q(P)-characteristic curves can be individually calculated using linear decision tree regression to support voltage stability, provide reactive power flexibility and potentially reduce grid losses and component loadings. In this paper, the newly calculated characteristic curves are applied in two representative case studies, and the results demonstrate that the proposed method outperforms the reference methods suggested by grid codes. Full article

(This article belongs to the Special Issue Control of Renewable Energy Sources in Power Systems and Smart Grids)

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20 pages, 6249 KiB

Open AccessArticle

A Comparison of Grid-Connected Local Hospital Loads with Typical Backup Systems and Renewable Energy System Based Ad Hoc Microgrids for Enhancing the Resilience of the System

by Majid Ali, Juan C. Vasquez, Josep M. Guerrero, Yajuan Guan, Saeed Golestan, Jorge De La Cruz, Mohsin Ali Koondhar and Baseem Khan

Energies 2023, 16(4), 1918; https://doi.org/10.3390/en16041918 - 15 Feb 2023

Cited by 5 | Viewed by 1956

Abstract

Extreme weather conditions and natural disasters (ND) are the main causes of power outages in the electric grid. It is necessary to strengthen the electrical power system’s resilience during these catastrophic occurrences, and microgrids may be seen as the best way to achieve this goal. In this paper, two different energy system scenarios were proposed for increasing the resiliency of the electric power system during random outages. In the first scenario, a diesel generator (DG) was used to deliver energy to key loads during grid disruptions, in conjunction with a utility electric grid (UEG) and local electric load (ELL). A grid-connected ad hoc microgrid (MG) with a photovoltaic (PV) system, a battery energy storage (BES) system, and local electric loads made up the second scenario. The PV system and the BES system were used to supply the key loads with electricity during the outage. The major aim of this research was to compare the two resilient-based systems from the perspectives of technology, economics, and the environment. Given that it requires greater resilience than the other loads during severe weather, a hospital load on Indonesia’s Lombok Island was chosen as the critical load. The objective function considers the system’s predefined constraints to reduce the overall net present cost (NPC) and the cost of energy in order to maximize the system resilience (COE). The Optimization of Multiple Energy Resources (HOMER) Grid simulated a 3-day outage in August 2021, and the results demonstrated that the resiliency enhancement for both scenarios was nearly identical. The first scenario resulted in fewer CO₂ emissions; however, the second scenario delivered lower operating costs and COE. The simulation’s findings showed that system 1 created an annual emission of 216.902 kg/yr while system 2 only produced an emission of 63.292 kg/yr. This study shows that since RES-based MGs don’t burn fossil fuels to generate power, they are more environmentally friendly resources. Full article

(This article belongs to the Special Issue Control of Renewable Energy Sources in Power Systems and Smart Grids)

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17 pages, 7442 KiB

Open AccessArticle

Modified Cascaded Controller Design Constructed on Fractional Operator ‘β’ to Mitigate Frequency Fluctuations for Sustainable Operation of Power Systems

by Muhammad Majid Gulzar, Sadia Murawwat, Daud Sibtain, Kamal Shahid, Imran Javed and Yonghao Gui

Energies 2022, 15(20), 7814; https://doi.org/10.3390/en15207814 - 21 Oct 2022

Cited by 9 | Viewed by 1509

Abstract

The demand for energy is increasing at an abrupt pace, which has highly strained the power system, especially with high share of power generation from renewable energy sources (RES). This increasing strain needs to be effectively managed for a continuous and smooth operation of the power system network. Generation and demand exhibit a strong correlation that directly creates an impact on the power system frequency. Fluctuations and disruptions in load frequency can manifest themselves as over-voltages and physical damages in the power grid and, in the worst case, can lead to blackouts. Thus, this paper proposed an effective solution to mitigate the load frequency problem(s), which is initiated by the changing load demand under high penetration of RES. This paper presented an improved cascaded structure, the proportional integral with a fractional operator coupled with proportional derivative

(PI - ({FO}_{P} + PD))

. The proposed

{FO}_{P} + PD

modifies the (1+PD) controller by introducing fractional properties that improve its tracking efficiency and mitigate frequency fluctuations taking minimal time. The introduction of

{FO}_{P} (β)

diversifies its tracking and overall controlling ability, which translates it as a significant controller. The controller optimal parameters are extracted by deploying a dragonfly search algorithm (DSA). The study of the results illustrates that the proposed design displays efficient performance under any disturbance or uncertainty in the power system. Full article

(This article belongs to the Special Issue Control of Renewable Energy Sources in Power Systems and Smart Grids)

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16 pages, 1655 KiB

Open AccessFeature PaperCommentary

Adaptation of High Spatio-Temporal Resolution Weather/Load Forecast in Real-World Distributed Energy-System Operation

by Amir Ali Safaei Pirooz, Mohammad J. Sanjari, Young-Jin Kim, Stuart Moore, Richard Turner, Wayne W. Weaver, Dipti Srinivasan, Josep M. Guerrero and Mohammad Shahidehpour

Energies 2023, 16(8), 3477; https://doi.org/10.3390/en16083477 - 16 Apr 2023

Cited by 2 | Viewed by 1238

Abstract

Despite significant advances in distributed renewable energy systems (DRES), the technology still faces several substantial challenges that prevent the large-scale adoption of these systems into a country’s energy sector. The intermittency of renewables, uncertainties associated with real-time multi-horizon weather and load forecasts, and lack of comprehensive control systems are among the main technical and regulatory challenges for the real-world adoption of DRES. This paper outlines the current state of knowledge in the real-world operation of DRES and also describes pathways and methodologies that enable and facilitate the uptake of DRES in a country’s energy sector. Full article

(This article belongs to the Special Issue Control of Renewable Energy Sources in Power Systems and Smart Grids)

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