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Application of Advanced Control Theories to Power Electronics and Power Systems

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F3: Power Electronics".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 3334

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Prof. Dr. Isabel Jesus

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Department of Electrical Engineering, Institute of Engineering-Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, 4249-015 Porto, Portugal
Interests: photovoltaic systems; fractional order control systems; fuzzy control systems; evolutionary algorithms
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Special Issue Information

Dear Colleagues,

Power electronics and power systems involve many areas strongly important in the real world. Nowadays, these systems are related to the areas of energy markets and regulation, electric machines and drives, electronic devices, inverters, power converters, control, computational techniques or artificial intelligent algorithms, among many others.

The research in the area of power electronics and power systems focuses its attention on the management of electrical power and control, so that global energy consumption can be reduced. Improving the efficiency of power conversion systems is crucial to reducing energy waste, particularly during conversion.

In these fields, many works have aimed to improve the cost-effectiveness and efficiency of power electronics technologies and to guarantee the stability, reliability, and flexibility of power systems. To achieve that, several techniques have been implemented in industries in the fields of optimization converter topologies, design of advanced control algorithms, smart grid technologies, and exploring novel semiconductor devices. Nevertheless, some challenges related to power generation, the integration of renewable energy sources, the implementation of more efficient control algorithms, and the improvement of energetic distribution still need to be addressed.

In this perspective, the main topics of this Special Issue include, but are not limited to:

Advanced power semiconductor devices;

Medium voltage power electronics for applications in renewable energy;

Energy storage and smart grid systems;

High-frequency-power-electronic conversion systems;

DC power grids;

Power system analyses;

Modeling and simulation of power systems;

Energy system optimization;

Electricity markets;

Distributed generation;

Artificially intelligent algorithms for power systems.

Prof. Dr. Isabel Jesus
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

advanced power semiconductor devices
medium voltage power electronics for applications in renewable energy
energy storage and smart grid systems
high-frequency-power-electronic conversion systems
DC power grids
power system analyses
modeling and simulation of power systems
energy system optimization
electricity markets
distributed generation
artificially intelligent algorithms for power systems

Published Papers (3 papers)

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Research

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23 pages, 5817 KiB

Open AccessArticle

Investigation of Load, Solar and Wind Generation as Target Variables in LSTM Time Series Forecasting, Using Exogenous Weather Variables

by Thomas Shering, Eduardo Alonso and Dimitra Apostolopoulou

Energies 2024, 17(8), 1827; https://doi.org/10.3390/en17081827 - 11 Apr 2024

Viewed by 337

Abstract

Accurately forecasting energy metrics is essential for efficiently managing renewable energy generation. Given the high variability in load and renewable energy power output, this represents a crucial area of research in order to pave the way for increased adoption of low-carbon energy solutions. Whilst the impact of different neural network architectures and algorithmic approaches has been researched extensively, the impact of utilising additional weather variables in forecasts have received far less attention. This article demonstrates that weather variables can have a significant influence on energy forecasting and presents methodologies for using these variables within a long short-term memory (LSTM) architecture to achieve improvements in forecasting accuracy. Moreover, we introduce the use of the seasonal components of the target time series, as exogenous variables, that are also observed to increase accuracy. Load, solar and wind generation time series were forecast one hour ahead using an LSTM architecture. Time series data were collected in five Spanish cities and aggregated for analysis, alongside five exogenous weather variables, also recorded in Spain. A variety of LSTM architectures and hyperparameters were investigated. By tuning exogenous weather variables, a 33% decrease in mean squared error was observed for solar generation forecasting. A 22% decrease in mean absolute squared error (MASE), compared to 24-h ahead forecasts made by the Transmission Service Operator (TSO) in Spain, was also observed for solar generation. Compared to using the target variable in isolation, utilising exogenous weather variables decreased MASE by approximately 10%, 15% and 12% for load, solar and wind generation, respectively. By using the seasonal component of the target variables as an exogenous variable itself, we demonstrated decreases in MASE of 19%, 12% and 8% for load, solar and wind generation, respectively. These results emphasise the significant benefits of incorporating weather and seasonal components into energy-related time series forecasts. Full article

(This article belongs to the Special Issue Application of Advanced Control Theories to Power Electronics and Power Systems)

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22 pages, 6820 KiB

Open AccessArticle

Sizing PV and BESS for Grid-Connected Microgrid Resilience: A Data-Driven Hybrid Optimization Approach

by Mahtab Murshed, Manohar Chamana, Konrad Erich Kork Schmitt, Suhas Pol, Olatunji Adeyanju and Stephen Bayne

Energies 2023, 16(21), 7300; https://doi.org/10.3390/en16217300 - 27 Oct 2023

Cited by 2 | Viewed by 1359

Abstract

This article presents a comprehensive data-driven approach on enhancing grid-connected microgrid grid resilience through advanced forecasting and optimization techniques in the context of power outages. Power outages pose significant challenges to modern societies, affecting various sectors such as industries, households, and critical infrastructures. The research combines statistical analysis, machine-learning algorithms, and optimization methods to address this issue to develop a holistic approach for predicting and mitigating power outage events. The proposed methodology involves the use of Monte Carlo simulations in MATLAB for future outage prediction, training a Long Short-Term Memory (LSTM) network for forecasting solar irradiance and load profiles with a dataset spanning from 2009 to 2018, and a hybrid LSTM-Particle Swarm Optimization (PSO) model to improve accuracy. Furthermore, the role of battery state of charge (SoC) in enhancing system resilience is explored. The study also assesses the techno-economic advantages of a grid-tied microgrid integrated with solar panels and batteries over conventional grid systems. The proposed methodology and optimization process demonstrate their versatility and applicability to a wide range of microgrid design scenarios comprising solar PV and battery energy storage systems (BESS), making them a valuable resource for enhancing grid resilience and economic efficiency across diverse settings. The results highlight the potential of the proposed approach in strengthening grid resilience by improving autonomy, reducing downtime by 25%, and fostering sustainable energy utilization by 82%. Full article

(This article belongs to the Special Issue Application of Advanced Control Theories to Power Electronics and Power Systems)

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Review

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29 pages, 1866 KiB

Open AccessReview

A Review of Smart Energy Management in Residential Buildings for Smart Cities

by Faiza Qayyum, Harun Jamil and Faiyaz Ali

Energies 2024, 17(1), 83; https://doi.org/10.3390/en17010083 - 22 Dec 2023

Cited by 2 | Viewed by 901

Abstract

This survey critically examines the integration of energy management systems within smart residential buildings, serving as key nodes in the smart city network. It systematically maps out the intricate relationships between smart grid technologies, energy storage capabilities, infrastructure development, and their confluence in residential settings. From the evolution of power generation methods, incorporating both traditional and renewable sources, to the cutting-edge progress in energy-efficient transport systems, we assess their cumulative impact on the smart urban environment. While our approach is rooted in theoretical exploration rather than mathematical modeling, we provide a comprehensive review of the prevailing frameworks and methodologies that drive energy management in smart urban ecosystems. We also discuss the implications of these systems on urban sustainability and the critical importance of integrating various energy domains to facilitate effective energy governance. By bringing together a diverse array of scholarly insights, our paper aspires to enhance the understanding of energy interdependencies in smart cities and to catalyze the development of innovative, sustainable policies and practices that will define the future of urban energy management. Through this expanded perspective, we underscore the necessity of cross-disciplinary research and the adoption of holistic strategies to optimize energy usage, reduce carbon footprints, and promote resilient urban living in the era of smart cities. Full article

(This article belongs to the Special Issue Application of Advanced Control Theories to Power Electronics and Power Systems)

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