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Challenges and Research Trends of Renewable Energy Power System

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: closed (24 October 2022) | Viewed by 23141

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Dr. Yogendra Arya

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Department of Electrical Engineering, J.C. Bose University of Science & Technology, YMCA, Sector-6, Faridabad, India
Interests: renewable energy; power/energy systems; energy storage system; computer simulation; modelling; automatic generation control; load frequency control; nonlinear control; soft computing techniques; artificial intelligence techniques; fuzzy controller; fuzzy systems; electrical engineering; power system operation and control; control systems/engineering

Special Issue Information

Dear Colleagues,

Through the last decade, the power sector has experienced significant changes due to the incessantly swelling load demand, rapid reduction in fossil fuels, and electricity deregulation policies. Furthermore, because of the modern lifestyle, a growing power demand, growth in industrialization, environmental concerns, and the integration of renewable energy sources (RESs), wind and solar energy in power systems has become the expected choice, with fossil fuel reserves anticipated to naturally come to an end in the future. Consequently, alternatives and RESs will have a noteworthy role in the near-future global energy portfolio.

The fabulous advantages of RESs are their no-carbon emission, clean source, plentiful availability, being environmentally friendly, resource conservation, energy security, health benefits, improving social and economic development through potential employment opportunities, energy access, climate change mitigation, etc. However, RES power generation is intermittent in nature and rests upon weather conditions and its characteristic changes at every instant of time. Additionally, with RES integration, there is uncertainty regarding both the supply and demand sides, possibly creating challenges in power systems regarding various issues such as voltage and frequency stability, decline in the system inertia, intermittent generation, high starting costs, low-grade power quality, demand-supply unbalancing and system reliability.

An innovative outlook and novel ideas are needed to alleviate the aforementioned problems to enhance the penetration of RESs in the electric power grid to convert the old-fashioned electricity grids into smart grids. The variety of energy storage system (ESS) technologies requires development and use in power systems. Although, at the same time, the liberalization of energy markets, revised incentives policies and technology upgrading policies are required to generate competition among generation companies to benefit consumers and grid reliability.

We invite papers related to challenges and new research trends in RES-integrated power systems, topics of interest comprising of automatic generation control (AGC), load frequency control, automatic voltage control (AVR), optimal energy storage devices, hydro power plants, distributed generations, smart grids, power quality, energy harvesting, RES integration into the power system, the flexible AC transmission system (FACTS), etc.

The Special Issue aims to divide problems related to the integration of renewable energy sources into both large and small power energy systems. This consideration includes renewable sources’ influence on the intelligent network construction and the energy market design, also assessing the impact of the distributed generation increase on the energy power system’s stability and reliability, the behaviour of distributed generation in the presence of disturbances in the energy system and many other factors. In this Special Issue, we wish to present results of analytical, experimental or numerical studies of scientists from all over the world, which shall become available to a wide audience through the open access journal Energies, helping to solve the abovementioned problems, also potentially benefiting researchers and policy makers worldwide.

Dr. Yogendra Arya
Guest Editor

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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

renewable energy sources (RESs)
solar power plant
wind power plant
biomass/biofuels energy plant
tidal/marine energy plants
geothermal energy plant
micro-grid system
distributed generation (DG)
electric vehicle (EV)
RES-based EV changing management
energy storage systems (ESS)
hybrid power systems
secondary/primary frequency regulation
power system reliability
power system stability
power electronics in renewable energy systems
power system control
restructured power system
hydro power plants
advanced modelling approaches
electricity markets and policy group
electricity supply industry
energy trading
power system transient stability
small-signal stability
voltage stability
demand side management
power system flexibility
reliability and security of supply
smart grid
smart inverters
regulatory and policy issues
forecasting strategies
impacts of COVID-19 pandemic on the RES-based energy systems
use of AI/soft computing techniques in RES-based power systems

Published Papers (11 papers)

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Research

Jump to: Review

26 pages, 15456 KiB

Open AccessFeature PaperArticle

Real-Time Validation of a Novel IAOA Technique-Based Offset Hysteresis Band Current Controller for Grid-Tied Photovoltaic System

by Bhabasis Mohapatra, Binod Kumar Sahu, Swagat Pati, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak and Mosleh Alharthi

Energies 2022, 15(23), 8790; https://doi.org/10.3390/en15238790 - 22 Nov 2022

Cited by 5 | Viewed by 1996

Abstract

Renewable energy sources have power quality and stability issues despite having vast benefits when integrated with the utility grid. High currents and voltages are introduced during the disconnection or injection from or into the power system. Due to excessive inverter switching frequencies, distorted voltage waveforms and high distortions in the output current may be observed. Hence, advancing intelligent and robust optimization techniques along with advanced controllers is the need of the hour. Therefore, this article presents an improved arithmetic optimization algorithm and an offset hysteresis band current controller. Conventional hysteresis band current controllers (CHCCs) offer substantial advantages such as fast dynamic response, over-current, and robustness in response to impedance variations, but they suffer from variable switching frequency. The offset hysteresis band current controller utilizes the zero-crossing time of the current error for calculating the lower/upper hysteresis bands after the measurement of half of the error current period. The duty cycle and hysteresis bands are considered as design variables and are optimally designed by minimizing the current error and the switching frequency. It is observed that the proposed controller yields a minimum average switching frequency of 2.33 kHz and minimum average switching losses of 9.07 W in comparison to other suggested controllers. Results are validated using MATLAB/Simulink environment followed by real-time simulator OPAL-RT 4510. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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19 pages, 10260 KiB

Open AccessArticle

Intelligent Control of Irrigation Systems Using Fuzzy Logic Controller

by Arunesh Kumar Singh, Tabish Tariq, Mohammad F. Ahmer, Gulshan Sharma, Pitshou N. Bokoro and Thokozani Shongwe

Energies 2022, 15(19), 7199; https://doi.org/10.3390/en15197199 - 30 Sep 2022

Cited by 8 | Viewed by 3451

Abstract

In this paper, we explain the design and implementation of an intelligent irrigation control system based on fuzzy logic for the automatic control of water pumps used in farms and greenhouses. This system enables its user to save water and electricity and prevent over-watering and under-watering of the crop by taking into account the climatic parameters and soil moisture. The irrigation system works without human intervention. The climate sensors are packaged using electronic circuits, and the whole is interfaced with an Arduino and a Simulink model. These sensors provide information that is used by the Simulink model to control the water pump speed; the speed of the water pump is controlled to increase or decrease the amount of water that needs to be pushed by the pump. The Simulink model contains the fuzzy control logic that manages the data read by the Arduino through sensors and sends the command to change the pump speed to the Arduino by considering all the sensor data. The need for human intervention is eliminated by using this system and a more successful crop is produced by supplying the right amount of water to the crop when it is needed. The water supply is stopped when a sufficient amount of moisture is present in the soil and it is started as soon as the soil moisture levels drops below certain levels, depending upon the environmental factors. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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25 pages, 4539 KiB

Open AccessArticle

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods

by Sivakavi Naga Venkata Bramareswara Rao, Venkata Pavan Kumar Yellapragada, Kottala Padma, Darsy John Pradeep, Challa Pradeep Reddy, Mohammad Amir and Shady S. Refaat

Energies 2022, 15(17), 6124; https://doi.org/10.3390/en15176124 - 23 Aug 2022

Cited by 41 | Viewed by 2812

Abstract

The modern-day urban energy sector possesses the integrated operation of various microgrids located in a vicinity, named cluster microgrids, which helps to reduce the utility grid burden. However, these cluster microgrids require a precise electric load projection to manage the operations, as the integrated operation of multiple microgrids leads to dynamic load demand. Thus, load forecasting is a complicated operation that requires more than statistical methods. There are different machine learning methods available in the literature that are applied to single microgrid cases. In this line, the cluster microgrids concept is a new application, which is very limitedly discussed in the literature. Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand in the short term. The effectiveness of these methods is analyzed by computing various factors such as root mean square error, R-square, mean square error, mean absolute error, mean absolute percentage error, and time of computation. From this, it is observed that the ANN provides effective forecasting results. In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. The effectiveness of these optimization algorithms is verified in terms of training, test, validation, and error analysis. The proposed system simulation is carried out using the MATLAB/Simulink-2021a^® software. From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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30 pages, 7196 KiB

Open AccessArticle

Real-Time Peak Valley Pricing Based Multi-Objective Optimal Scheduling of a Virtual Power Plant Considering Renewable Resources

by Anubhav Kumar Pandey, Vinay Kumar Jadoun and Jayalakshmi N. Sabhahit

Energies 2022, 15(16), 5970; https://doi.org/10.3390/en15165970 - 18 Aug 2022

Cited by 10 | Viewed by 1714

Abstract

In the era of aiming toward reaching a sustainable ecosystem, the primary focus is to curb the emissions generated by non-conventional resources. One way to achieve this goal is to find an alternative to traditional power plants (TPP) by integrating various distributed energy resources (DERs) via a Virtual Power Plant (VPP) in modern power systems. Apart from reducing emissions, a VPP enhances the monetary benefits to all its participants, including the DER owners, participants, and utility personnel. In this paper, the multi-objective optimal scheduling of the VPP problem considering multiple renewable energy resources has been solved using the multi-objective black widow optimization (MOBWO) algorithm. Renewable resources consist of solar PV modules, wind turbines, fuel cells, electric loads, heat-only units, and CHP units. The weighting factor method was adopted to handle the multi-objective optimal scheduling (MOOS) problem by simultaneously maximizing profit and minimizing emission while satisfying the related constraints. In this research, a peak valley power pricing strategy is introduced and the optimal scheduling of the VPP is attained by performing a multi-objective scheduling strategy (MOSS), which is day-ahead (on an hourly basis) and 15-min based (for a one-day profile), to observe the behavior of the anticipated system with a better constraint handling method. This algorithm is capable of dealing with a complex problem in a reduced computational time, ensuring the attainment of the considered objective functions. The numerical results obtained by the MOBWO algorithm after 100 independent trials were compared with the latest published work showing the effectiveness and suitability of the developed system. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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16 pages, 4084 KiB

Open AccessArticle

Super-Twisting Algorithm-Based Virtual Synchronous Generator in Inverter Interfaced Distributed Generation (IIDG)

by Sudhir Kumar Singh, Rajveer Singh, Haroon Ashfaq, Sanjeev Kumar Sharma, Gulshan Sharma and Pitshou N. Bokoro

Energies 2022, 15(16), 5890; https://doi.org/10.3390/en15165890 - 14 Aug 2022

Cited by 4 | Viewed by 1360

Abstract

The significant proliferation of renewable resources, primarily inverter interfaced distributed generation (IIDG) in the utility grid, leads to a dearth of overall inertia. Subsequently, the system illustrates more frequency nadir and a steeper frequency response. This may degrade the dynamic frequency stability of the overall system. Further, virtual inertia has been synthetically developed in IIDG, which is known as a virtual synchronous generator (VSG). In this work, a novel STO-STC-based controller has been developed, which offers flexible inertia following system disturbance. The controller is based on the super-twisting algorithm (STA), which is a further advancement in the conventional sliding mode control (SMC), and has been incorporated in the control loop of the VSG. In this scheme, two steps have been implemented, where the first one is to categorize all states of the system using a super-twisting observer (STO) and further, it is required to converge essential states very quickly, exploiting a super-twisting controller (STC). Thus, the STO-STC controller reveals a finite-time convergence to the numerous frequency disturbances, based on various case studies. The performance of the controller has been examined in the MATLAB environment with time–domain results that corroborate the satisfactory performance of the STO-STC scheme and that illustrate eminence over the state of the art. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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15 pages, 6243 KiB

Open AccessArticle

Coordinated Control of Wind Energy Conversion System during Unsymmetrical Fault at Grid

by Hemant Ahuja, Arika Singh, Sachin Sharma, Gulshan Sharma and Pitshou N. Bokoro

Energies 2022, 15(13), 4898; https://doi.org/10.3390/en15134898 - 4 Jul 2022

Cited by 7 | Viewed by 1468

Abstract

High penetration of wind power into the grid necessitates the coordinated action of wind energy conversion systems and the grid. A suitable generation control is required to fulfill the grid integration requirements, especially during faults. A system using a pair of voltage source converters with a squirrel cage induction generator coupled to a wind turbine is proposed to provide fault ride-through during grid faults. A threefold action is used for providing the effective fault ride-through via coordinated action of the machine side and the grid side converter. The entire wind energy conversion system is controlled such that the wind turbine remains connected even during the faults. To implement the threefold action: (i) A decoupled current controller is placed in the grid side converter, which separately controls the positive and negative sequence currents arising during faults. The grid side converter controller is capable of eliminating the double frequency oscillations at the dc-link voltage and, hence, real power, which arises during the unsymmetrical faults; (ii) Reactive power injection is additionally provided by the grid side converter for better grid support; and (iii) The vector control technique is used in machine side converter along with the droop control to adjust the generator speed and the torque resulting in actuation of the pitch control mechanism to limit power generation without shutdown of the turbine. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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17 pages, 4892 KiB

Open AccessArticle

A Fuzzy-PSO-PID with UPFC-RFB Solution for an LFC of an Interlinked Hydro Power System

by Milan Joshi, Gulshan Sharma, Pitshou N. Bokoro and Narayanan Krishnan

Energies 2022, 15(13), 4847; https://doi.org/10.3390/en15134847 - 1 Jul 2022

Cited by 14 | Viewed by 1694

Abstract

An LFC plays a vital part in passing on quality electric energy to energy consumers. Furthermore, with cutting-edge designs to move to modern and pollution-free energy generation, it may be conceivable to have a major hydropower in the future. Hydro plants are not suitable for continuous load alteration due to the large response time of hydroturbines. Hence, this paper shows a novel control design for an LFC of a hydro-hydro interlinked system based on joint actions of fuzzy logic with PID effectively optimized through particle swarm optimization (PSO) resulting in a Fuzzy-PSO-PID. The outcome of Fuzzy-PSO-PID is evaluated for step load variation in one of the regions of hydropower, and the outcomes of Fuzzy-PSO-PID are compared with a recently published LFC with respect to integral time absolute error (ITAE) value, values of PID, and graphical outcomes to show the impact of the proposed LFC action. The numerical results show that the ITAE value (0.002725) obtained through the proposed design is minimum in comparison to error values achieved through other LFC actions, and the pickup values obtained on these error values are considered to achieve the desired LFC. However, there is still scope for LFC enhancement as responses of hydropower are sluggish with higher oscillations; hence the UPFC and RFB are integrated into the interlinked hydro-hydro system, and the application outcomes are evaluated again considering the non-linearity, standard load alteration, random load pattern, and in view of parametric alterations. It is seen that the ITAE value reduces to 0.002471 from 0.002725 when UPFC is connected to the tie-line, and it further reduces to 0.001103 when a UPFC-RFB combination is used with Fuzzy-PSO-PID for a hydro leading system. The positive impact of the UPFC-RFB for hydropower is also seen from the application results. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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16 pages, 3116 KiB

Open AccessArticle

Available Transfer Capability Enhancement in Deregulated Power System through TLBO Optimised TCSC

by Anurag Gautam, Ibraheem, Gulshan Sharma, Pitshou N. Bokoro and Mohammad F. Ahmer

Energies 2022, 15(12), 4448; https://doi.org/10.3390/en15124448 - 18 Jun 2022

Cited by 7 | Viewed by 1649

Abstract

Rapid industrial development and innovations in technology bring about the menace of congestion in deregulated power systems (DPS). The transmission lines are continuously working under a stressed condition with reduced power transfer capacity. In this situation, the power losses and voltage deviations at the load buses are increased and hence reduce the system stability. To mitigate congestion, improving available transfer capability (ATC) of the transmission system is one of the most feasible and practical solution. This paper focuses on the implementation of Thyristor Controlled Series capacitor (TCSC) to mitigate congestion by enhancing ATC and via reducing power losses. AC Power Transfer Distribution Factor (ACPTDF) is applied to calculate ATC and to find the location of TCSC. To optimize the TCSC parameter (reactance), a Teaching Learning Based Optimization (TLBO) is proposed in the present work. The proposed optimization is validated on the IEEE 30 Bus system. The results are validated by matching with the results obtained through standard grey wolf optimization (GWO) and particle swarm optimization (PSO) techniques. The results show that despite two antagonistic objectives of ATC enhancement and power loss reduction, TLBO outperformed the other optimization techniques under different contingency conditions. The overall ATC of the IEEE 30 Bus system for the bilateral transactions is enhanced by 11.86%. Further active and reactive power losses are reduced by 16.7% and 29.6% for DPS. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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19 pages, 6133 KiB

Open AccessArticle

A Novel Solution for Solving the Frequency Regulation Problem of Renewable Interlinked Power System Using Fusion of AI

by Mohammed Ozayr Abdul Kader, Kayode Timothy Akindeji and Gulshan Sharma

Energies 2022, 15(9), 3376; https://doi.org/10.3390/en15093376 - 6 May 2022

Cited by 6 | Viewed by 1832

Abstract

The requirement for clean energy has increased drastically over the years due to the emission of CO₂ and the degrading of the environment by introducing Renewable Energy Systems (RES) into the existing power grid. While these systems are a positive change, they come at a cost, with some issues relating to the stability of the grid and feasibility. Hence, this research paper closely investigates the modeling and interlinking of photovoltaic (PV)-based solar power and Double-Fed Induction Generator (DFIG)-based wind turbines with the conventional power systems. RES has been known to contribute to a highly non-linear system and complexity. To return the power systems to their original state after a load disturbance, a novel control technique based on the fractional-order Type-2 Fuzzy logic system, well developed via particle swarm optimization (PSO), has been utilized for solving the frequency control problem of a renewable interlinked power system. The efficacy of the proposed technique is validated for various possible operating conditions and the system results are compared with some of the recent methods with and without including non-linearity, and the performance of the controllers is superimposed on frequency/time graphs for ease of understanding to show the benefits of the proposed research work. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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26 pages, 7583 KiB

Open AccessArticle

Unintentional Passive Islanding Detection and Prevention Method with Reduced Non-Detection Zones

by Sowmya Ramachandradurai, Narayanan Krishnan and Natarajan Prabaharan

Energies 2022, 15(9), 3038; https://doi.org/10.3390/en15093038 - 21 Apr 2022

Cited by 8 | Viewed by 1227

Abstract

Islanding detection and prevention are involved in tandem with the rise of large- and small-scale distribution grids. To detect islanded buses, either the voltage or the frequency variation has been considered in the literature. A modified passive islanding detection strategy that coordinates the V-F (voltage–frequency) index was developed to reduce the non-detection zones (NDZs), and an islanding operation is proposed in this article. Voltage and frequency were measured at each bus to check the violation limits by implementing the proposed strategy. The power mismatch was alleviated in the identified islands by installing a battery and a diesel generator, which prevented islanding events. The proposed strategy was studied on the three distinct IEEE radial bus distribution systems, namely, 33-, 69-, and 118-bus systems. The results obtained in the above-mentioned IEEE bus systems were promising when the proposed strategy was implemented. The results of the proposed strategy were compared with those of methods developed in the recent literature. As a result, the detection time and number of islanded buses are reduced. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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Review

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21 pages, 2393 KiB

Open AccessReview

Operational Issues of Contemporary Distribution Systems: A Review on Recent and Emerging Concerns

by Kabulo Loji, Sachin Sharma, Nomhle Loji, Gulshan Sharma and Pitshou N. Bokoro

Energies 2023, 16(4), 1732; https://doi.org/10.3390/en16041732 - 9 Feb 2023

Cited by 1 | Viewed by 1928

Abstract

Distribution systems in traditional power systems (PS) constituted of passive elements and the distribution issues were then limited to voltage and thermal constraints, harmonics, overloading and unbalanced loading, reactive power compensation issues, faults and transients, loss minimization and frequency stability problems, to name a few. Contemporary distribution systems are becoming active distributed networks (ADNs) that integrate a substantially increasing amount of distributed energy resources (DERs). DERS include distributed generation (DG) sources, energy storage resources and demand side management (DSM) options. Despite their evidenced great benefits, the large-scale deployment and integration of DERs remain a challenge as they subsequently lead to the network operational and efficiency issues, hampering PS network reliability and stability. This paper carries out a comprehensive literature survey based on the last decade’s research on operational challenges reported and focusing on dispatchable and non-dispatchable DGs grid integration, on various demand response (DR) mechanisms and, on battery energy storage system (BESS) charging and discharging challenges, with the aim to pave the way to developing suitable optimization techniques that will solve the coordination of multiple renewable sources, storage systems and DRs to minimize distribution systems’ operational issues and thus improve stability and reliability. This paper’s findings assist the researchers in the field to conduct further research and to help PS planners and operators decide on appropriate relevant technologies that address challenges inherent to DG grid integration. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Renewable Energy Power System)

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