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Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources
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Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 38705

Special Issue Editors

Dr. Md Alamgir Hossain

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Guest Editor
Research Fellow at Queensland Micro-and Nano-technology Centre, Griffith University, Brisbane, QLD, Australia
Interests: AC/DC microgrids; machine learning; optimization, converter interfaced DG; energy storage devices
Special Issues, Collections and Topics in MDPI journals
Dr. ‪Ripon Kumar Chakrabortty

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Guest Editor
Capability Systems Centre, School of Engineering and IT, UNSW Canberra, Canberra, BC 2610, Australia
Interests: machine learning with optimization algorithms and applications; operations research and operations management techniques (focus: sustainable smart scheduling, project scheduling, logistics and supply chain management)
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Stefano Squartini

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Guest Editor
Department of Information Engineering, Università Politecnica delle Marche, 60121 Ancona, Italy
Interests: computational intelligence and digital signal processing, with special focus on speech/audio/music processing and energy management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Renewable energy sources are integrated significantly into existing distribution networks to fulfil growing power demands, reduce electricity prices and minimise greenhouse gas emissions. The penetration of these sources may cause reliability and security issues in the power system due to the intermittent nature of their power generation in addition to variable power demand. These issues become more prominent with the further integration of solar PV panels on rooftops, leading to a restriction on PV penetration. The challenges can be minimised in a number of ways, including scheduling flexible loads (electric vehicles), employing energy storage systems and introducing smart electricity prices. It is crucial that the technical aspects of such resources are critically analysed to harness the maximum benefits. In addition, the intelligent use of resources can facilitate further penetration of renewable energy sources while maintaining a network’s security with minimum operating costs. It is obvious that there should be a trade-off between cost and resource utilisation, and thus different optimisation methods and operational research concepts should come forward. This Special Issue will focus on the development of optimisation algorithms and problem formulations to facilitate the high penetration of renewable energy sources, such as solar PV panels, wind power generation, hydropower and biomass energy.

Dr. Md Alamgir Hossain
Dr. Ripon Kumar Chakrabortty
Prof. Stefano Squartini
Guest Editors

Manuscript Submission Information

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Keywords

  • optimal sizing of energy storage systems
  • scheduling resources
  • real-time energy management
  • demand-side management
  • EV planning and scheduling
  • stochastic optimisation algorithms
  • meta-heuristic optimisation algorithms
  • optimal power flow problems
  • multi-objective optimisation algorithms
  • energy storage systems
  • microgrids
  • smart cities
  • optimisation problems
  • real-time electricity prices.

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Published Papers (10 papers)

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Research

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29 pages, 4259 KiB  
Article
Estimation of Solar Radiation on a PV Panel Surface with an Optimal Tilt Angle Using Electric Charged Particles Optimization
by Muhammad Saud Khan, Makbul A. M. Ramli, Hatem Faiz Sindi, Taufal Hidayat and Houssem R. E. H. Bouchekara
Electronics 2022, 11(13), 2056; https://doi.org/10.3390/electronics11132056 - 30 Jun 2022
Cited by 2 | Viewed by 4184
Abstract
Solar energy is a promising renewable energy source that can fulfill the world’s current and future energy needs. The angle at which a photovoltaic (PV) panel faces the horizon determines the incidence of solar radiation. The incident solar radiation on PV panels could [...] Read more.
Solar energy is a promising renewable energy source that can fulfill the world’s current and future energy needs. The angle at which a photovoltaic (PV) panel faces the horizon determines the incidence of solar radiation. The incident solar radiation on PV panels could be optimized by adjusting their tilt angles and increasing the power output of the PV array. In this study, solar energy model-based research was conducted in the Saudi Arabian cities of Dhahran and Makkah. This study investigated the performance of a 1 kW monocrystalline silicon PV array in these cities. Analyzing the optimal tilt angle for efficiency and performance improvement of the PV panel is challenging. The optimal tilt angle is determined by combining the data of the Sun’s diffuse, direct radiation and the global horizontal Sun radiation. This research examined the four empirical models by applying the electric charged particle optimization (ECPO) algorithm to estimate the solar radiation on sloped surfaces. The model’s results were compared to the global horizontal solar radiation based on the daily mean solar radiation value in these cities. The Hay–Davies–Klucher–Reindel model presented the maximum amount of tilted surface solar radiation in the year and at different periods. In contrast, the Badescu model exhibited the weakest results of all the isotropic and anisotropic models. Finally, using the ECPO algorithm, all models indicated that tilted surfaces (IT) received more solar radiation than horizontal surfaces (Ig). Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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19 pages, 3622 KiB  
Article
The Possibility of Enhanced Power Transfer in a Multi-Terminal Power System through Simultaneous AC–DC Power Transmission
by Shaista Parveen, Salman Hameed, Hafizur Rahman, Khaliqur Rahman, Mohd Tariq, Basem Alamri and Akbar Ahmad
Electronics 2022, 11(1), 108; https://doi.org/10.3390/electronics11010108 - 30 Dec 2021
Cited by 4 | Viewed by 2310
Abstract
The feasibility of power transfer enhancement, through simultaneous AC–DC power transmission in a two-terminal transmission network, has been proposed earlier by the authors, and the concept is well established. To meet the increase in demand for electricity, a new technique is proposed in [...] Read more.
The feasibility of power transfer enhancement, through simultaneous AC–DC power transmission in a two-terminal transmission network, has been proposed earlier by the authors, and the concept is well established. To meet the increase in demand for electricity, a new technique is proposed in this article to increase the use of existing transmission lines in addition to independent control of AC and DC power flow. This paper extends the concept to a three-terminal transmission network by considering a power tapping from the middle of the line. DC is also superimposed in the already existing three-terminal AC transmission system. In the proposed topology, a multi-terminal simultaneous AC–DC system is used, which is integrated with a zig-zag transformer and more than two voltage source converter (VSC) stations. Each terminal may represent an area of the power system. Anyone/two-terminal(s) may act as sending end, whereas the remaining two/one terminal(s) may act as receiving end. Power can flow in either direction through each segment of the transmission system. At sending end, VSC converts a part of AC to DC and injects it into the neutral of the zig-zag transformer. On receiving terminal, DC power is tapped from neutral of zig-zag transformer and fed to VSC for conversion back to AC. The concept is verified in the digital simulation software PSCAD/EMTDC. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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36 pages, 3252 KiB  
Article
Multi-Household Energy Management in a Smart Neighborhood in the Presence of Uncertainties and Electric Vehicles
by Luca Serafini, Emanuele Principi, Susanna Spinsante and Stefano Squartini
Electronics 2021, 10(24), 3186; https://doi.org/10.3390/electronics10243186 - 20 Dec 2021
Cited by 4 | Viewed by 3134
Abstract
The pathway toward the reduction of greenhouse gas emissions is dependent upon increasing Renewable Energy Sources (RESs), demand response, and electrification of public and private transportation. Energy management techniques are necessary to coordinate the operation in this complex scenario, and in recent years [...] Read more.
The pathway toward the reduction of greenhouse gas emissions is dependent upon increasing Renewable Energy Sources (RESs), demand response, and electrification of public and private transportation. Energy management techniques are necessary to coordinate the operation in this complex scenario, and in recent years several works have appeared in the literature on this topic. This paper presents a study on multi-household energy management for Smart Neighborhoods integrating RESs and electric vehicles participating in Vehicle-to-Home (V2H) and Vehicle-to-Neighborhood (V2N) programs. The Smart Neighborhood comprises multiple households, a parking lot with public charging stations, and an aggregator that coordinates energy transactions using a Multi-Household Energy Manager (MH-EM). The MH-EM jointly maximizes the profits of the aggregator and the households by using the augmented ϵ-constraint approach. The generated Pareto optimal solutions allow for different decision policies to balance the aggregator’s and households’ profits, prioritizing one of them or the RES energy usage within the Smart Neighborhood. The experiments have been conducted over an entire year considering uncertainties related to the energy price, electric vehicles usage, energy production of RESs, and energy demand of the households. The results show that the MH-EM optimizes the Smart Neighborhood operation and that the solution that maximizes the RES energy usage provides the greatest benefits also in terms of peak-shaving and valley-filling capability of the energy demand. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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28 pages, 7357 KiB  
Article
Forecasting Daily Electricity Price by Hybrid Model of Fractional Wavelet Transform, Feature Selection, Support Vector Machine and Optimization Algorithm
by Rahmad Syah, Afshin Davarpanah, Marischa Elveny, Ashish Kumar Karmaker, Mahyuddin K. M. Nasution and Md. Alamgir Hossain
Electronics 2021, 10(18), 2214; https://doi.org/10.3390/electronics10182214 - 9 Sep 2021
Cited by 9 | Viewed by 2590
Abstract
This paper proposes a novel hybrid forecasting model with three main parts to accurately forecast daily electricity prices. In the first part, where data are divided into high- and low-frequency data using the fractional wavelet transform, the best data with the highest relevancy [...] Read more.
This paper proposes a novel hybrid forecasting model with three main parts to accurately forecast daily electricity prices. In the first part, where data are divided into high- and low-frequency data using the fractional wavelet transform, the best data with the highest relevancy are selected, using a feature selection algorithm. The second part is based on a nonlinear support vector network and auto-regressive integrated moving average (ARIMA) method for better training the previous values of electricity prices. The third part optimally adjusts the proposed support vector machine parameters with an error-base objective function, using the improved grey wolf and particle swarm optimization. The proposed method is applied to forecast electricity markets, and the results obtained are analyzed with the help of the criteria based on the forecast errors. The results demonstrate the high accuracy in the MAPE index of forecasting the electricity price, which is about 91% as compared to other forecasting methods. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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35 pages, 12045 KiB  
Article
Chaos Induced Coyote Algorithm (CICA) for Extracting the Parameters in a Single, Double, and Three Diode Model of a Mono-Crystalline, Polycrystalline, and a Thin-Film Solar PV Cell
by Shoeb Ahmad Khan, Shafiq Ahmad, Adil Sarwar, Mohd Tariq, Javed Ahmad, Mohammed Asim, Ahmed T. Soliman and Md. Alamgir Hossain
Electronics 2021, 10(17), 2094; https://doi.org/10.3390/electronics10172094 - 29 Aug 2021
Cited by 7 | Viewed by 2927
Abstract
The design of a solar PV system and its performance evaluation is an important aspect before going for a mass-scale installation and integration with the grid. The parameter evaluation of a solar PV model helps in accurate modeling and consequently efficient designing of [...] Read more.
The design of a solar PV system and its performance evaluation is an important aspect before going for a mass-scale installation and integration with the grid. The parameter evaluation of a solar PV model helps in accurate modeling and consequently efficient designing of the system. The parameters appear in the mathematical equations of the solar PV cell. A Chaos Induced Coyote Algorithm (CICA) to obtain the parameters in a single, double, and three diode model of a mono-crystalline, polycrystalline, and a thin-film solar PV cell has been proposed in this work. The Chaos Induced Coyote Algorithm for extracting the parameters incorporates the advantages of the conventional Coyote Algorithm by employing only two control parameters, making it easier to include the unique strategy that balances the exploration and exploitation in the search space. A comparison of the Chaos Induced Coyote Algorithm with some recently proposed solar photovoltaic cell parameter extraction algorithms has been presented. Analysis shows superior curve fitting and lesser Root Mean Square Error with the Chaos Induced Coyote Algorithm compared to other algorithms in a practical solar photovoltaic cell. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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16 pages, 1322 KiB  
Article
Comprehensive Survey of Various Energy Storage Technology Used in Hybrid Energy
by Ahmed Riyaz, Pradip Kumar Sadhu, Atif Iqbal and Basem Alamri
Electronics 2021, 10(16), 2037; https://doi.org/10.3390/electronics10162037 - 23 Aug 2021
Cited by 6 | Viewed by 2748
Abstract
Various power generation technologies, such as wind turbines and solar power plants, have been increasingly installed in renewable energy projects as a result of rising demand and ongoing efforts by global researchers to mitigate environmental effects. The sole source of energy for such [...] Read more.
Various power generation technologies, such as wind turbines and solar power plants, have been increasingly installed in renewable energy projects as a result of rising demand and ongoing efforts by global researchers to mitigate environmental effects. The sole source of energy for such generation is nature. The incorporation of the green unit into the power grid also results in volatility. The stabilization of frequencies is critical and depends on the balance of supply and demand. An efficient monitoring scheme called Load Frequency Monitoring (LFM) is introduced to reduce the frequency deviation from its natural state. Specific energy storage systems may be considered to improve the efficiency of the control system. The storage system contributes to the load rate, peak rushing, black start support, etc., in addition to high energy and rapid responsive features. A detailed study of different power storage systems, their current business scenario, and the application of LFM facilities, as well as their analysis and disturbance, is presented in this paper. According to the literature analysis, the current approaches can be divided into two categories: grid and load scale structures. This article also distinguishes between the organized aggregate system and the uncoordinated system control scheme, both of which have advantages and disadvantages in terms of technology. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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21 pages, 472 KiB  
Article
Simultaneous Minimization of Energy Losses and Greenhouse Gas Emissions in AC Distribution Networks Using BESS
by Federico Molina-Martin, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Jesus C. Hernández and Carlos A. Ramírez-Vanegas
Electronics 2021, 10(9), 1002; https://doi.org/10.3390/electronics10091002 - 22 Apr 2021
Cited by 27 | Viewed by 3015
Abstract
The problem of the optimal operation of battery energy storage systems (BESSs) in AC grids is addressed in this paper from the point of view of multi-objective optimization. A nonlinear programming (NLP) model is presented to minimize the total emissions of contaminant gasses [...] Read more.
The problem of the optimal operation of battery energy storage systems (BESSs) in AC grids is addressed in this paper from the point of view of multi-objective optimization. A nonlinear programming (NLP) model is presented to minimize the total emissions of contaminant gasses to the atmosphere and costs of daily energy losses simultaneously, considering the AC grid complete model. The BESSs are modeled with their linear relation between the state-of-charge and the active power injection/absorption. The Pareto front for the multi-objective optimization NLP model is reached through the general algebraic modeling system, i.e., GAMS, implementing the pondered optimization approach using weighting factors for each objective function. Numerical results in the IEEE 33-bus and IEEE 69-node test feeders demonstrate the multi-objective nature of this optimization problem and the multiple possibilities that allow the grid operators to carry out an efficient operation of their distribution networks when BESS and renewable energy resources are introduced. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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30 pages, 18202 KiB  
Article
Economic and Ecological Design of Hybrid Renewable Energy Systems Based on a Developed IWO/BSA Algorithm
by Mohammed Kharrich, Salah Kamel, Rachid Ellaia, Mohammed Akherraz, Ali S. Alghamdi, Mamdouh Abdel-Akher, Ahmad Eid and Mohamed I. Mosaad
Electronics 2021, 10(6), 687; https://doi.org/10.3390/electronics10060687 - 15 Mar 2021
Cited by 19 | Viewed by 3096
Abstract
In this paper, an optimal design of a microgrid including four houses in Dakhla city (Morocco) is proposed. To make this study comprehensive and applicable to any hybrid system, each house has a different configuration of renewable energies. The configurations of these four [...] Read more.
In this paper, an optimal design of a microgrid including four houses in Dakhla city (Morocco) is proposed. To make this study comprehensive and applicable to any hybrid system, each house has a different configuration of renewable energies. The configurations of these four houses are PV/wind turbine (WT)/biomass/battery, PV/biomass, PV/diesel/battery, and WT/diesel/battery systems. The comparison factor among these configurations is the cost of energy (COE), comparative index, where the load is different in the four houses. Otherwise, the main objective function is the minimization of the net present cost (NPC), subject to several operating constraints, the power loss, the power generated by the renewable sources (renewable fraction), and the availability. This objective function is achieved using a developed optimization algorithm. The main contribution of this paper is to propose and apply a new optimization technique for the optimal design of a microgrid considering different economic and ecological aspects. The developed optimization algorithm is based on the hybridization of two metaheuristic algorithms, the invasive weed optimization (IWO) and backtracking search algorithm (BSA), with the aim of collecting the advantages of both. The proposed hybrid optimization algorithm (IWO/BSA) is compared with the original two optimization methods (IWO and BSA) as well as other well-known optimization methods. The results indicate that PV/biomass and PV/diesel/battery systems have the best energy cost using the proposed IWO/BSA algorithm with 0.1184 $/kWh and 0.1354 $/kWh, respectively. The best system based on its LCOE factor is the PV/biomass which represents an NPC of 124,689 $, the size of this system is 349.55 m2 of PV area and the capacity of the biomass is 18.99 ton/year. The PV/diesel/battery option has also good results, with a system NPC of 142,233 $, the size of this system is about 391.39 m2 of PV area, rated power of diesel generator about 0.55 kW, and a battery capacity of 12.97 kWh. Otherwise, the proposed IWO/BSA has the best convergence in all cases. It is observed that the wind turbine generates more dumped power, and the PV system is highly suitable for the studied area. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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21 pages, 7736 KiB  
Article
High-Level Renewable Energy Integrated System Frequency Control with SMES-Based Optimized Fractional Order Controller
by Md. Shafiul Alam, Majed A. Alotaibi, Md Ahsanul Alam, Md. Alamgir Hossain, Md Shafiullah, Fahad Saleh Al-Ismail, Md. Mamun Ur Rashid and Mohammad A. Abido
Electronics 2021, 10(4), 511; https://doi.org/10.3390/electronics10040511 - 22 Feb 2021
Cited by 20 | Viewed by 3259
Abstract
The high-level penetration of renewable energy sources (RESs) is the main reason for shifting the conventional centralized power system control paradigm into distributed power system control. This massive integration of RESs faces two main problems: complex controller structure and reduced inertia. Since the [...] Read more.
The high-level penetration of renewable energy sources (RESs) is the main reason for shifting the conventional centralized power system control paradigm into distributed power system control. This massive integration of RESs faces two main problems: complex controller structure and reduced inertia. Since the system frequency stability is directly linked to the system’s total inertia, the renewable integrated system frequency control is badly affected. Thus, a fractional order controller (FOC)-based superconducting magnetic energy storage (SMES) is proposed in this work. The detailed modeling of SMES, FOC, wind, and solar systems, along with the power network, is introduced to facilitate analysis. The FOC-based SMES virtually augments the inertia to stabilize the system frequency in generation and load mismatches. Since the tuning of FOC and SMES controller parameters is challenging due to nonlinearities, the whale optimization algorithm (WOA) is used to optimize the parameters. The optimized FOC-based SMES is tested under fluctuating wind and solar powers. The extensive simulations are carried out using MATLAB Simulink environment considering different scenarios, such as light and high load profile variations, multiple load profile variations, and reduced system inertia. It is observed that the proposed FOC-based SMES improves several performance indices, such as settling time, overshoot, undershoot compared to the conventional technique. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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Review

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29 pages, 4359 KiB  
Review
Electric Power Network Interconnection: A Review on Current Status, Future Prospects and Research Direction
by Imdadullah, Basem Alamri, Md. Alamgir Hossain and M. S. Jamil Asghar
Electronics 2021, 10(17), 2179; https://doi.org/10.3390/electronics10172179 - 6 Sep 2021
Cited by 34 | Viewed by 9109
Abstract
An interconnection of electric power networks enables decarbonization of the electricity system by harnessing and sharing large amounts of renewable energy. The highest potential renewable energy areas are often far from load centers, integrated through long-distance transmission interconnections. The transmission interconnection mitigates the [...] Read more.
An interconnection of electric power networks enables decarbonization of the electricity system by harnessing and sharing large amounts of renewable energy. The highest potential renewable energy areas are often far from load centers, integrated through long-distance transmission interconnections. The transmission interconnection mitigates the variability of renewable energy sources by importing and exporting electricity between neighbouring regions. This paper presents an overview of regional and global energy consumption trends by use of fuel. A large power grid interconnection, including renewable energy and its integration into the utility grid, and globally existing large power grid interconnections are also presented. The technologies used for power grid interconnections include HVAC, HVDC (including LCC, VSC comprising of MMC-VSC, HVDC light), VFT, and newly proposed FASAL are discussed with their potential projects. Future trends of grid interconnection, including clean energy initiatives and developments, UHV AC and DC transmission systems, and smart grid developments, are presented in detail. A review of regional and global initiatives in the context of a sustainable future by implementing electric energy interconnections is presented. It presents the associated challenges and benefits of globally interconnected power grids and intercontinental interconnectors. Finally, in this paper, research directions in clean and sustainable energy, smart grid, UHV transmission systems that facilitate the global future grid interconnection goal are addressed. Full article
(This article belongs to the Special Issue Advanced Optimization Algorithms for High Penetration of Renewable Energy Sources)
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