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Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

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A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 43588

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Prof. Dr. Nicu Bizon

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Faculty of Electronics, Communication and Computers, University of Pitesti, 110040 Pitesti, Romania
Interests: electrical engineering; power electronics; power converters; inverters; renewable energy; energy efficiency; energy storage; fuel cell; hybrid power systems; control; optimization; MATLAB simulation
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Dear Colleagues,

Generation of distributed electricity using micro- and nanogrids is an obvious opportunity to reduce CO2 emissions if hydrogen energy technology is used in addition to renewable energy potential. It is expected that these hybrid microgrids will play an important role in the implementation of the scenario of limiting global warming to 20 °C by replacing fossil fuels with renewables. Thus, to highlight the latest solutions and paradigms in hybrid microgrid, such as vehicle-to-building (V2B), vehicle-to-grid (V2G), power-following and grid-responsive strategies, and Global Optimization (GO)-based fuel economy, this Special Issue, entitled “Advanced Modeling and Research in Hybrid Microgrid Control and Optimization”, has been proposed for Mathematics MDPI, which is an international peer-reviewed open access journal covered by many databases such as WOS (SCIE Impact Factor 1.105 (2018), Q1) and SCOPUS (Elsevier). The present Special Issue aims to collect innovative solutions and experimental research supported by appropriate modeling and design, but also state-of-the-art studies, in the following topics:

Hybrid nano- and microgrids
Hybrid power systems (HPSs);
Renewable energy sources (RESs);
Fuel cell (FC) systems;
Hybrid energy storage systems (HESSs);
Energy management and optimization strategies;
Smart contracts based on IoT blockchain technology;
Cybersecurity, reliability, maintenance, resilience, and safety in operation of FC RES hybrid microgrids.

Papers received will be subject to a rigorous, but fast, peer review procedure, and the wide dissemination of research results accepted for this Special Issue is ensured. I am writing to invite you to submit your original work to this Special Issue. I look forward to receiving your outstanding research outcomes.

Prof. Dr. Nicu Bizon
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. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

Hybrid nano- and micro-grids
Hybrid power systems (HPSs)
Renewable energy sources (RESs)
Fuel cell (FC) systems
FC RES hybrid microgrids
Energy management strategies (EMSs)
Blockchain technology
Smart contracts
Hybrid energy storage systems (HESSs)
Fuel cell vehicles (FCVs)
Vehicle-to-building (V2B)
Vehicle-to-grid (V2G)
Global optimization (GO)
System modeling and design
Cybersecurity, reliability, maintenance, resilience, and safety in operation

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Published Papers (12 papers)

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Research

15 pages, 3734 KiB

Open AccessArticle

Hybrid Gravitational–Firefly Algorithm-Based Load Frequency Control for Hydrothermal Two-Area System

by Deepak Kumar Gupta, Ankit Kumar Soni, Amitkumar V. Jha, Sunil Kumar Mishra, Bhargav Appasani, Avireni Srinivasulu, Nicu Bizon and Phatiphat Thounthong

Mathematics 2021, 9(7), 712; https://doi.org/10.3390/math9070712 - 25 Mar 2021

Cited by 32 | Viewed by 2625

Abstract

The load frequency control (LFC) and tie-line power are the key deciding factors to evaluate the performance of a multiarea power system. In this paper, the performance analysis of a two-area power system is presented. This analysis is based on two performance metrics: LFC and tie-line power. The power system consists of a thermal plant generation system and a hydro plant generation system. The performance is evaluated by designing a proportional plus integral (PI) controller. The hybrid gravitational search with firefly algorithm (hGFA) has been devised to achieve proper tuning of the controller parameter. The designed algorithm involves integral time absolute error (ITAE) as an objective function. For two-area hydrothermal power systems, the load frequency and tie-line power are correlated with the system generation capacity and the load. Any deviation in the generation and in the load capacity causes variations in the load frequencies, as well as in the tie-line power. Variations from the nominal value may hamper the operation of the power system with adverse consequences. Hence, performance of the hydrothermal power system is analyzed using the simulations based on the step load change. To elucidate the efficacy of the hGFA, the performance is compared with some of the well-known optimization techniques, namely, particle swarm optimization (PSO), genetic algorithm (GA), gravitational search algorithm (GSA) and the firefly algorithm (FA). Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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29 pages, 26983 KiB

Open AccessArticle

A Simple and Safe Strategy for Improving the Fuel Economy of a Fuel Cell Vehicle

by Nicu Bizon and Phatiphat Thounthong

Mathematics 2021, 9(6), 604; https://doi.org/10.3390/math9060604 - 11 Mar 2021

Cited by 3 | Viewed by 2384

Abstract

A new real-time strategy is proposed in this article to optimize the hydrogen utilization of a fuel cell vehicle, by switching the control references of fueling regulators, based on load-following. The advantages of this strategy are discussed and compared, with advanced strategies that also use the aforementioned load-following mode regulator of fueling controllers, but in the entire loading range, respectively, with a benchmark strategy utilizing the static feed-forward control of fueling controllers. Additionally, the advantages of energy-storage function in a charge-sustained mode, such as a longer service life and reduced size due to the implementation of the proposed switching strategy, are presented for the dynamic profiles across the entire load range. The optimization function was designed to improve the fuel economy by adding to the total power of the fuel utilization efficiency (in a weighted way). The proposed optimization loop will seek the reference value to control the fueling regulator in real-time, which is not regulated by a load-following approach. The best switching threshold between the high and low loading scales were obtained using a sensitivity analysis carried out for both fixed and dynamic loads. The results obtained were promising—(1) the fuel economy was two-times higher than the advanced strategies mentioned above; and (2) the total fuel consumption was 13% lower than the static feed-forward strategy. This study opens new research directions for fuel cell vehicles, such as for obtaining the best fuel economy or estimating fuel consumption up to the first refueling station on the planned road. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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20 pages, 5261 KiB

Open AccessArticle

Impact of Renewable Energy Sources into Multi Area Multi-Source Load Frequency Control of Interrelated Power System

by Krishan Arora, Ashok Kumar, Vikram Kumar Kamboj, Deepak Prashar, Bhanu Shrestha and Gyanendra Prasad Joshi

Mathematics 2021, 9(2), 186; https://doi.org/10.3390/math9020186 - 18 Jan 2021

Cited by 41 | Viewed by 2710

Abstract

There is an increasing concentration in the influences of nonconventional power sources on power system process and management, as the application of these sources upsurges worldwide. Renewable energy technologies are one of the best technologies for generating electrical power with zero fuel cost, a clean environment, and are available almost throughout the year. Some of the widespread renewable energy sources are tidal energy, geothermal energy, wind energy, and solar energy. Among many renewable energy sources, wind and solar energy sources are more popular because they are easy to install and operate. Due to their high flexibility, wind and solar power generation units are easily integrated with conventional power generation systems. Traditional generating units primarily use synchronous generators that enable them to ensure the process during significant transient errors. If massive wind generation is faltered due to error, it may harm the power system’s operation and lead to the load frequency control issue. This work proposes binary moth flame optimizer (MFO) variants to mitigate the frequency constraint issue. Two different binary variants are implemented for improving the performance of MFO for discrete optimization problems. The proposed model was evaluated and compared with existing algorithms in terms of standard testing benchmarks and showed improved results in terms of average and standard deviation. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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18 pages, 9358 KiB

Open AccessArticle

Grid Frequency and Amplitude Control Using DFIG Wind Turbines in a Smart Grid

by José Antonio Cortajarena, Oscar Barambones, Patxi Alkorta and Jon Cortajarena

Mathematics 2021, 9(2), 143; https://doi.org/10.3390/math9020143 - 11 Jan 2021

Cited by 10 | Viewed by 3068

Abstract

Wind-generated energy is a fast-growing source of renewable energy use across the world. A dual-feed induction machine (DFIM) employed in wind generators provides active and reactive, dynamic and static energy support. In this document, the droop control system will be applied to adjust the amplitude and frequency of the grid following the guidelines established for the utility’s smart network supervisor. The wind generator will work with a maximum deloaded power curve, and depending on the reserved active power to compensate the frequency drift, the limit of the reactive power or the variation of the voltage amplitude will be explained. The aim of this paper is to show that the system presented theoretically works correctly on a real platform. The real-time experiments are presented on a test bench based on a 7.5 kW DFIG from Leroy Somer’s commercial machine that is typically used in industrial applications. A synchronous machine that emulates the wind profiles moves the shaft of the DFIG. The amplitude of the microgrid voltage at load variations is improved by regulating the reactive power of the DFIG and this is experimentally proven. The contribution of the active power with the characteristic of the droop control to the load variation is made by means of simulations. Previously, the simulations have been tested with the real system to ensure that the simulations performed faithfully reflect the real system. This is done using a platform based on a real-time interface with the DS1103 from dSPACE. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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13 pages, 828 KiB

Open AccessArticle

Enhanced IoV Security Network by Using Blockchain Governance Game

by Song-Kyoo (Amang) Kim

Mathematics 2021, 9(2), 109; https://doi.org/10.3390/math9020109 - 7 Jan 2021

Cited by 21 | Viewed by 3733

Abstract

This paper deals with the design of the secure network in an Enhanced Internet of Vehicles by using the Blockchain Governance Game (BGG). The BGG is a system model of a stochastic game to find best strategies towards preparation of preventing a network malfunction by an attacker and the paper applies this game model into the connected vehicle security. Analytically tractable results for decision-making parameters enable to predict the moment for safety operations and to deliver the optimal combination of the number of reserved nodes with the acceptance probability of backup nodes to protect a connected car. This research helps for whom considers the enhanced secure IoV architecture with the BGG within a decentralized network. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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17 pages, 10147 KiB

Open AccessArticle

Common-Ground-Type Single-Source High Step-Up Cascaded Multilevel Inverter for Transformerless PV Applications

by Hossein Khoun Jahan, Naser Vosoughi Kurdkandi, Mehdi Abapour, Kazem Zare, Seyed Hossein Hosseini, Yongheng Yang and Frede Blaabjerg

Mathematics 2020, 8(10), 1716; https://doi.org/10.3390/math8101716 - 7 Oct 2020

Cited by 5 | Viewed by 1999

Abstract

The cascaded multilevel inverter (CMI) is one type of common inverter in industrial applications. This type of inverter can be synthesized either as a symmetric configuration with several identical H-bridge (HB) cells or as an asymmetric configuration with non-identical HB cells. In photovoltaic (PV) applications with the CMI, the PV modules can be used to replace the isolated dc sources; however, this brings inter-module leakage currents. To tackle the issue, the single-source CMI is preferred. Furthermore, in a grid-tied PV system, the main constraint is the capacitive leakage current. This problem can be addressed by providing a common ground, which is shared by PV modules and the ac grid. This paper thus proposes a topology that fulfills the mentioned requirements and thus, CMI is a promising inverter with wide-ranging industrial uses, such as PV applications. The proposed CMI topology also features high boosting capability, fault current limiting, and a transformerless configuration. To demonstrate the capabilities of this CMI, simulations and experimental results are provided. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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20 pages, 3517 KiB

Open AccessArticle

Electricity Cost Optimization in Energy Storage Systems by Combining a Genetic Algorithm with Dynamic Programming

by Seung-Ju Lee and Yourim Yoon

Mathematics 2020, 8(9), 1526; https://doi.org/10.3390/math8091526 - 7 Sep 2020

Cited by 11 | Viewed by 4202

Abstract

Recently, energy storage systems (ESSs) are becoming more important as renewable and microgrid technologies advance. ESSs can act as a buffer between generation and load and enable commercial and industrial end users to reduce their electricity expenses by controlling the charge/discharge amount. In this paper, to derive efficient charge/discharge schedules of ESSs based on time-of-use pricing with renewable energy, a combination of genetic algorithm and dynamic programming is proposed. The performance of the combined method is improved by adjusting the size of the base units of dynamic programming. We show the effectiveness of the proposed method by simulating experiments with load and generation profiles of various commercial electricity consumers. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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26 pages, 2914 KiB

Open AccessArticle

Reducing the Cost of Electricity by Optimizing Real-Time Consumer Planning Using a New Genetic Algorithm-Based Strategy

by Laurentiu-Mihai Ionescu, Nicu Bizon, Alin-Gheorghita Mazare and Nadia Belu

Mathematics 2020, 8(7), 1144; https://doi.org/10.3390/math8071144 - 13 Jul 2020

Cited by 12 | Viewed by 3372

Abstract

To ensure the use of energy produced from renewable energy sources, this paper presents a method for consumer planning in the consumer–producer–distributor structure. The proposed planning method is based on the genetic algorithm approach, which solves a cost minimization problem by considering several input parameters. These input parameters are: the consumption for each unit, the time interval in which the unit operates, the maximum value of the electricity produced from renewable sources, and the distribution of energy production per unit of time. A consumer can use the equipment without any planning, in which case he will consume energy supplied by a distributor or energy produced from renewable sources, if it is available at the time he operates the equipment. A consumer who plans his operating interval can use more energy from renewable sources, because the planning is done in the time interval in which the energy produced from renewable sources is available. The effect is that the total cost of energy to the consumer without any planning will be higher than the cost of energy to the consumer with planning, because the energy produced from renewable sources is cheaper than that provided from conventional sources. To be validated, the proposed approach was run on a simulator, and then tested in two real-world case studies targeting domestic and industrial consumers. In both situations, the solution proposed led to a reduction in the total cost of electricity of up to 25%. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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25 pages, 1276 KiB

Open AccessArticle

Hybrid LQR-PI Control for Microgrids under Unbalanced Linear and Nonlinear Loads

by Gerardo Humberto Valencia-Rivera, Luis Ramon Merchan-Villalba, Guillermo Tapia-Tinoco, Jose Merced Lozano-Garcia, Mario Alberto Ibarra-Manzano and Juan Gabriel Avina-Cervantes

Mathematics 2020, 8(7), 1096; https://doi.org/10.3390/math8071096 - 4 Jul 2020

Cited by 10 | Viewed by 4975

Abstract

A hybrid Linear Quadratic Regulator (LQR) and Proportional-Integral (PI) control for a MicroGrid (MG) under unbalanced linear and nonlinear loads was presented and evaluated in this paper. The designed control strategy incorporates the microgrid behavior, low-cost LQR, and error reduction in the stationary state by the PI control, to reduce the overall energetic cost of the classical PI control applied to MGs. A Genetic Algorithm (GA) calculates the parameters of LQR with high-accuracy fitness function to obtain the optimal controller parameters as settling time and overshoot. The gain values of the classical PI controller were determined through the improved LQR values and geometrical root locus. When MG operates in the grid-tied mode under unbalanced conditions, the controller performance of the Current Source Inverter (CSI) of the MG is considerably affected. Consequently, the CSI operates in a negative-sequence mode to compensate for unbalanced current at the Point of Common Coupling (PCC) between the MG and the utility grid. The study cases involved the reduction of the negative-sequence percentage in the current at the PCC, mitigation of harmonics in the current signal injected by the MG, and close related power quality issues. All these cases have been analyzed by implementing an MG connected at the PCC of a low-voltage distribution network. A numerical model of the MG in Matlab/Simulink was implemented to verify the performance of the designed LQR-PI control to mitigate or overcome the power quality concerns. The extensive simulations have permitted verifying the robustness and effectiveness of the proposed strategy. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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28 pages, 9299 KiB

Open AccessArticle

Multi-Stack Lifetime Improvement through Adapted Power Electronic Architecture in a Fuel Cell Hybrid System

by Milad Bahrami, Jean-Philippe Martin, Gaël Maranzana, Serge Pierfederici, Mathieu Weber, Farid Meibody-Tabar and Majid Zandi

Mathematics 2020, 8(5), 739; https://doi.org/10.3390/math8050739 - 7 May 2020

Cited by 23 | Viewed by 3641

Abstract

To deal with the intermittency of renewable energy resources, hydrogen as an energy carrier is a good solution. The Polymer Electrolyte Membrane Fuel Cell (PEMFC) as a device that can directly convert hydrogen energy to electricity is an important part of this solution. However, durability and cost are two hurdles that must be overcome to enable the mass deployment of the technology. In this paper, a management system is proposed for the fuel cells that can cope with the durability issue by a suitable distribution of electrical power between cell groups. The proposed power electronics architecture is studied in this paper. A dynamical average model is developed for the proposed system. The validation of the model is verified by simulation and experimental results. Then, this model is used to prove the stability and robustness of the control method. Finally, the energy management system is assessed experimentally in three different conditions. The experimental results validate the effectiveness of the proposed topology for developing a management system with which the instability of cells can be confronted. The experimental results verify that the system can supply the load profile even during the degradation mode of one stack and while trying to cure it. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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18 pages, 6964 KiB

Open AccessArticle

Differential Flatness-Based Cascade Energy/Current Control of Battery/Supercapacitor Hybrid Source for Modern e–Vehicle Applications

by Burin Yodwong, Phatiphat Thounthong, Damien Guilbert and Nicu Bizon

Mathematics 2020, 8(5), 704; https://doi.org/10.3390/math8050704 - 2 May 2020

Cited by 24 | Viewed by 4017

Abstract

This article proposes a new control law for an embedded DC distributed network supplied by a supercapacitor module (as a supplementary source) and a battery module (as the main generator) for transportation applications. A novel control algorithm based on the nonlinear differential flatness approach is studied and implemented in the laboratory. Using the differential flatness theory, straightforward solutions to nonlinear system stability problems and energy management have been developed. To evaluate the performance of the studied control technique, a hardware power electronics system is designed and implemented with a fully digital calculation (real-time system) realized with a MicroLabBox dSPACE platform (dual-core processor and FPGA). Obtained test bench results with a small scale prototype platform (a supercapacitor module of 160 V, 6 F and a battery module of 120 V, 40 Ah) corroborate the excellent control structure during drive cycles: steady-state and dynamics. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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20 pages, 1431 KiB

Open AccessArticle

An Optimization Model for the Temporary Locations of Mobile Charging Stations

by Maria-Simona Răboacă, Irina Băncescu, Vasile Preda and Nicu Bizon

Mathematics 2020, 8(3), 453; https://doi.org/10.3390/math8030453 - 21 Mar 2020

Cited by 41 | Viewed by 5261

Abstract

A possible solution with which to alleviate the range anxiety of electric vehicle (EV) drivers could be a mobile charging station which moves in different places to charge EVs, having a charging time of even half an hour. A problem that arises is the impossibility of charging in any location due to heavy traffic or limited space constraints. This paper proposes a new operational mode for the mobile charging station through temporarily stationing it at different places for certain amounts of time. A mathematical model, in the form of an optimization problem, is built by modeling the mobile charging station as a queuing process, the goal of the problem being to place a minimum number of temporary service centers (which may have one or more mobile charging stations) to minimize operating costs and the charger capacity of the mobile charging station so that the service offered is efficient. The temporary locations obtained are in areas with no or few fixed charging stations, making the mobile station infrastructure complementary to the fixed charging station infrastructure. The temporary location operational mode, compared to current moving operational mode, is more efficient, having a small miss ratio, short mean response time and short mean queuing time. Full article

(This article belongs to the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization)

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