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The growth of distributed renewable energy in the electrical grid presents challenges to its stability and quality. To address this at the local level, flexibility energy strategies emerge as an innovative technique. However, managing these strategies in residential areas becomes complex due to the unique characteristics of each prosumer. A major challenge lies in managing communication among diverse devices with different protocols. To address these issues, a comprehensive framework is designed and implemented to facilitate prosumers' integration in flexibility strategies, addressing communication at various levels. The effectiveness of the proposed framework is demonstrated through its implementation in a real smart home environment with diverse devices. The framework enables seamless integration and communication between IoT devices and IEC 61,850-compliant power devices. This research presents a novel approach to address the challenges of managing flexibility strategies in residential areas, providing a practical solution for prosumers to actively participate in optimizing energy consumption and enhancing the stability and quality of the electricity system amidst the growing integration of distributed renewable energy.

© 2023 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0, This paper proposes a cooperative strategy for the flexible integration of stand-alone AC microgrids using an intermediate multiterminal DC link based on voltage source converters. The strategy manages cooperative power exchange between microgrids through a knowledge-based fuzzy inference system that relies on the current operating conditions of the microgrids. By determining the amount of power to be exchanged between microgrids to improve global reliability, the cooperative strategy achieves an overall reduction in load loss and an increase in the use of available renewable energy. Additionally, the multiterminal DC link provides complete isolation between microgrids, allowing for independent AC bus voltage regulation and management. The effectiveness and expandability of the proposed cooperative energy exchange strategy for enhancing the overall operation of multiple integrated microgrids have been fully verified by simulation and experimental validation., Peer Reviewed, Postprint (published version)

This paper aims to design a robust internal model-based voltage control (RIMVC) scheme for DC Microgrids (DCMGs) in the presence of unknown external disturbances. Maintaining voltage reference tracking under measurement noise, delays, model parameter uncertainties and unknown external disturbances while the load changes simultaneously is a severe challenge for the DC–DC converters in DCMGs. By developing a modified internal model-based voltage control for DC–DC converters, this work proposes a plug-and-play (PnP) robust voltage control scheme to address the abovementioned challenge. The proposed control method has a cascade structure. In the first step, a modified IMC control is designed to achieve desired tracking performance for a nominal dynamical system. In the next step, the output feedback H∞ control part is added to improve the performance robustness under external disturbances and parameter uncertainties. The efficiency of the proposed control scheme is evaluated using a real-time MATLAB/Simulink testbed, taking into account unknown internal and external disturbances under various rapid voltage reference changes, model parameter uncertainties, constant power loads, system delays and normal load profile changes in multiple case study scenarios., QC 20230823

The Second Order Generalized Integrator–Frequency Locked Loop (SOGI-FLL) is a widely used and popular adaptive filter for estimating grid voltage parameters with minimal computational burden. However, it is vulnerable to voltage sag and swell faults, especially voltage sags that can significantly distort the estimated frequency. In this paper, we propose an error-and-hold algorithm for the SOGI-FLL that can quickly detect faults and hold the estimated frequency during these perturbations. The algorithm uses the absolute value of the SOGI's error, its average, and the average of the FLL's estimated frequency to operate. It reduces induced errors in the SOGI-FLL's quadrature outputs, improves the FLL's transient response, holds the estimated frequency, and restores the phase to its previous value before the fault. The proposed algorithm is a straightforward and low computational burden algorithm that can be executed on a low-cost processor. We validate the effectiveness of the proposed error-and-hold algorithm through simulations and experimental results., Peer Reviewed, Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant, Postprint (published version)

Pulsed power load (PPL) is a special load type in shipboard microgrids (SMGs), which consists of the generation module, energy storage system, and various types of loads. Having a reliable power supply to shipboard loads is a challenge as the SMG operates in islanded mode in most cases. Particularly, the PPLs require high transient power transfer with fast dynamics and strong robustness. Conventional solution to supply for the PPL is based on proportional-integral (PI) control, which can be used by linearizing the system around the equilibrium operation point. However, for a pulsed power supply (PPS) system, the load demand drastically changes in a short time, usually in millisecond level, making the operating point changes when the pulsed power is triggered or terminated. To supply the PPL with fast dynamics and robustness, an improved PPS control method is presented in this paper. By adopting a nonlinear sliding mode control (SMC) method, fast voltage regulation and robust pulse power tracking can be achieved. In the PPS, the PPL power demand is divided into two terms: one is the average power that is supplied by the SMG and the other is the fast pulsed power that is supplied by the storage capacitor. The size and cost of the storage capacitor are reduced as it is intentionally driven to a deep discharge. The PPS system configuration and coordination principle, SMC controllers, and sizing of passive elements in the PPS are analyzed in detail. The effectiveness of the presented PPS is verified by simulation results., Peer Reviewed, Postprint (published version)

Microgrid (MG) is one of the practical and best concepts to provide energy access to rural communities, where electric grid extension is not techno-economically feasible. Since the trend of load consumption is not uniform with a low load factor in a rural area, the required rating of the system becomes very high. Similarly, the generation is fixed for these MGs, whereas the load increases continuously over time. Such a system faces supply deficit issues triggering a high number of interruptions that may cause frequent blackouts. Hence, rolling blackout and load clipping techniques are preferred during the peak load period in most of the rural MGs. These issues lead to an unreliable power supply and low satisfaction level of the user. This paper presents the load prioritization technique to guarantee the continuous supply for the essential loads within the rural community. A day-ahead energy allocation technique is mathematically formulated and optimized to maximize the total hours of energy served. This technique maximized the hours of energy served to the load with higher priority followed by the load with lower priorities. From this study, it is found that the proposed strategy helps to improve the hours of energy served in the overall system, by improving the state of charge (SoC) level of the battery system. The result shows that the user satisfaction level has been improved by 5% through 100% of continuity for the essential loads.

The trend toward Microgrids (MGs) is significantly increasing by employing Distributed Generators (DGs) which leads to new challenges, especially in the fault detection. This paper proposes an algorithm based on the Total Harmonic Distortion (THD) of the grid voltages to detect the events of faults in MGs. The algorithm uses the THD together with the estimate amplitude voltages and the zero-sequence component for the detection and identification of the faults. The performance is evaluated by using MATLAB/Simulink simulations to validate the capability for detecting different fault types in the least possible time., Comment: Proc. of the Interdisciplinary Conference on Mechanics, Computers and Electrics (ICMECE 2022) 6-7 October 2022, Barcelona, Spain

The rapid growth of the distributed generators (DGs) integration into the distribution systems (DSs) creates new technical issues; conventional relay settings need to be updated depending on the network topology and operational mode as fault protection is a major challenge. This emphasizes the need for new fault protection methods to ensure secure protection and prevent undesirable tripping. Total harmonic distortion (THD) is an important indicator for assessing the quality of the grid. Here, a new protection system based on the THD of the grid voltages is proposed to address fault events in the electrical distribution network. The proposed protection system combines the THD with the estimates of the amplitude voltages and the zero-sequence component for defining an algorithm based on a finite state machine (FSM) for the detection, identification, and isolation of faults in the grid. The algorithm employs communication lines between all the protective devices (PDs) of the system to transmit tripping signals, allowing PDs to be coordinated. A second order generalized integrator (SOGI) and multiple SOGI (MSOGI) are used to obtain the THDs, estimated amplitude voltages, and zero-sequence component, which allows for fast detection with a low computational burden. The protection algorithm performance is evaluated through simulations in MATLAB/Simulink and a comparative study is developed between the proposed protection method and a differential relay (DR) protection system. The proposed method shows its capability to detect and isolate faults during different fault types with different fault resistances in different locations in the proposed network. In all the tested scenarios, the detection time of the faults has been between 7–10 ms. Moreover, this method gave the best solution as it has a higher accuracy and faster response than the conventional DR protection system., Peer Reviewed, Postprint (published version)

Altres ajuts: Acord transformatiu CRUE-CSIC, Life support systems (LSSs) are autonomous systems integrating various generation, recycling, and consumption subsystems with storage capability to maintain the balance of key system compounds. A novel hierarchical control is proposed in this paper to operate an exemplary controlled ecological LSS. The study focuses on the control of O concentration in the crew compartment, as the main consumer of a LSS, while coordinating a network of biological compartments with a variety of generation, consumption, and storage capabilities. A concentrated gas buffer tank is included in the system to demonstrate its capability to support the system operation flexibility and efficiency. Simulation analyses for changing O demand scenarios are carried to assess the proposed control architecture performance.

A novel stochastic strategy for solving the problem of optimal power management of multi-microgrid (MMG) systems is suggested in this paper. The considered objectives are minimizing the total cost and emission of the system. The suggested algorithm is applied on a MMG consisting of four microgrids (MG), each including fossil fuel-based generator units, wind turbine (WT), photovoltaic (PV) panel, battery, and local loads. The unscented transformation (UT) method is applied to deal with the inherent uncertainties of the renewable energy sources (RES) and forecasted values of the load demand and electricity price. The proposed algorithm is applied to solve the power management of a sample MMG system in both deterministic and probabilistic scenarios. It is justified through simulation results that the suggested algorithm is an efficient approach in satisfying the minimization of the cost and the environmental objective functions. When considering uncertainties, it is observed that the maximum achievable profit is about 23% less than that of the deterministic condition, while the minimum emission level increases 22%. It can be concluded that considering uncertainties has a significant effect on the economic index. Therefore, to present more accurate and realistic results it is essential to consider uncertainties in solving the optimal power management of MMG system.

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Community Microgrid offers effective energy harvesting from distributed energy resources and efficient energy consumption by employing an energy management system (EMS). Therefore, the collaborative microgrids are essentially required to apply an EMS, underlying an operative control strategy in order to provide an efficient system. An EMS is apt to optimize the operation of microgrids from several points of view. Optimal production planning, optimal demand-side management, fuel and emission constraints, the revenue of trading spinning and non-spinning reserve capacity can effectively be managed by EMS. Consequently, the importance of optimization is explicit in microgrid applications. In this paper, the most common control strategies in the microgrid community with potential pros and cons are analyzed. Moreover, a comprehensive review of single objective and multi-objective optimization methods is performed by considering the practical and technical constraints, uncertainty, and intermittency of renewable energies sources. The Pareto-optimal solution as the most popular multi-objective optimization approach is investigated for the advanced optimization algorithms. Eventually, feature selection and neural network-based clustering algorithms in order to analyze the Pareto-optimal set are introduced., This work was supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (MICINN)–Agencia Estatal de Investigación (AEI), and by the European Regional Development Funds (ERDF), a way of making Europe, under Grant PGC2018-098946-B-I00 funded by MCIN/AEI/10.13039/501100011033/., Peer Reviewed, Postprint (published version)

Modelling higher plant growth is of strategic interest for modern agriculture as well as for the development of bioregenerative life support systems for space applications, where crop growth is expected to play an essential role. The capability of constraint-based metabolic models to cope the diel dynamics of plants growth is integrated into a multilevel modelling approach including mass and energy transfer and enzyme kinetics. Lactuca sativa is used as an exemplary crop to validate, with experimental data, the approach presented as well as to design a novel model-based predictive control strategy embedding metabolic information. The proposed modelling strategy predicts with high accuracy the dynamics of gas exchange and the distribution of fluxes in the metabolic network whereas the control architecture presented can be useful to manage higher plants chambers and open new ways of merging metabolome and control algorithms.

In order to maximize the use of renewable-based distributed generators (DGs), in addition to dealing with the effects of the inherent power management uncertainties of microgrids (MGs), applying storage devices is essential in the electrical system. The main goal of this paper is to minimize the total operation cost as well as the emissions of MG energy resources, alongside the better utilization of renewable energy sources (RES) and energy storage systems. The uncertainties of wind speed, solar irradiation, market price and electrical load demand are modeled using reduced unscented transformation (RUT) method. Simulation results reveal that, as expected, by increasing the battery efficiency, the achievable minimum daily operational cost of the system is reduced. For example, with 93% battery efficiency, the operational cost equals EUR 9200, while for an efficiency of 97%, the achievable minimum daily operational cost is EUR 8900. Moreover, the proper economic/environmental performance of the suggested approach, which contributes to the possibility of selecting a compromise solution for the MG operator in accordance with technical and economic constraints, is justified.

The power calculation is an indispensable element in droop-controlled inverters because the bandwidth of the measured power has a direct impact on the controller performance. This paper proposes a fast and accurate power calculation algorithm based on the combined Second Order Generalized Integrator (SOGI) filters in stationary coordinates for a three-phase system, which takes into consideration the use of nonlinear loads. The power calculation scheme is formed by the two-stage SOGI filters that are employed for obtaining the active and reactive powers required to perform a droop-based inverter operation, respectively. From the two-stage structure, the first SOGI is used as a band-pass filter (BPF) for filtering harmonics and obtaining the fundamental current of the nonlinear load; The second SOGI is used as a low-pass filter (LPF) for extracting the DC-component, which corresponds with the average power. A small-signal model of a two droop-controlled inverters system is built to obtain the dynamical response and stability margin of the system. And compared it with the dynamical behaviour of a standard droop-control method. Next, the proposed power calculation system is designed in order to achieve the same ripple amplitude voltage as that obtained with the standard droop-control method by adjusting the bandwidth gains. Through simulation and hardware in the loop (HIL) validation, the proposed approach presents a faster and more accurate performance when sharing nonlinear loads, and also drives the inverters’ output voltage with lower distortion., Peer Reviewed, Postprint (published version)

The increasing demands of reducing fuel consumption for marine transportation have motivated the use of high fuel efficiency power plants and the development of power management systems (PMS). Current studies on shipboard PMS are mostly categorized as centralized, which are easy to be implemented and able to converge to the global optimum solutions. However, centralized techniques may suffer from the high computational burden and single-point failures. Considering the future trends of marine vessels toward zonal electrical distribution (ZED), distributed PMS are becoming an alternative choice. To achieve the ship high fuel-efficiency operation under high fluctuated propulsion loads, a real-time distributed PMS is developed in this paper that can acquire as good fuel economy as centralized PMS, but with faster computing speed. With a combination of filter-based, rule-based, and optimization-based approaches in a highly computationally efficient manner, the distributed PMS is constructed based on three layers that guarantees not only high fuel efficiency, but also sufficient energy reservation in different sailing modes and even in faulty conditions. Convergence tests and multiple case studies are conducted to prove the effectiveness of the proposed PMS in terms of fast convergence speed, improved fuel efficiency, and enhanced resilience., Peer Reviewed, Postprint (published version)

Frequency control is one important issue in autonomous operating mode of Microgrids (MGs). In stand-alone microgrids, when generation power is not enough, it is inevitable to shed some parts of the load. This paper presents a decentralized fuzzy controller for optimal load shedding in MGs. The proposed controller which is separately installed for each load center uses a hierarchical fuzzy controller approach to make the optimal decision. Three inputs of the hierarchical fuzzy controller are the power of non-critical load, the load energy not supplied and its interruption frequency. From a specific time of the past, these inputs are calculated for all load centers, and updated periodically. The non-critical part of the loads which can be shed to survive network. Each decentralized controller of the loads has a bilateral communication with the microgrid central controller to transact some information, periodically. Simulation results on a typical microgrid with several load buses showing the effectiveness of the proposed method.

A multilevel topology for photovoltaic (PV) systems with integrated energy storage (ES) is presented in this article. Both PV and ES power cells are connected in series to form a dc link, which is then connected to an H-bridge to convert the dc voltage to an ac one. The main advantage of the proposed converter compared to the cascaded-H-bridge (CHB) converter, as well as compared to the available multilevel topologies, is that fewer semiconductor devices are needed here. As the output voltage levels increase, more switches are saved, which results in a more efficient, cheaper, and smaller converter. So far, there is still no modulation strategy that is designed particularly for PV-fed multilevel converters with built-in ES. The standard modulations are impractical for such an application since they suffer from deficiencies, such as polluted output signals - thus, requiring larger output filter - and overmodulation. A modified modulation strategy for PV+ES multilevel inverters is, therefore, introduced in this article. The proposal has been simulated and experimentally validated to evaluate its effectiveness, where it has been shown that the proposed topology is not exclusively feasible, but also suffers from less conduction and switching loss, achieving higher efficiency with respect to its counterpart CHB.

Satisfying the mobile traffic demand in next generation cellular networks increases the cost of energy supply. Renewable energy sources are a promising solution to power base stations in a self-sufficient and cost-effective manner. This paper presents an optimal method for designing a photovoltaic (PV)-battery system to supply base stations in cellular networks. A systematic approach is proposed for determining the power rating of the photovoltaic generator and battery capacity from a technical and economical point of view in order to minimize investment cost as well as operational expenditure, while the power autonomy of the PV-battery system is maximized in a multi-objective optimization framework. The proposed method is applied to optimally size a photovoltaic-battery system for three cases with different availability of solar power to investigate the effect of environmental conditions. Problem-solving using the proposed approach leads to a set of solutions at different costs versus different levels of power autonomy. According to the importance of each criterion and the preference of decision-makers, one of the achieved solutions can be selected for the implementation of the photovoltaic-battery system to supply base stations in cellular networks

This letter proposes a multilevel inverter (MLI), which can be considered to be belonging to the cascaded H-bridge (CHB) family. In the proposed MLI, some of the H-bridges are connected to dc-sources, whereas most of the H-bridges are connected to only floating capacitors. A boosting circuit is integrated in the CHB, which permits charging the floating capacitors, enabling a higher voltage at the inverter's output with respect to the dc-sources total one. This boosting feature is essential in some applications, such as photovoltaic and fuel cell systems. Compared to the popular solutions in the literature, the proposal still offers a high boosting ratio with fewer employed components. A prototype of the proposed MLI has been built, and the results confirming its validity are shown in this letter. Efficiency analysis and evaluation with respect to one of the conventional solutions is also presented, where it is demonstrated that the proposal shows an improvement of 3.94% according to the European efficiency.

In order to provide Internet access to rural areas and places without a reliable economic electricity grid, self-sustainable drone-based cellular networks have recently been presented. However, the difficulties of power consumption and mission planning lead to the challenge of optimal sizing of the power supply for future cellular telecommunication networks. In order to deal with this challenge, this paper presents an optimal approach for sizing the photovoltaic (PV)-battery power supply for drone-based cellular networks in remote areas. The main objective of the suggested approach is to minimize the total cost, including the capital and operational expenditures. The suggested framework is applied to an off-grid cellular telecommunication network with drone-based base stations that are powered by PV-battery systems-based recharging sites in a rural location. The PV-battery system is optimally designed for three recharging sites with three different power consumption profiles with different peak and cumulative loads. Results show that the optimal design of the PV-battery system is dependent on geographical data, solar irradiation, and ambient temperature, which affect the output power of the PV system, as well as the power consumption profile, which affects the required number of PV panels and battery capacity.

Existing power systems are both weak and vulnerable when it comes to environmental threats, whether these occur due to natural disasters like earthquakes and hurricanes or extreme weather phenomena like torrential rains and hail. Under these circumstances, urban and rural communities are continuously evolving towards more self-balanced, self-sustainable electrical arrangements. This paper gives a brief overview of the existing energy community models, the technologies involved, and the services, along with some background in order to illustrate how these come about and what the conditions and requirements are to advance such initiatives, from both the private and the public sectors., QC 20220118

Frequency control is one important issue in autonomous operating mode of Microgrids (MGs). In stand-alone microgrids, when generation power is not enough, it is inevitable to shed some parts of the load. This paper presents a decentralized fuzzy controller for optimal load shedding in MGs. The proposed controller which is separately installed for each load center uses a hierarchical fuzzy controller approach to make the optimal decision. Three inputs of the hierarchical fuzzy controller are the power of non-critical load, the load energy not supplied and its interruption frequency. From a specific time of the past, these inputs are calculated for all load centers, and updated periodically. The non-critical part of the loads which can be shed to survive network. Each decentralized controller of the loads has a bilateral communication with the microgrid central controller to transact some information, periodically. Simulation results on a typical microgrid with several load buses showing the effectiveness of the proposed method., QC 20211117

The enhanced phase-locked loop (EPLL) is one of the most famous PLLs in single-phase applications and a versatile tool for different signal processing applications, especially for the grid synchronization of power converters. Recently, it has been proved that the EPLL has a quite narrow stable zone (compared to its unstable zone) in the positive parameter space from a small-signal point of view. This zone will be even more narrow if maintaining a minimum stability margin is required. This article aims to modify the EPLL structure to improve its stability margin, and at the same time, make it unconditionally stable in the positive parameter space from a small-signal point of view., Peer Reviewed, Postprint (author's final draft)

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., An accurate model to represent the photovoltaic modules is essential to facilitate the efficient deployment of these systems in terms of design, analysis, and monitoring considerations. In this respect, this study proposes a new approach to improve the accuracy of the widely used five-parameter single-diode model. Two new physical equations are introduced to represent the series and shunt resistances, while the other parameters are represented by well established physical expressions. In the proposed model, most of the parameters are in terms of the cell temperature, irradiance, and datasheet values, while a few parameters need to be tuned. The model is compared with four well-known methodologies to extract the parameters of the single-diode and double-diode models. The simulation studies make use of the different I-V characteristics provided in the photovoltaics (PVs) datasheets, characteristics extracted from an outdoor module, as well as the ones simulated with the software PC1D. The results show an improved precision of the proposed model to estimate the power characteristics for a wide range of temperatures and irradiances, not only in the maximum power point but also in the whole range of voltages. Furthermore, the proposed physical model can be easily applied to other kind of studies where a physical meaning of the PV parameters is of great importance., Peer Reviewed, Postprint (author's final draft)

Nonlinear dynamical systems such as weakly coupled oscillators are an interesting approach to be adopted for the regulation of power inverters inside microgrids. Aiming at the synchronization and load sharing in islanded mirogrid, this paper is inspired by oscillator synchronization property to propose a Hopf oscillator controller for the single-phase inverters. The Hopf oscillator dynamic equations are used for providing the inverter's frequency and amplitude voltage references which lead to a robust nonlinear droop behavior for driving the system without using communications. The Hopf oscillator provides better sharing of the load between inverters with higher robustness, less harmonic distortion, and faster time response of the associated limit cycle than the achieved by the other approach made with a Van der Pol oscillator. In addition, global asymptotic synchronization of system is proven by Lyapunov approach. Simulation results of a system composed by paralleled inverters are provided and compared with a Van der Pol oscillator approach reported in literature. Experimental results are also provided to prove the Hopf oscillator based controller under different circumstances., Peer Reviewed, Postprint (author's final draft)

Frequency control is one important issue in autonomous operating mode of Microgrids (MGs). In stand-alone microgrids, when generation power is not enough, it is inevitable to shed some parts of the load. This paper presents a decentralized fuzzy controller for optimal load shedding in MGs. The proposed controller which is separately installed for each load center uses a hierarchical fuzzy controller approach to make the optimal decision. Three inputs of the hierarchical fuzzy controller are the power of non-critical load, the load energy not supplied and its interruption frequency. From a specific time of the past, these inputs are calculated for all load centers, and updated periodically. The non-critical part of the loads which can be shed to survive network. Each decentralized controller of the loads has a bilateral communication with the microgrid central controller to transact some information, periodically. Simulation results on a typical microgrid with several load buses showing the effectiveness of the proposed method.

Satisfying the mobile traffic demand in next generation cellular networks increases the cost of energy supply. Renewable energy sources are a promising solution to power base stations in a self-sufficient and cost-effective manner. This paper presents an optimal method for designing a photovoltaic (PV)-battery system to supply base stations in cellular networks. A systematic approach is proposed for determining the power rating of the photovoltaic generator and battery capacity from a technical and economical point of view in order to minimize investment cost as well as operational expenditure, while the power autonomy of the PV-battery system is maximized in a multi-objective optimization framework. The proposed method is applied to optimally size a photovoltaic-battery system for three cases with different availability of solar power to investigate the effect of environmental conditions. Problem-solving using the proposed approach leads to a set of solutions at different costs versus different levels of power autonomy. According to the importance of each criterion and the preference of decision-makers, one of the achieved solutions can be selected for the implementation of the photovoltaic-battery system to supply base stations in cellular networks.

In order to provide Internet access to rural areas and places without a reliable economic electricity grid, self-sustainable drone-based cellular networks have recently been presented. However, the difficulties of power consumption and mission planning lead to the challenge of optimal sizing of the power supply for future cellular telecommunication networks. In order to deal with this challenge, this paper presents an optimal approach for sizing the photovoltaic (PV)-battery power supply for drone-based cellular networks in remote areas. The main objective of the suggested approach is to minimize the total cost, including the capital and operational expenditures. The suggested framework is applied to an off-grid cellular telecommunication network with drone-based base stations that are powered by PV-battery systems-based recharging sites in a rural location. The PV-battery system is optimally designed for three recharging sites with three different power consumption profiles with different peak and cumulative loads. Results show that the optimal design of the PV-battery system is dependent on geographical data, solar irradiation, and ambient temperature, which affect the output power of the PV system, as well as the power consumption profile, which affects the required number of PV panels and battery capacity.

Recently, the penetration of renewable energy sources (RESs) into electrical power systems is witnessing a large attention due to their inexhaustibility, environmental benefits, storage capabilities, lower maintenance and stronger economy, etc. Among these RESs, offshore wind power plants (OWPP) are ones of the most widespread power plants that have emerged with regard to being competitive with other energy technologies. However, the application of power electronic converters (PECs), offshore transmission lines and large substation transformers result in considerable power quality (PQ) issues in grid connected OWPP. Moreover, due to the installation of filters for each OWPP, some other challenges such as voltage and frequency stability arise. In this regard, various customs power devices along with integration control methodologies have been implemented to deal with stated issues. Furthermore, for a smooth and reliable operation of the system, each country established various grid codes. Although various mitigation schemes and related standards for OWPP are documented separately, a comprehensive review covering these aspects has not yet addressed in the literature. The objective of this study is to compare and relate prior as well as latest developments on PQ and stability challenges and their solutions. Low voltage ride through (LVRT) schemes and associated grid codes prevalent for the interconnection of OWPP based power grid have been deliberated. In addition, various PQ issues and mitigation options such as FACTS based filters, DFIG based adaptive and conventional control algorithms, ESS based methods and LVRT requirements have been summarized and compared. Finally, recommendations and future trends for PQ improvement are highlighted at the end.

An accurate model to represent the photovoltaic modules is essential to facilitate the efficient deployment of these systems in terms of design, analysis, and monitoring considerations. In this respect, this study proposes a new approach to improve the accuracy of the widely used five-parameter single-diode model. Two new physical equations are introduced to represent the series and shunt resistances, while the other parameters are represented by well established physical expressions. In the proposed model, most of the parameters are in terms of the cell temperature, irradiance, and datasheet values, while a few parameters need to be tuned. The model is compared with four well-known methodologies to extract the parameters of the single-diode and double-diode models. The simulation studies make use of the different I–V characteristics provided in the photovoltaics (PVs) datasheets, characteristics extracted from an outdoor module, as well as the ones simulated with the software PC1D. The results show an improved precision of the proposed model to estimate the power characteristics for a wide range of temperatures and irradiances, not only in the maximum power point but also in the whole range of voltages. Furthermore, the proposed physical model can be easily applied to other kind of studies where a physical meaning of the PV parameters is of great importance.

For several reasons, particularly due to the mismatch in the feeder impedance, accurate power sharing in islanded microgrids is a challenging task. To get around this problem, a distributed event-triggered power sharing control strategy is proposed in this paper. The suggested technique adaptively regulates the virtual impedances at both fundamental positive/negative sequence and harmonic frequencies and, therefore, accurately share the reactive, unbalanced, and harmonics powers among distributed generation (DG) units. The proposed method requires no information of feeder impedance and involves exchanging information between units at only event-triggered times, which reduces the communication burden without affecting the system performance. The stability and inter-event interval are analyzed in this paper. Finally, experimental results are presented to validate the effectiveness of the proposed scheme.

The Republic of Colombia is a country situated in the northwest of South America, with territories in Central America. In 2005, the interconnected electricity system served 87% of the population, a percentage that is below the 95% average for Latin America and the Caribbean. The Colombian government is making massive efforts to increase the electrification, especially at very remote and rural places. However, there are still several rural communities isolated from the main grid in Colombia. Also, although some communities have already been connected to the distribution system, the security and reliability are still an issue. One key element in the effort of electrification is the use of very small microgrids projects called “nanogrids.” A nanogrid is a small power system that uses a combination of renewable and conventional energy sources to supply power to small local loads. The total load in a nanogrid is typically less than 20 kW, as an industrial site, small rural village. or a household. The generators are primarily based on clean energy such as solar arrays, wind turbines, and fuel cells. In Colombia, the Caribbean coastline, Andes Mountains, and strong agriculture provide the country with abundant distributed renewable energy resources that might largely surpass the fast-growing electricity demand. In this framework, the nanogrids emerge as a solution to supply energy for some communities, located far away from the network, improving the inhabitant's quality of life. Moreover, the nanogrids might improve the security and reliability levels of the distribution system. This chapter discusses good practices and proposed some solutions to overcome challenges detected in nanogrid projects developed in Colombia. In essence, this chapter is a case study of nanogrid systems; it focuses on a full detailed explanation of 23 nanogrid projects developed in Colombia considering location, installed power, purpose, etc. Then the nanogrid projects are evaluated, and it gives, QC 20200911

In a hydrogen-based DC microgrid (MG), the integration of hydrogen subsystem increases the system complexity and flexibility. Effective power split, bus voltage stability and reliable operation become significant control issues of hydrogen-based DC MG. This paper proposes a simple and effective decentralized energy management strategy based on a mode-triggered droop scheme for an islanded PV/hydrogen/battery DC MG. In a decentralized manner, the proposed decentralized energy management strategy is implemented through two control steps: mode divisions and droop control. For practical implementation purposes of the proposed energy management strategy, the mode divisions scheme autonomously divides this DC MG into eight operating modes based on the system local information; the adaptive droop control method controls the distributed generation units based on their droop relationships under different operating modes. In addition, an islanded DC MG hardware-in-the-loop (HIL) RT-LAB simulation platform and a lab-scaled experimental platform are built to validate the effectiveness of the proposed decentralized strategy. The simulation and experiment results show that the proposed energy management strategy has an efficient power distribution ability without communication link under various operating modes.

The difference in power cell irradiances in cascaded multilevel converters results in different duty cycles among those cells when maintaining the maximum power point tracking (MPPT). However, the difference in cell duty cycles is undesired since it is proportional to the output voltage and current distortions. To this regard, a multilevel topology for photovoltaic (PV) applications is proposed, where an H6 bridge power cell is used instead of an H-bridge one. In case of solar irradiance mismatch among the power cells, the proposed converter injects power with lower voltage from the shaded cells without altering the PV voltage; hence maintaining the MPPT operation. This modification allows us to retain an equal duty cycle in all the power cells whatever the meteorological conditions are present; consequently, maintaining good output voltage and current waveform qualities. To test the effectiveness of the proposed solution, a detailed simulation model as well as an experimental prototype is built. The obtained results show that the proposed topology provides significantly improved output voltage and current qualities compared to the cascaded H-bridge one. The performance of the proposed topology compared to one offering improved harmonics performance, according to the European efficiency, has been also compared, where an enhancement of 2.64% has been registered.

In the conventional photovoltaic (PV) fed quasi-Z (qZ) network-based impedance-source converters (ISCs), the PV array is connected to their input, whereas in the proposed topology in this article, an additional array is paralleled to the second qZ-network's capacitor (C2). This modification allows harvesting more PV power through full utilization of the employed qZ-network in the classical ISCs. Moreover, the proposal offers higher conversion efficiency since the current in the second qZ-network's inductor (i_L2) is smaller. The voltage of the added PV array (PV2) is independent of the voltage of the primary array (PV1) in a wide range, which promotes tracking their maximum power points (MPPs) separatly, achieving a higher efficiency even under partial shading. The use of two separate maximum power point trackings (MPPTs) in one converter is a challenge since the perturbation done by the first MPPT alters the power in PV2 as well, and vice versa. Therefore, a two MPPs tracker algorithm, which perturbs two parameters and observes four variables, is proposed for the presented converter. The theoretical analysis is validated through real-time hardware-in-the-loop tests, and it demonstrates that at least 11% more power can be harvested compared to the conventional qZ-network-based ISC.

The electric sector is majorly concerned about the greenhouse and non-greenhouse gas emissions generated from both conventional and renewable energy sources, as this is becoming a major issue globally. Thus, the utilities must adhere to certain environmental guidelines for sustainable power generation. Therefore, this paper presents a novel nature-inspired and population-based Harris Hawks Optimization (HHO) methodology for controlling the emissions from thermal generating sources by solving single and multi-objective Optimal Power Flow (OPF) problems. The OPF is a non-linear, non-convex, constrained optimization problem that primarily aims to minimize the fitness function by satisfying the equality and inequality constraints of the system. The cooperative behavior and dynamic chasing patterns of hawks to pounce on escaping prey is modeled mathematically to minimize the objective function. In this paper, fuel cost, real power loss and environment emissions are regarded as single and multi-objective functions for optimal adjustments of power system control variables. The different conflicting framed multi-objective functions have been solved using weighted sums using a no-preference method. The presented method is coded using MATLAB software and an IEEE (Institute of Electrical and Electronics Engineers) 30-bus. The system was used to demonstrate the effectiveness of selective objectives. The obtained results are compared with the other Artificial Intelligence (AI) techniques such as the Whale Optimization Algorithm (WOA), the Salp Swarm Algorithm (SSA), Moth Flame (MF) and Glow Warm Optimization (GWO). Additionally, the study on placement of Distributed Generation (DG) reveals that the system losses and emissions are reduced by an amount of 9.8355% and 26.2%, respectively.

This paper presents the automatic load frequency control (ALFC) of two-area multisource hybrid power system (HPS). The interconnected HPS model consists of conventional and renewable energy sources operating in disparate combinations to balance the generation and load demand of the system. In the proffered work, the stability analysis of nonlinear dynamic HPS model was analyzed using the Hankel method of model order reduction. Also, an attempt was made to apply cascade proportional integral - proportional derivative (PI-PD) control for HPS. The gains of the controller were optimized by minimizing the integral absolute error (IAE) of area control error using particle swarm optimization-gravitational search algorithm (PSO-GSA) optimization technique. The performance of cascade control was compared with other classical controllers and the efficiency of this approach was studied for various cases of HPS model. The result shows that the cascade control produced better transient and steady state performances than those of the other classical controllers. The robustness analysis also reveals that the system overshoots/undershoots in frequency response pertaining to random change in wind power generation and load perturbations were significantly reduced by the proposed cascade control. In addition, the sensitivity analysis of the system was performed, with the variation in step load perturbation (SLP) of 1% to 5%, system loading and inertia of the system by ±25% of nominal values to prove the efficiency of the controller. Furthermore, to prove the efficiency of PSO-GSA tuned cascade control, the results were compared with other artificial intelligence (AI) methods presented in the literature. Further, the stability of the system was analyzed in frequency domain for different operating cases.

The electric sector is majorly concerned about the greenhouse and non-greenhouse gas emissions generated from both conventional and renewable energy sources, as this is becoming a major issue globally. Thus, the utilities must adhere to certain environmental guidelines for sustainable power generation. Therefore, this paper presents a novel nature-inspired and population-based Harris Hawks Optimization (HHO) methodology for controlling the emissions from thermal generating sources by solving single and multi-objective Optimal Power Flow (OPF) problems. The OPF is a non-linear, non-convex, constrained optimization problem that primarily aims to minimize the fitness function by satisfying the equality and inequality constraints of the system. The cooperative behavior and dynamic chasing patterns of hawks to pounce on escaping prey is modeled mathematically to minimize the objective function. In this paper, fuel cost, real power loss and environment emissions are regarded as single and multi-objective functions for optimal adjustments of power system control variables. The different conflicting framed multi-objective functions have been solved using weighted sums using a no-preference method. The presented method is coded using MATLAB software and an IEEE (Institute of Electrical and Electronics Engineers) 30-bus. The system was used to demonstrate the effectiveness of selective objectives. The obtained results are compared with the other Artificial Intelligence (AI) techniques such as the Whale Optimization Algorithm (WOA), the Salp Swarm Algorithm (SSA), Moth Flame (MF) and Glow Warm Optimization (GWO). Additionally, the study on placement of Distributed Generation (DG) reveals that the system losses and emissions are reduced by an amount of 9.8355% and 26.2%, respectively.

This paper presents the automatic load frequency control (ALFC) of two-area multisource hybrid power system (HPS). The interconnected HPS model consists of conventional and renewable energy sources operating in disparate combinations to balance the generation and load demand of the system. In the proffered work, the stability analysis of nonlinear dynamic HPS model was analyzed using the Hankel method of model order reduction. Also, an attempt was made to apply cascade proportional integral - proportional derivative (PI-PD) control for HPS. The gains of the controller were optimized by minimizing the integral absolute error (IAE) of area control error using particle swarm optimization-gravitational search algorithm (PSO-GSA) optimization technique. The performance of cascade control was compared with other classical controllers and the efficiency of this approach was studied for various cases of HPS model. The result shows that the cascade control produced better transient and steady state performances than those of the other classical controllers. The robustness analysis also reveals that the system overshoots/undershoots in frequency response pertaining to random change in wind power generation and load perturbations were significantly reduced by the proposed cascade control. In addition, the sensitivity analysis of the system was performed, with the variation in step load perturbation (SLP) of 1% to 5%, system loading and inertia of the system by ±25% of nominal values to prove the efficiency of the controller. Furthermore, to prove the efficiency of PSO-GSA tuned cascade control, the results were compared with other artificial intelligence (AI) methods presented in the literature. Further, the stability of the system was analyzed in frequency domain for different operating cases.

Regular assessments of events taking place around the globe can be a conduit for the development of new ideas, contributing to the research world. In this study, the authors present a new optimization algorithm named doctor and patient optimization (DPO). DPO is designed by simulating the process of treating patients by a physician. The treatment process has three phases, including vaccination, drug administration, and surgery. The efficiency of the proposed algorithm in solving optimization problems compared to eight other optimization algorithms on a benchmark standard test function with 23 objective functions is been evaluated. The results obtained from this comparison indicate the superiority and quality of DPO in solving optimization problems in various sciences. The proposed algorithm is successfully applied to solve the energy commitment problem for a power system supplied by a multiple energy carriers system., Peer Reviewed, Postprint (published version)

In today’s world, the development and continuation of life require energy. Supplying this energy demand requires careful and scientific planning of the energy provided by a variety of products, such as oil, gas, coal, electricity, etc. A new study on the operation of energy carriers called Energy Commitment (EC) is proposed. The purpose of the EC is to set a pattern for the use of energy carriers to supply energy demand, considering technical and economic constraints. EC is a constrained optimization problem that can be solved by using optimization methods. This study suggests the Following Optimization Algorithm (FOA) to solve the EC problem to achieve technical and economic benefits. Minimizing energy supply costs for the total study period is considered as an objective function. The FOA simulates social relationships among the community members who try to improve their community by following each other. Simulation is carried out on a 10-unit energy system supplied by various types of energy carriers that includes transportation, agriculture, industrial, residential, commercial, and public sectors. The results show that the optimal energy supply for a grid with 0.15447 Millions of Barrels of Oil Equivalent (MBOE) of energy demand costs 9.0922 millions dollar for a 24-h study period. However, if the energy supply is not optimal, the costs of operating energy carriers will increase and move away from the optimal economic situation. The economic distribution of electrical demand between 10 power plants and the amount of production units per hour of the study period is determined. The EC outputs are presented, which include an appropriate pattern of energy carrier utilization, energy demand supply costs, appropriate combination of units, and power plant production. The behavior and process of achieving the answer in the convergence curve for the implementation of FOA on EC indicates the exploration and exploitation capacity of FOA. Based on the simulated results, EC p, Peer Reviewed, Postprint (published version)

The dynamic performance of the local control of single-phase voltage source inverters (VSIs) can be degraded when supplying to nonlinear loads (NLLs) in microgrids. When this control is based on the droop principles, a proper calculation of the active and reactive averaged powers (P–Q) is essential for a proficient dynamic response against abrupt NLL changes. In this work, a VSI supplying to an NLL was studied, focusing the attention on the P–Q calculation stage. This stage first generated the direct and in-quadrature signals from the measured load current through a second-order generalized integrator (SOGI). Then, the instantaneous power quantities were obtained by multiplying each filtered current by the output voltage, and filtered later by utilizing a SOGI to acquire the averaged P–Q parameters. The proposed algorithm was compared with previous proposals, while keeping the active power steady-state ripple constant, which resulted in a faster calculation of the averaged active power. In this case, the steady-state averaged reactive power presented less ripple than the best proposal to which it was compared. When reducing the velocity of the proposed algorithm for the active power, it also showed a reduction in its steady-state ripple. Simulations, hardware-in-the-loop, and experimental tests were carried out to verify the effectiveness of the proposal., Peer Reviewed, Postprint (published version)

In this paper, a non-isolated high step-up dc-dc converter is presented. The proposed converter is composed of an interleaved structure and diode-capacitor multiplier cells for interfacing low-voltage renewable energy sources to high-voltage distribution buses. The aforementioned topology can provide a very high voltage gain due to employing the coupled inductors and the diode-capacitor cells. The coupled inductors are connected to the diode-capacitor multiplier cells to achieve the interleaved energy storage in the output side. Furthermore, the proposed topology provides continuous input current with low voltage stress on the power devices. The reverse recovery problem of the diodes is reduced. This topology can be operated at a reduced duty cycle by adjusting the turn ratio of the coupled inductors. Moreover, the performance comparison between the proposed topology and other converters are introduced. The design considerations operation principle, steady-state analysis, simulation results, and experimental verifications are presented. Therefore, a 500-W hardware prototype with an input voltage of 30-V and an output voltage of 1000-V is built to verify the performance and the theoretical analysis., Comment: 2020 North American Power Symposium

A simple high-performance decentralized controller based on Hopf oscillator is proposed for three-phase parallel voltage source inverter (VSI) in islanded Microgrid. In aß frame, the oscillators equations corresponding output current and com-mon bus voltage as feedbacks are designed according to coupled oscillator synchronization properties. The enough common bus information is considered to realize external synchronization, and the current feedback is to achieve internal synchronization between VSIs. Then, the controller employs Hopf evolution dynamics to integrate their both. Therefore, a larger phase error can be eliminated when additional inverter connects, and the pre-synchronization item is proposed to be close to synchronize with the operational inverters. In addition, an integrated small-signal states pace based on averaged model for two parallel VSIs is developed, and the root locus shows the large stability margin and low sensitivity of parameters. Simulation and experiment results verifi ed the effectiveness of the proposed method in aspects of the fast dynamics response and precise current sharing performance., Peer Reviewed, Postprint (published version)

Impedance network inverters are a good alternative for voltage-source and current-source inverters. The shoot-through solution and the boosting capability of such converters make them an excellent solution for photovoltaic (PV) application. Furthermore, energy storage integration in these inverters does not require any additional components in the converter; indeed, a battery can be directly connected in parallel with one of the capacitors of the Z- or quasi Z-network. However, for an optimal control of these converters, complex control and modulation strategies are required. Model Predictive Control (MPC) provides high control performance at the expense of the computational effort. In this paper, a low computational control method where both MPC and proportional resonant (PR) controller are combined, is proposed. This makes the proposed controller perform two iterations only instead of iterating for all the available switching states. As shown in the obtained results, the proposed controller conserves the high performance of the conventional MPC with 50% less computational burden.