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This paper aimed to identify the main aspects and influencing factors in the design of hybrid systems for powering base transceiver stations based on solar resources, with the goal of optimizing both the design and the initial investment costs for these systems. For this purpose, a hybrid solar-Diesel system with battery storage was designed for a low-power transceiver station, located in an area with a well-defined solar resource. Both the main design stages and the influencing factors on the design and, implicitly, the costs were identified, with the study's conclusions highlighted at the end.

This paper aimed to identify the main aspects and influencing factors in the design of hybrid systems for powering base transceiver stations based on solar resources, with the goal of optimizing both the design and the initial investment costs for these systems. For this purpose, a hybrid solar-Diesel system with battery storage was designed for a low-power transceiver station, located in an area with a welldefined solar resource. Both the main design stages and the influencing factors on the design and, implicitly, the costs were identified, with the study's conclusions highlighted at the end. [ABSTRACT FROM AUTHOR]

This study proposes an advanced control strategy for the coordination of an energy storage system (ESS) based on fuel cells (FCs) and renewable energy sources (RESs) to enhance frequency dynamic performance in hybrid power systems (HPSs). The proposed coordination control strategy is based on the nonlinear proportional-integral (NPI) controller, which increases the system's flexibility in dealing with disturbances and changing operating conditions. In addition, it improves the system's dynamic response and attempts to address system weakness caused by highly penetrating RESs. The proposed NPI controller is optimally designed using a new optimization algorithm, called dandelion optimizer (DO), whose proficiency and effectiveness are verified by comparing its performance with other well-known optimization algorithms used in the literature; particle swarm optimization (PSO), grey wolf optimization (GWO), and ant lion optimization (ALO) algorithms considering various standard objective functions. Furthermore, the proposed NPI controller performs better than other control strategies used in the literature under load/RESs fluctuations. The effectiveness of the proposed nonlinear coordination control strategy is examined and investigated through a self-contained HPS that includes a diesel generator, RESs (i.e., photovoltaic and wind power plants), battery ESS, flywheel ESS, aqua electrolyzer for hydrogen production, FCs, electric vehicles, and customer loads. The simulation results carried out by the MATLAB software demonstrate the superior performance of the proposed DO-optimized NPI controller for HPS frequency regulation, even when the power system's parameters have substantial variations. Moreover, the results revealed that the proposed strategy significantly reduces the frequency deviation by approximately 95% compared to the conventional coordination strategy based on the fixed contribution of RESs and by 90% compared to the adaptive coordination control based on the PI controller.

This work reports load-frequency-control (LFC) of a three-area hybrid power system incorporating renewables and electric-vehicles (EV). Such a power system with applicable non-linearities necessitates a resilient controller. In this respect, a multi-stage fractional-order proportional-integral-derivative (MSFOPID) controller is explored for the LFC operation of the presented hybrid power system. For the proposed controller, there is a considerable improvement of 81.3% in terms of objective function (ISE value). Similarly, the foible evidence study shows an improvement of 39% with respect to other considered secondary controllers. The active role of EVs in preserving the system dynamics is inspected thoroughly. The impact of redox-flow batteries as an energy storage device and parametric variation of phase-locked-loop for system dynamic control are illustrated. Furthermore, the robustness of explored MSFOPID controller optimized gains is checked against alterations in power-system-loading and renewable energy sources, respectively. [ABSTRACT FROM AUTHOR]

Due to the high uncertainty of renewable energy sources, and the diversity of energy sources and storage systems, it is mandatory to seek a controller that manages all these renewable energy sources and this hybrid energy storage. This paper proposed a renewable energy management system using flatness control and PID and PSO technologies that track the maximum power point from the PV array and manages the energy storage elements. Two energy storage are adopted: battery storage and hydrogen tank. The proposed (Nero-fuzzy) controller also works to fill the hydrogen storage tank wisely and safely by controlling the alkaline electrolyzer and the tank's pressure. The main aim of this combined system is to attain power stability. Since the PV is the primary production source, a PSO MPPT is a proposed system for optimum power delivered by the PV under different radiation and temperature conditions. The fuel cell has been used to compensate for the energy lost when there is a lack of control due to weather conditions or high-power demand by the DC load. A battery was coupled to the DC bus to respond quickly to the power requirement. When the radiation intensity is 1000 W/m2, the PV will generate enough 18 kW to supply the load, run the electrolyzer 7 kW, and charge the batteries. While in the radiation change, when it is 240 W/m2, the solar panels produce (4.3 kW) and the load (4.7 kW). The battery works first because of its quick response, and then the fuel cell works to generate instead of it, which is sufficient to operate the load only. The results show a stable and fast response grid under different weather conditions and load scenarios. [ABSTRACT FROM AUTHOR]

The present paper introduces a disturbance‐rejection based fractional‐order proportional‐integral‐derivative (DR‐foPID) controller as optimal control strategy for performance enhancement of hybrid power system (HPS). The two‐area HPS is equipped with various generation sources in the form of solar–thermal‐system (STS), conventional thermal, wind‐turbine‐system (WTS) and geo‐thermal power plants establishing a coordinated system frequency and tie‐line power control. In addition, electric vehicles (EVs) are integrated with the HPS to check its effect on dynamic characteristics. The controller gains are optimized using an effective bio‐geography based krill herd (BBKH) optimization technique to achieve the required performance of the HPS. This study validates the efficacy of the BBKH adjusted DR‐foPID controller for efficient operation of system dynamic characteristics. The resilience of DR‐foPID controller gains is confirmed by a sensitivity test involving large fluctuations in system load variations from their nominal values. It is also demonstrated that EVs help to increase the performance of HPS. A study involving the power management capability of EVs for improving the system performance is also demonstrated. Moreover, the effect of redox flow battery as energy storage device for system dynamic control are also illustrated. At last, a DR‐foPID controller is tested in case study on three‐area HPS. [ABSTRACT FROM AUTHOR]

This work primarily focuses on electrical characteristics of a hybrid power system (HPS) incorporating renewable energy generation (REG) (HPSREG). The major components of HPSREG are the resources coordinated with multi-unit of photovoltaic cells, multi-unit of wind turbine generators, a diesel engine generator (DEG), energy storage system (ESS) with diverse nature and an electric vehicle (EV). The performance characteristics of HPSREG are determined by constant generation of power from the various sources as well as varying load perturbations. As the variation in load demand will introduce fluctuation in frequency and power with constant generation. In few of overcome the frequency and power deviation under both the above-mentioned generation and load demand conditions, proper control technique is required. In order to control the deviation in frequency and power, an integration in the environment of fractional order (FO) calculus for proportional–integral–derivative (PID) controller and fuzzy controller, termed with FO-Fuzzy PID controller tuned with quasi-opposition based harmonic search (QOHS) algorithm has been proposed. The results acquired with the proposed FO-Fuzzy-PID controller are then analyzed along with FO-PID and PID controller route for quantify effectiveness for the same under the considered cases to determine the effectiveness of the algorithm undertaken. Sensitivity investigation is also conducted in order to show the strength of the technique under study of differences in HPSREG parameters of magnitude.

Abstract This study proposes an energy management system (EMS) to manage a standalone hybrid power system (HPS) comprising solar photovoltaic (PV), proton exchange membrane fuel cell (PEMFC), and a battery energy storage. The battery and a hydrogen storage system in PEMFC provide short‐ and long‐term electricity storage, respectively. The EMS ensures electrical efficiency during normal/abnormal operation of the HPS and related limitations, namely unexpected variations in solar irradiance and loads, PEMFC cold start, and battery charging status. The proposed EMS is evaluated using mathematical modelling, simulation studies, and real‐time digital simulation. The results show that the proposed EMS is resilient to complex solar PV/load power changes and keeps the dc‐link voltage in place. The viability of the proposed HPS is analysed using daily average solar insolation and load profiles. This analysis is useful to schedule problems of load/generation. The economic analysis of the proposed EMS, done using Homer pro, ensures that the HPS operates cost‐effectively.

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 large-scale penetration of intermittent Renewable Energy (RE) sources such as wind and solar power generation may cause a problem of frequency aberration of interconnected Hybrid Power System (HPS). This occurs when the load frequency control of interconnected system is unable to compensate the power balance between generation and load demand. Also owing to the enhancement of future transport, the Plug-in Electric Vehicle (PEV) plays a significant role to customer at demand side. Thus, the PEV can act as a power control to compensate the power balance in Renewable Energy integrated power system. This paper presents a physics inspired Atom Search Optimization (ASO) algorithm for tuning the parameters of Fractional Order Proportional-Integral-Derivative (FOPID) controller for Automatic Load Frequency control of HPS. In this proposed work, an attempt has been made to analyze the frequency stability of HPS using Matignon's theorem. The interconnected HPS consists of reheat thermal power system, RE sources such as wind and solar thermal power generation associated with energy storage devices namely aqua electrolyzer, fuel cell and electric vehicle. The gain and fractional terms of the controller were obtained by minimizing the Integral Time Absolute Error of interconnected system. The robustness of ASO-tuned FOPID controller is tested on two-area HPS that was modelled using MATLAB/Simulink. The results obtained were then compared with other fractional order and classical integer order controllers. From the simulation results, it is inferred that the proposed ASO-tuned FOPID controller gives superior transient and steady-state response compared with other controllers. Moreover, the self-adaptiveness and robustness of the controller was validated to account for the change in RE power generations and system parameters. Furthermore, the effectiveness of the method is proved by comparing its performance with the recent literature works. The real-time applicability of proffered controller is validated in hardware-in-the-loop simulation using Real Time Digital Simulator.

Article outlines hybrid energy sources for fulfil supply demand through proposed approach. The hybrid renewable energy sources generation capacity of 6 kW as solar power and 50 kW power as solid oxide fuel cell plant with storage system are interfaced to the DC bus in proposed paper for performance diagnosis on the basis of power demand as per utility load application by conversion of DC power to AC power and power quality of grid/load parameters collected on PCC, which affected by RE source integration at utility bus in terms of power quality parameters as per event ON/OFF grid mode. For this study design a two-bus test system, first bus is DC bus for integration of solar PV plant and solid oxide fuel cell power plant to generate hybrid DC power which convert to AC power by using inverter technology and deliver to the second bus of utility load bus in proposed test system for application of utility load as well as utility grid as per event proposed. A low pass LC filter is modeled to remove high frequency harmonics from the inverter output which is fed to grid as well as test system of utility network.

Summary: A considerable number of intermittent renewable resources like photovoltaic generation and wind energy when integrated into the conventional grid technology causes serious issues in the power systems like frequency instability. So an intelligent controller is desired for steady and reliable operation of the electric grid. This paper deals with the frequency control of hybrid power system (HPS) employing a sine cosine adopted Harris' hawks optimization (SCaHHO) technique. The proposed technique aims at improving the performance of the original Harris' hawks optimization (HHO) algorithm by incorporating a sine and cosine function in the calculation of escaping energy and chances of escaping of prey respectively to emphasize the exploitation process of hawks. The effectiveness of the SCaHHO technique is validated with the novel HHO technique as well as moth flame optimization, sine cosine algorithm, grey wolf optimization, salp swarm algorithm and gravitational search algorithm using 23 standard test functions. A non‐parametric statistical investigation is also carried out to verify the effectiveness of the suggested technique. Later the SCaHHO technique is utilized to tune a newly proposed adaptive fuzzy proportional integral derivative controller (AFPID) for frequency control of HPS. The suggested SCaHHO‐tuned AFPID controller achieves an improved control action by moderating the frequency fluctuations as compared to the PID controller. Hardware‐in‐loop validation of the proposed load frequency control scheme is also carried out using OPAL‐RT to measure its fidelity with the numerical simulation results. [ABSTRACT FROM AUTHOR]

A considerable no. of intermittent renewable sources such as PV generation and wind energy when integrated to the conventional grid technology causes serious issues in the power systems like frequency instability. So a more balancing controller is desired for a stable and reliable operation of the power system. Bidirectional power control of the EV aggregator is making itself a wise choice for distributed energy storage to scale down the frequency and power fluctuation. In this work, an intelligent load frequency controller using a fractional-order adaptive fuzzy PID controller with filter (FOAFPIDF) for hybrid power system with electric vehicle (EV) based on modified salp swarm algorithm (MSSA) technique is proposed. The effectiveness of MSSA technique is compared with original salp swarm algorithm as well as moth flame optimization , grey wolf optimization , particle swarm optimization and sine cosine algorithm techniques for benchmark test functions using statistical analysis. The effectiveness of the suggested load frequency control strategy by the use of electric vehicle as well as with other energy storing elements such as the superconducting magnetic energy storage component, flywheel energy storage system and ultra-capacitor along with their inherent rate constraint nonlinearity is validated by numerical simulations conducted on the studied test system. It is demonstrated that the proposed controller provides a better control action to suppress the frequency fluctuations as compared to PID controller. The robustness of the controller is also investigated against variation of system parameters and random load changes. [ABSTRACT FROM AUTHOR]

Concerned with the increasing greenhouse gases in the atmosphere due to fossil fuels, the entire world is focusing on electricity generation through renewable energy resources. The most advantageous aspect of the distributed renewable sources is to provide the electricity to remote, scattered and the deprived rural areas by developing the hybrid power system at the smaller scale where power transmission through grid extension is not viable due to some economical, technical or environmental constraints for building new transmission lines. An accurate and adequate control strategy becomes inevitable to uphold the smooth operation by restraining the frequency and voltage deviation within its limit ensuring the highest degree of reliability of hybrid power system to provide an adequate power quality. In this paper, a comprehensive review of different control strategies adopted in isolated and interconnected multi-area hybrid power systems is presented.

This study proposes an advanced control strategy for the coordination of an energy storage system (ESS) based on fuel cells (FCs) and renewable energy sources (RESs) to enhance frequency dynamic performance in hybrid power systems (HPSs). The proposed coordination control strategy is based on the nonlinear proportional-integral (NPI) controller, which increases the system's flexibility in dealing with disturbances and changing operating conditions. In addition, it improves the system's dynamic response and attempts to address system weakness caused by highly penetrating RESs. The proposed NPI controller is optimally designed using a new optimization algorithm, called dandelion optimizer (DO), whose proficiency and effectiveness are verified by comparing its performance with other well-known optimization algorithms used in the literature; particle swarm optimization (PSO), grey wolf optimization (GWO), and ant lion optimization (ALO) algorithms considering various standard objective functions. Furthermore, the proposed NPI controller performs better than other control strategies used in the literature under load/RESs fluctuations. The effectiveness of the proposed nonlinear coordination control strategy is examined and investigated through a self-contained HPS that includes a diesel generator, RESs (i.e., photovoltaic and wind power plants), battery ESS, flywheel ESS, aqua electrolyzer for hydrogen production, FCs, electric vehicles, and customer loads. The simulation results carried out by the MATLAB software demonstrate the superior performance of the proposed DO-optimized NPI controller for HPS frequency regulation, even when the power system's parameters have substantial variations. Moreover, the results revealed that the proposed strategy significantly reduces the frequency deviation by approximately 95% compared to the conventional coordination strategy based on the fixed contribution of RESs and by 90% compared to the adaptive coordination control based on the PI controller. [ABSTRACT FROM AUTHOR]

• Various optimization techniques in AGC are critically reviewed. • Role of demand side management in AGC is also addressed. • Impact of electric vehicle integration to the grid is studied. Load and generation must be balanced for the system to be stable, which implies frequency deviation must be minimal. Whenever load perturbation takes place in the network, frequency diverges from its nominal value and unplanned exchange of power leads to unfortunate consequences. This will cause the mal-operation of electrical equipment such as change in speed, low efficiency, vibrations, harmonics, inaccuracy etc. Automatic Generation Control (AGC) provides a signal to alter the actual output power of multiple generators within a certain range based on changes in system frequency. For this purpose, several control techniques were employed in the system. This paper focuses on various approaches in the domain of automatic generation control for microgrid based hybrid power system. AI based techniques shows progressive results as compared to other classical and cascaded approaches. Machine learning and deep learning based controlling schemes has also been studied and study shows that these techniques provides loftier performance in comparison of other AI methods due to the availability of large number of trained data sets of controlled variable. Further massive data of controlled variables can be used to restore the system after cyber-attack. It is also addressed how to integrate electric vehicles with the power grid for Load Frequency Control. At the end of this article, some research gap such as role of demand response, protection and control issues, resilient controllers for cyber threats etc. are also addressed which will be useful for researcher working in this area. [ABSTRACT FROM AUTHOR]

A hybrid power system (HPS) is developed for the photovoltaic (PV) powered and tethered multirotor unmanned aerial vehicle (UAV) based on the robot operating system (ROS) and verified using an indoor hardware-in-the-loop (HIL) test. All the processes, including a UAV flight mode change (i.e., takeoff, hovering, and landing) and power flow control (consisting of PV modules, a LiPo battery pack, and a UAV) are completely automated using a combination of Pixhawk 2.1 and the Raspberry Pi 3 Model B (RPi 3B). Once the indoor HIL test starts, (1) the UAV takes off and hovers with a preassigned 10 m altitude at a fixed point and keeps hovering until the voltage drops below 13.4 V ; (2) the UAV lands when the voltage drops below 13.4 V, and the hybrid power controller (HPC) starts to charge the LiPo battery pack using the energy from PV modules; and (3) the UAV takes off when the voltage of the battery pack becomes more than 16.8 V, and the procedure repeats from (1). A PV-powered and tethered multirotor UAV using the proposed HPS can fly more safely for a longer time, particularly in an urban area, and so it is competitive to the traditional multirotor type UAV in the sense of both the flight time and the surveillance mission performance.

In developing countries like India, very limited observatory stations are available to collect daily global solar radiation (GSR). This paper focuses to develop a common model for daily GSR estimation and standalone hybrid power system (HPS) design in view of six different climate locations in India. A new strategy is applied for finding the daily GSR model in Madurai location in Tamil Nadu, India. It is based on new parameter, which is named as 'approximate-bright sunshine duration' from the real-time measurement. The remaining six locations are estimated from the new model developed. In addition, to improve the accuracy of estimation, the developed linear one input variable model is further modified as two input variable model, based on the latitudes of six different climatic locations. The performances of developed one-input and two input models are analyzed using statistical indicators. The result shows that the developed two input variable model has provided excellent estimations for Madurai and also other six Indian climatic locations of latitudes ranging from 9°N to 13°N. This work also projects a detailed analysis of HPS design based on three meteorological data inputs to cover the residential energy demand. The NASA data, predicted ANFIS data (estimated data) and the measurement data are used in the analysis for the HPS feasibility and size optimization. The analysis shows that the hybrid configurations are same for all the locations, whereas PV and converter sizes are varied in the range of 47–52 kW and 23–27 kW, respectively. [ABSTRACT FROM AUTHOR]

Feed-in Tariff (FiT) has been one of the most effective policies in accelerating the development of renewable energy (RE) projects. The amount of RE electricity in the FiT purchase agreement is an important decision that has to be made by the RE project developers. They have to consider various crucial factors associated with RE system operation as well as its stochastic nature. The presented work aims to assess the sensitivity and profitability of a hybrid power system (HPS) in cases of RE system failure or shutdown. The amount of RE electricity for the FiT purchase agreement in various scenarios was determined using a novel tool called On-Grid Problem Table based on the Power Pinch Analysis (PoPA). A sensitivity table has also been introduced to assist planners to evaluate the effects of the RE system's failure on the profitability of the HPS. This table offers insights on the variance of the RE electricity. The sensitivity analysis of various possible scenarios shows that the RE projects can still provide financial benefits via the FiT, despite the losses incurred from the penalty levied. [ABSTRACT FROM AUTHOR]

This paper aims to present a mathematical model for the design of a hybrid power system (HPS) to support a remote island with 100 thousand citizens. The goal is to reduce diesel fuel consumption by adequate expansion of wind power supply. Pumped hydroelectric storage (PHS) is used in the HPS to buffer the impact of intermittent behavior of wind energy. A superstructure is proposed for HPS design, considering all possible capital decisions (e.g. the number of wind turbines) and hourly-basis operational variables (such as the amount of surplus electricity in storage and its discharge). The HPS design problem can then be formulated as a mixed-integer linear program (MILP) based on the proposed superstructure. For a given total share of wind power, the optimal mix of diesel-based and wind power supplies as well as the required capacity of PHS are determined using a four-step optimization approach, involving minimizing (i) the consumption of diesel fuel, (ii) the number of wind turbines, (iii) the size of the upper water reservoir, and (iv) the charge/discharge rates of the PHS system. In this sequential optimization, the objective value obtained in a previous step is added as an additional constraint to the next step. The proposed HPS design model is applied to a real case study of the remote K Island on the other side of Taiwan Strait using hourly-basis, year-round historical data. Inclusion of other renewable energy sources, such as photovoltaic cells and biomass-fired power plants, as well as economic perspectives will be considered in future work. [ABSTRACT FROM AUTHOR]

Aiming at improving the efficiency of braking energy regeneration in hybrid power system of electric vehicle, hybrid power system (HPS) with battery, ultracapacitor and bi-directional DC/DC converter and normal strategy were studied. HPS was improved, which created three modes of regeneration. Piecewise control strategy of braking energy regeneration was proposed. In high-speed, middle-speed and low-speed each section, different modes of regeneration were carried out. According to voltage of ultracapacitor, speed of motor and so on, time of switchover between the sections was decided. Based on control of braking current of motor and time of switchover, smooth braking was achieved. Normal strategy and piecewise control strategy were experimentalized in different velocities on a miniature electric vehicle. The experimental results indicate that the efficiency of braking energy regeneration increases and smooth braking is achieved by the piecewise control strategy. [ABSTRACT FROM AUTHOR]

Highlights: [•] Investigation on economic feasibility of PV/diesel system in various climatic zones. [•] HOMER is used to solve economic feasibility analysis. [•] By the sensitivity analysis, the net present cost is reduced. [•] Optimum climatic zone in Tamil Nadu, India is recommended. [Copyright &y& Elsevier]

Abstract: In this paper we present firstly the different hybrid systems with fuel cell. Then, the study is given with a hybrid fuel cell–photovoltaic generator. The role of this system is the production of electricity without interruption in remote areas. It consists generally of a photovoltaic generator (PV), an alkaline water electrolyzer, a storage gas tank, a proton exchange membrane fuel cell (PEMFC), and power conditioning units (PCU) to manage the system operation of the hybrid system. Different topologies are competing for an optimal design of the hybrid photovoltaic–electrolyzer–fuel cell system. The studied system is proposed. PV subsystem work as a primary source, converting solar irradiation into electricity that is given to a DC bus. The second working subsystem is the electrolyzer which produces hydrogen and oxygen from water as a result of an electrochemical process. When there is an excess of solar generation available, the electrolyzer is turned on to begin producing hydrogen which is sent to a storage tank. The produced hydrogen is used by the third working subsystem (the fuel cell stack) which produces electrical energy to supply the DC bus. The modelisation of the global system is given and the obtained results are presented and discussed. [Copyright &y& Elsevier]

Most of the research on Hybrid Power Systems (HPS) is to provide an economical and sustainable power to the rural electrification. This paper focuses on the design of an HPS for the building which is a part of the urban electrification. In the developing countries, the rate of increase in the demand is more than the rate of increase in the supply, which is a major challenge resulting in very frequent outages. There are number of motives to build integrated and synergistic renewable energy based HPS including environmental, economic, and social benefits. Most of these HPS topologies use inverters to interface the renewable sources to the buildings with an offering of low quality power. Hence, modern sustainability initiatives call for a design for both new HPS and retrofitting of an existing HPS topology. With this aspect, this paper describes the topology of retrofitting HPS with dc Motor-Synchronous Generator set instead of the use of inverter to an existing building power system. This can improve the power quality, reliability of the supply, and ensures stable plant operation. The proposed HPS topology can be used in small-to-medium sized isolated constructions like green buildings, industries, and universities. Different renewable energy sources like Photo Voltaics (PV), Wind Power (WP), and Fuel Cells (FC) are integrated to form HPS. An energy management and control algorithm is proposed to use the energy sources optimally to upgrade these buildings with more reliability and efficiency. The modeling and simulation is done using MATLAB/Simulink. [ABSTRACT FROM PUBLISHER]

Classical wind energy conversion systems are usually passive generators. The generated power does not depend on the grid requirement but entirely on the fluctuant wind condition. A dc-coupled wind/hydrogen/supercapacitor hybrid power system is studied in this paper. The purpose of the control system is to coordinate these different sources, particularly their power exchange, in order to make controllable the generated power. As a result, an active wind generator can be built to provide some ancillary services to the grid. The control system should be adapted to integrate the power management strategies. Two power management strategies are presented and compared experimentally. We found that the “source-following” strategy has better performances on the grid power regulation than the “grid-following” strategy. [ABSTRACT FROM AUTHOR]

Concerned with the increasing greenhouse gases in the atmosphere due to fossil fuels, the entire world is focusing on electricity generation through renewable energy resources. The most advantageous aspect of the distributed renewable sources is to provide the electricity to remote, scattered and the deprived rural areas by developing the hybrid power system at the smaller scale where power transmission through grid extension is not viable due to some economical, technical or environmental constraints for building new transmission lines. An accurate and adequate control strategy becomes inevitable to uphold the smooth operation by restraining the frequency and voltage deviation within its limit ensuring the highest degree of reliability of hybrid power system to provide an adequate power quality. In this paper, a comprehensive review of different control strategies adopted in isolated and interconnected multi-area hybrid power systems is presented. [ABSTRACT FROM AUTHOR]

A hybrid power system (HPS) is developed for the photovoltaic (PV) powered and tethered multirotor unmanned aerial vehicle (UAV) based on the robot operating system (ROS) and verified using an indoor hardware-in-the-loop (HIL) test. All the processes, including a UAV flight mode change (i.e., takeoff, hovering, and landing) and power flow control (consisting of PV modules, a LiPo battery pack, and a UAV) are completely automated using a combination of Pixhawk 2.1 and the Raspberry Pi 3 Model B (RPi 3B). Once the indoor HIL test starts, (1) the UAV takes off and hovers with a preassigned 10 m altitude at a fixed point and keeps hovering until the voltage drops below 13.4 V ; (2) the UAV lands when the voltage drops below 13.4 V, and the hybrid power controller (HPC) starts to charge the LiPo battery pack using the energy from PV modules; and (3) the UAV takes off when the voltage of the battery pack becomes more than 16.8 V, and the procedure repeats from (1). A PV-powered and tethered multirotor UAV using the proposed HPS can fly more safely for a longer time, particularly in an urban area, and so it is competitive to the traditional multirotor type UAV in the sense of both the flight time and the surveillance mission performance. [ABSTRACT FROM AUTHOR]