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Integration of renewable energies such as wind and solar with an energy storage system (ESS) in a distribution network is the interest of current studies in power system engineering. Wind and battery ESS (BESS) are known for their complement and efficient approaches into the distribution networks. The promising of renewable energies for wind and solar in Afghanistan is a motivation for stepping up the power sector of the country by enhancing the power quality as well as selfdependency in electricity production. In this study, a multi-objective optimisation technique, non-dominated sorting genetic algorithm II (NSGA-II) is proposed for an extensive distribution network in Kabul city considering technical, environmental, and financial control schemes for the network improvement. Three different scenarios with various objective functions are deemed to evaluate their impact on decision variables and network parameters. Furthermore, optimum allocation of the wind turbine and charge/discharge scheduling of BESS are revealed with improvement in performance of the power system. Simulations are deployed in MATLAB® with its application on developed 162-bus real-distribution network to demonstrate the effect of different objective function arrangements in each scenario as well as confirming the robustness of the proposed approach. [ABSTRACT FROM AUTHOR]

Integration of renewable energies such as wind and solar with an energy storage system (ESS) in a distribution network is the interest of current studies in power system engineering. Wind and battery ESS (BESS) are known for their complement and efficient approaches into the distribution networks. The promising of renewable energies for wind and solar in Afghanistan is a motivation for stepping up the power sector of the country by enhancing the power quality as well as self‐dependency in electricity production. In this study, a multi‐objective optimisation technique, non‐dominated sorting genetic algorithm II (NSGA‐II) is proposed for an extensive distribution network in Kabul city considering technical, environmental, and financial control schemes for the network improvement. Three different scenarios with various objective functions are deemed to evaluate their impact on decision variables and network parameters. Furthermore, optimum allocation of the wind turbine and charge/discharge scheduling of BESS are revealed with improvement in performance of the power system. Simulations are deployed in MATLAB® with its application on developed 162‐bus real‐distribution network to demonstrate the effect of different objective function arrangements in each scenario as well as confirming the robustness of the proposed approach. [ABSTRACT FROM AUTHOR]

The rapid growth of renewable energies specifically wind and solar with their intermittent phenomena has recently become an exciting and important topic among researchers worldwide. The integration of such devices in distribution networks comprising of battery energy storage systems (BESSs) is considered as efficient and complementation approach which their well-managed configuration and scheduling via optimal arrangement yield not only productive and reliable power delivery to end-users, but cost-saving opportunity for utility managers. When dealing with photovoltaic (PV), reactive power capability of PV inverter is another aspect of interest that can contribute in enhancing effective penetration of wind, solar, and storage system into distribution networks. In this paper, a robust and novel optimization technique epsilon multiobjective genetic algorithm $\epsilon$ -MOGA is proposed and applied to a real 162-bus distribution network. A three-objective function optimization encompassing environmental, technical, and economic aspect is developed to size the centralized wind-farm and BESS parameters, distributed rooftop PV, and PV inverter reactive power control in an optimal manner. The proposed arrangement is simulated in MATLAB and compared with several cases to show its superior implementation concerning carbon emission reduction, better technical aspect, annual saving, and grid power alleviation. [ABSTRACT FROM AUTHOR]

Due to the interconnected scheme of multiple components, such as distributed generators, storage systems, and loads through converters to a common bus in DC microgrids, the possibility of fault occurrence is increasing significantly. Meanwhile, due to the huge and rapid increase of short-circuit currents, the development of a small- and large-scale DC system requires a reliable and fast protection system to ensure fault clearance and maintain safety for the rest of the system. Thus, fault protection has been focused on as one of the most critical issues in a direct current network. The application of traditional circuit-breakers for DC fault protection has the drawback of slow operation, which requires a high rating power equipment. Recently, the high speed and excellent performance capabilities of semiconductor breakers have attracted a lot of attention and been considered as an optimal solution for fast DC fault interruption. In this study, a bidirectional Insulated-Gate Bipolar Transistor (IGBT) semiconductor breaker, suitable for the fault protection of low-voltage DC networks, is proposed. The operating characteristics of this breaker are based on changes in the circuit current and terminal voltage of IGBTs. It detects the abrupt change of the terminal voltage as an abnormal condition and isolates the faulted branch in a short time to prevent the operation disturbance in the healthy part of the network. Therefore, for the entire protection of a typical 400V DC-microgrid cluster, breakers need to be integrated and examined in each branch and the interconnected lines. The proposed protection method in this study is examined in a Simulink®/MATLAB environment to analyze and assess its operation. [ABSTRACT FROM AUTHOR]

Featured Application: The incentive method with flexible contribution functions can be applied to demand response by the reactive power market and distribution company, which has the possibility to reduce the additional installation of distribution control equipment and battery capacity. It also leads to the reduction of total electricity purchase cost of consumers, and the power system can achieve high mixing of renewable energy in the grid with the reactive power incentive demand response and the IoT development. Furthermore, reliability assessment of cooperative control with the participation rate will give an important contribution to the robust design of the system. In order to solve urgent energy and environmental problems, it is essential to carry out high installation of distributed generation using renewable energy sources (RESs) and environmentally-friendly storage technologies. However, a high penetration of RESs usually leads to a conventional power system unreliability, instability and low power quality. Therefore, this paper proposes a reactive power control method based on the demand response (DR) program to achieve a safe, reliable and stable power system. This program does not enforce a change in the active power usage of the customer, but provides a reactive power incentive to customers who participate in the cooperative control of the distribution company (DisCo). Customers can achieve a reduction in their total energy purchase by gaining a reactive power incentive, whilst the DisCo can achieve a reduction of its total procurement of equipment and distribution losses. An optimal control schedule is calculated using the particle swarm optimization (PSO) method, and also in order to avoid over-control, a modified scheduling method that is a dual scheduling method has been adopted in this paper. The effectiveness of the proposed method was verified by numerical simulation. Then, simulation results have been analyzed by case studies. [ABSTRACT FROM AUTHOR]

In consideration of the natural environment and depletion of energy resources, the widespread use of electric power system is expected in which the power is generated from sources of renewables such as wind and solar. When these plants are introduced in large scale, the use of broad land is required. Due to low transmission losses and small stability problems, multi-terminal high voltage direct current (MTDC) transmission becomes advantageous as long-distance power transmission system. Since DC current does not incorporate a zero cross point, therefore it's blocking is difficult. This paper proposes a DC resonant semiconductor breaker which enables rapid fault clearance for self-excited HVDC transmission. This circuit breaker is connected as a semiconductor switch, in parallel with a group of capacitors, and resistors in the DC transmission line. The capacitor is charged to a higher voltage from the DC transmission line. For generating reverse current to allow the zero cross point in the transmission line, the semiconductor switch turns on to open the circuit breaker. After blocking, the inductance of the line is demagnetized by the resistor and fault clearing is achieved. The system except fault point can continue its normal operation. [ABSTRACT FROM AUTHOR]

Due to the depletion of fossil resources and the increase in carbon dioxide emissions, renewable energy systems (RESs) such as photovoltaic (PV) and wind generator (WG) have become an active player in power systems (PSs). In Japan, diesel generators (DGs) are the means of power generation in most isolated islands. Therefore, the introduction of RESs into these islands is of great importance. However, due to the uncertainty of RESs, battery energy storage systems (BESSs), fuel cells (FCs) and exploiting the electric vehicles (EVs) owned by customers are expected as vital power sources for the next generation. Moreover, demand response programs are utilized in this paper. As a result of reforming PSs in recent years, transactions on power markets have also been increasing in Japan. The Japan electric power exchange provides day-ahead market, intraday hour-ahead market, and forward market. It is expected that these markets make it possible to deal with uncertainties related to the generated power fluctuation. This paper presents the optimal operation method for multi-area PSs consisting of DG, PV, WG, BESS and FC by using chance-constrained programming. The proposed method has achieved reduction of the total operational cost of the multi-area small power systems by using FC, household EVs and two power markets. [ABSTRACT FROM AUTHOR]

Japan contains a vast number of isolated islands. Majority of these islands are powered by diesel generators (DGs), which are operationally not economical. Therefore, the introduction of renewable energy systems (RESs) into these area is very much vital. However, the variability of RESs as a result of weather condition as well as load demand, battery energy storage system (BESS) is brought into play. Demand response (DR) programs have also been so attractive in the energy management systems for the past decades. Among them, the real-time pricing (RTP) has been one of the most effective demand response program being utilized. This program encourages the customer to increase or reduce the load consumption by varying the electricity price. Also, due to the increase in power transaction market, Japan electric power exchange (JEPX) has established spot (day-ahead), intraday hour-ahead, and forward market programs. This paper utilizes day-ahead and hour-ahead markets, since these markets can make it possible to deal with uncertainty related to generated power fluctuations. Therefore, this paper presents the optimal operation method coping with the uncertainties of RESs in multi-area small power systems. The proposed method enables flexibility to correspond to the forecasting error by providing two kinds of power markets among multi-area small power systems and trading the shortage and surplus powers. Furthermore, it accomplishes a stable power supply and demand by RTP. Thus, the proposed method was able to reduce operational cost for multi-area small power systems. The process of creating operational plan for RTP, power trading at the markets and the unit commitment of DGs are also presented in this paper. Simulation results corroborate the merit of the proposed program. [ABSTRACT FROM AUTHOR]

Recently, the off-grid smart house has been attracting attention in Japan for considering global warming. Moreover, the selling price of surplus power from the renewable energy system by Feed-In Tariff (FIT) has declined. Therefore, this paper proposes an off-grid smart house with the introduced Photovoltaic (PV) system, Solar Collector (SC) system, HotWater Heat Pump (HWHP), fixed battery and Electric Vehicle (EV). In this research, a multi-objective optimization problem is considered to minimize the introduced capacity and shortage of the power supply in the smart house. It can perform the electric power procurement from the EV charging station for the compensation of a shortage of power supply. From the simulation results, it is shown that the shortage of the power supply can be reduced by the compensation of the EV power. Furthermore, considering the uncertainty for PV output power, reliable simulation results can be obtained. [ABSTRACT FROM AUTHOR]

A smart house generally has a Photovoltaic panel (PV), a Heat Pump (HP), a Solar Collector (SC) and a fixed battery. Since the fixed battery can buy and store inexpensive electricity during the night, the electricity bill can be reduced. However, a large capacity fixed battery is very expensive. Therefore, there is a need to determine the economic capacity of fixed battery. Furthermore, surplus electric power can be sold using a buyback program. By this program, PV can be effectively utilized and contribute to the reduction of the electricity bill. With this in mind, this research proposes a multi-objective optimization, the purpose of which is electric demand control and reduction of the electricity bill in the smart house. In this optimal problem, the Pareto optimal solutions are searched depending on the fixed battery capacity. Additionally, it is shown that consumers can choose what suits them by comparing the Pareto optimal solutions. [ABSTRACT FROM AUTHOR]

Output power fluctuation of the wind turbine generator is a serious issue for power systems. The battery energy storage system is installed to the power system to solve this problem. However, the large battery energy storage system can increase the capital cost of the wind turbine generator system. Hence, the capacity of the battery should be reduced as much as possible. This article presents anH∞based control method for the output power smoothing method of the wind turbine generator by using a battery energy storage system. The output power fluctuation of the wind turbine generator is considered in the frequency domain. Low-frequency fluctuations are smoothed by pitch angle control of the wind turbine generator, while high-frequency variations are smoothed by charge or discharge of the battery energy storage system, respectively. The battery energy storage system’s capacity and mechanical stress of wind turbine blades can be reduced by the proposed method. In addition, the gain-scheduled control theory is applied to the pitch angle control system of the wind turbine generator. Therefore, the robust control performance for high non-linearities of the wind turbine generator model can be achieved. The effectiveness of the proposed method is validated by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper presents a power smoothing control scheme for a permanent-magnet-synchronous-generator-based wind farm considering wake effects. The integrated power smoothing method consists of a pitch angle control system, a kinetic wind-energy turbine inertia control system, and a dc-link voltage control system. Low frequency range power fluctuations caused by wind speed variations are smoothed by the pitch angle control system and the kinetic wind-energy turbine inertia control system. Power fluctuations in the high frequency range are smoothed by the dc-link voltage control system. This power smoothing approach is cost-effective because the power smoothing is made possible without additional energy storage devices. In addition, the wake effects of the wind farm are considered for power smoothing with different tower spaces. The proposed method is compared with the conventional maximum-power-point-tracking method. Simulation results confirm the proposed method efficacy in smoothing the power injected by a wind farm. [ABSTRACT FROM PUBLISHER]

ABSTRACT This paper concentrates on the output power smoothing and the grid dynamic response enhancement of a grid-interactive MW-class permanent magnet synchronous generator-based wind energy conversion system (WECS). A simple fuzzy controller method is applied to improve the overall performance of the WECS. The proposed method can retrieve the storing kinetic energy from the inertia of a wind turbine, perfectly. As a result, it can ensure a proficient power smoothing of the variable speed WECS. On the other hand, the grid side inverter is controlled by the fuzzy controller. This approach can reduce the fluctuation of DC link voltage and can deliver a smooth power to the power grid. The proposed method is compared with two other methods such as the maximum power point tracking control method and the without fuzzy controller method. A simple shunt circuit also includes in the DC link circuit. Therefore, during the system fault condition, the WECS can perform a stable operation. Effectiveness of the proposed method is verified by numerical simulations. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

To incorporate the abundance of renewable energy into the power system, it is required to reconfigure the energy system. An intelligent power grid such as the smart grid is the solution for future energy demand. Among several renewable sources, the wind energy conversion system (WECS) is the rapidly growing source of energy, which is considered as the backbone of renewable energy and the smart grid. This paper deals with control strategies of distributed wind farms that are connected to smart houses for a smart grid application. A grid-side energy storage system is considered to deliver smooth power to the system. Stable control strategies under the line fault condition are also discussed in this paper. The surplus power of the smart houses is sent back to the power grid, and a house owner can benefit by selling the extra power to the power company. The detailed modeling and control strategies of an intelligent power system are demonstrated in this paper. The effectiveness of the proposed system is verified by the extensive numerical simulation results. [ABSTRACT FROM AUTHOR]

A digital H∞ controller for a permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) is presented. Wind energy is an uncertain fluctuating resource which requires a tight control management. So, it is still an exigent task for the control design engineers. The conventional proportional-integral (PI) control is not ideal during high turbulence wind velocities, and the nonlinear behavior of the power converters. These are raising interest towards the robust control concepts. The robust design is to find a controller, for a given system, such that the closed-loop system becomes robust that assurance high-integrity and fault tolerant control system, robust H∞ control theory has befallen a standard design method of choice over the past two decades in industrial control applications. The robust H∞ control theory is also gaining eminence in the WECS. Due to the implementation complexity for the continuous H∞ controller, and availability of the high speedy micro-controllers, the design of a sample-data or a digital H∞ controller is very important for the realistic implementation. But there isn't a single research to evaluate the performance of the digital H∞ controller for the WECS. In this paper, the proposed digital H∞ controller schemes comprise for the both generator and grid interactive power converters, and the control performances are compared with the conventional PI controller and the fuzzy controller. Simulation results confirm the efficacy of the proposed method which are ensured the WECS stabilities, mitigate shaft stress, and improving the DC-link voltage and output power qualities [ABSTRACT FROM AUTHOR]

This paper deals with controlling the output power smoothing of a wind energy conversion systems (WECS) by using permanent magnet synchronous generator (PMSG). It uses the inertia control of the wind turbine and DC-link voltage control. The PMSG is connected to the grid through a generator-side converter and a grid-side inverter based on AC-DC-AC methods. The generator-side converter is used to control the torque of the PMSG while the grid-side inverter is used to control DC-Link voltage and grid voltage. Fuzzy logic is implemented to determine the torque command by using inertia of wind turbine. The inputs of the fuzzy logic are given by the operating point of the rotational speed of the PMSG and the difference between the wind turbine torque and the generator torque. From the proposed method, the generator torque is smoothed and kinetic energy generated by the inertia of the wind turbine is used to smooth the power fluctuations of PMSG. Also, a stable operation of WECS is achieved during the system fault by using the chopper circuit in the DC-link circuit. The output power smoothing is achieved with stability and low cost. The effectiveness of the proposed method is verified by the numerical simulations. [ABSTRACT FROM AUTHOR]

A pulse amplitude modulation (PAM) control can adjust the DC-link voltage of a motor drive. A bi-directional buck-boost DC-DC converter is required at the primary side of PWM-VSI to implement PAM control. This paper is proposed PAM control technique for a permanent magnet synchronous motor (PMSM) based on fuzzy control system. The PAM coefficient (K_PAM) is a constant value for a conventional PAM control system. It requires online adjustment to improve overall performance of a PAM control system. The proposed fuzzy controller based PAM control regulates the K_PAM according to online commanded load voltage. This paper deals with different operation modes of a bi-directional buck-boost DC-DC cascade converter, motoring (accelerate and steady state) and braking operations of a PMSM at different load conditions and speeds. The total harmonic distortion (THD) and system efficiency are also shown in this paper. Effectiveness of the proposed method is confirmed by simulation results. [ABSTRACT FROM AUTHOR]

This paper presents a high efficiency drive strategy for micro-turbine generator (MTG) in which permanent magnet synchronous generator (PMSG) is used. PMSG operates at maximum efficiency point by optimizing the phase of armature current of PMSG; i.e., an optimum d-axis current in the rotor reference frame is analytically derived from mathematical model of PMSG taking iron loss into account. In addition, in order to use turbine output power effectively, compressor input power is minimized by optimizing revolving speed of PMSG. Simulation results confirm validity of the proposed method. [ABSTRACT FROM AUTHOR]

Nowadays a sensor-less vector control system for a motor drive becomes promising to avoid a position sensor. A back electro-motive-force or flux observer is used for sensor-less drive of permanent magnet synchronous motors from middle to high speed range. Thus, the estimation accuracy of the observer influences sensor-less drive performance. This paper proposes a sensor- less vector control system using the H8 flux observer in which the observer gain is designed based on the H8 control theory. This observer is insensitive to high frequency disturbances such as voltage disturbance due to non-linearity of PWM voltage source inverter, measurement noise of current sensors, and modeling errors. So, the total performance of a sensor-less control system is enhanced. The detailed configuration of the H∞ flux observer is described in this paper. Simulation results are compared with the conventional full-order flux observer-based sensor-less system. [ABSTRACT FROM AUTHOR]

In this article, a technique is proposed for maximum power-point tracking control of a wind generation system. The optimal operation speed to which the wind turbine output power maximizes is determined with parameters identified by an iterative least squares technique. The effectiveness of the maximum point tracking control with identified parameters of wind turbine is verified by computer simulation. In addition, the article discusses how to address rotational speed and output power in the case when the wind turbine parameters used for determining the optimum rotational speed have errors. [ABSTRACT FROM AUTHOR]

Wind energy conversion systems have become important in the research of renewable energy sources. This is in no small part due to the rapid advances in the size of wind generators as well as the development of power electronics and their applicability in wind energy extraction. However, wind energy has a drawback of having only 1/800 (gm per cubic cm) density as compared to that of water energy. Wind energy does not remain constant and wind turbine output is proportional to the cube of wind speed, which causes the generated power of the wind turbine generator (WTG) to fluctuate. In this paper, a technique is proposed for output power leveling of a wind generation system. Wind turbine blades have a large inertia compared to the inertia of a generator. The inertia of the rotor behaves like an inductor in an electrical circuit. It helps smooth the wind turbine output power, stores energy during acceleration, and restores energy during deceleration. The effectiveness of output power leveling control is verified by simulations for the wind power generation system. [ABSTRACT FROM AUTHOR]

To realize the maximum efficiency control and/or flux-weakening control for interior permanent magnet synchronous motors, exact motor parameters are typically required. It is well known that motor parameters vary with driving conditions such as temperature and magnetic saturation. In this article, the effect of parameter variations on the performance of maximum efficiency control and flux-weakening control are quantitatively investigated. Then, an on-line parameter identification method is proposed to prevent parameter variation from degrading the control performance. This method simultaneously identifies motor parameters involved in the control strategies by using both the recursive least-squares method and constant gain adaptive identification method. The effectiveness of the maximum efficiency control and flux-weakening control incorporated with on-line parameter identification strategy is confirmed by computer simulations. [ABSTRACT FROM AUTHOR]

Currently, the Direct-Current (DC) microgrid has been gaining popularity because most electronics devices require a DC power input. A DC microgrid can significantly reduce the AC to DC energy conversion loss. However, a power grid may experience a line fault situation that may damage important household devices and cause a blackout in the power system. This work proposes a new line fault protection scheme for a DC microgrid system by using a battery energy storage system (BESS). Nowadays, the BESS is one of the most cost effective energy storage technologies for power system applications. The proposed system is designed from a distributed wind farm smart grid. A total of three off-shore wind farms provide power to the grid through a high voltage DC (HVDC) transmission line. The DC microgrid was modeled by a BESS with a bi-directional DC–DC converter, various DC-loads with step down DC–DC converters, a voltage source converter, and a voltage source inverter. Details of the control strategies of the DC microgrid are described. During the line fault situation, a transient voltage was controlled by a BESS. From the simulation analyses, it is confirmed that the proposed method can supply stable power to the DC grid, which can also ensure protection of several loads of the DC microgrid. The effectiveness of the proposed system is verified by in a MATLAB/SIMULINK® environment. [ABSTRACT FROM AUTHOR]