Distributed energy storage system‐based control strategy for hybrid DC/AC microgrids in grid‐connected mode

This paper concentrates on the issues with the aim of providing a constant dc‐link voltage and desired power sharing for a distributed energy storage system (DESS)‐based hybrid microgrid under load variations. The hybrid microgrid which is consisted of PV system, lithium battery‐based storage system and a grid‐connected dc/ac converter are controlled by designing a controller based on the zero dynamics‐based mathematical equations of all used converters. Two buck and bidirectional buck‐boost dc/dc converters employed in PV and DESS systems, respectively, are responsible for damping the dc‐link voltage fluctuations, and also the grid‐connected converter is set to enhance the grid power quality and supply continuously the grid‐connected loads. The main contributions of the proposed control technique are simplicity and providing the simultaneous stable performance for both DC and AC sides under both DC and grid‐connected loads variations. Moreover, another contribution of the proposed control technique is providing accurate coordination in both steady‐state and dynamic conditions. To analyze the proposed controller, the dynamic operations of the converters in various operating conditions are evaluated. In this evaluation, several curves based on their zero dynamics are achieved, and their desired operations are completely investigated in different operating conditions. Simulation results in MATLAB/SIMULINK verify the proposed controller ability at reaching the desired zero dynamics and the stable performance of the proposed hybrid microgrid.     

Power characteristics of a fuel cell micro‐grid with wind power generation

An independent micro‐grid connected with renewable energy has the potential to reduce energy costs, and reduce the amount of greenhouse gas discharge. However, the frequency and voltage of a micro‐grid may not be stable over a long time due to the input of unstable renewable energy, and changes in short‐period power load that are difficult to predict. Thus, when planning the installation of a micro‐grid, it is necessary to investigate the dynamic characteristics of the power. About the micro‐grid composed from 10 houses, a 2.5 kW proton exchange membrane fuel cell is installed in one building, and it is assumed that this fuel cell operated corresponding to a base load. A 1 kW PEM‐FC is installed in other seven houses, in addition a 1.5 kW wind turbine generator is installed. The micro‐grid to investigate connects these generating equipments, and supplies the power to each house. The dynamic characteristics of this micro‐grid were investigated in numerical analysis, and the cost of fuel consumption and efficiency was also calculated. Moreover, the stabilization time of the micro‐grid and its dynamic characteristics accompanied by wind‐power generation and fluctuation of the power load were studied. Copyright © 2007 John Wiley & Sons, Ltd.     

Optimum operation strategy and economic analysis of a photovoltaic-diesel-battery-mains hybrid uninterruptible power supply

This paper presents the optimum operation strategy and economic analysis of a photovoltaic-diesel-battery-mains hybrid uninterruptible power supply (UPS). The system involves a photovoltaic, battery and bi-directional inverter that is connected in parallel to the grid. A diesel generator is required when the grid is not available for a longer time. The optimum operation strategy of the system is proposed for the diesel-connected mode (when the grid fails for several hours), while the economic analysis is evaluated for the grid-connected mode. The optimum strategy determines the ‘set point’ value for starting and stopping the diesel generator, resulting in a lower system operation cost within its lifetime. The optimum value is obtained by comparing the cost of the diesel fuel consumption and the battery wear. The economic analysis includes the system operation as UPS and demand side management. The system will reduce the power flow from the mains by increasing the power from the inverter to the load when the tariff is high. However, when the grid tariff is low, the power from the mains is used to charge the battery and to meet the load simultaneously.     

A centralized vehicle‐to‐grid scheme with distributed computing capacity engaging internet of smart charging points: Case study

In order to accommodate additional plug‐in electric vehicle (PEV) charging loads for existing distribution power grids, the vehicle‐to‐grid (V2G) technology has been regarded as a cost‐effective solution. Nevertheless, it can hardly scale up to large PEVs fleet coordination due to the computational complexity issue. In this paper, a centralized V2G scheme with distributed computing capability engaging internet of smart charging points (ISCP) is proposed. Within ISCP, each smart charging point equips a computing unit and does not upload PEV sensitive information to the energy coordinator, to protect PEV users’ privacy. Particularly, the computational complexity can be decreased dramatically by employing distributed computing, viz., by decomposing the overall scheduling problem into many manageable sub‐problems. Moreover, six typical V2G scenarios are analyzed deliberately, and based on that, a load peak‐shaving and valley‐filling scheduling algorithm is built up. The proposed algorithm can be conducted in real‐time to mitigate the uncertainties in arrival time, departure time, and energy demand. Finally, the proposed scheme and its algorithm are verified under the distribution grid of the SUSTech campus (China). Compared with uncoordinated charging, the proposed scheme realizes load peak‐shaving and valley‐filling by 11.98% and 12.68%, respectively. The voltage values are ensured within the limitation range by engaging power flow calculation, in which the minimum voltage values are increasing and the maximum voltage values are decreasing with the expansion of PEV penetration. What is more, the computational complexity of peak‐shaving and valley‐filling strategy is near‐linear, which verifies the proposed scheme can be carried out very efficiently.     

Power flow control of grid connected hybrid renewable energy system using hybrid controller with pumped storage

This paper presents a grid-connected HRES using a hybrid controller with PHS for optimal power flow control and minimizing the production cost. The novelty of the proposed approach is the joined execution of the SSA and CSA named as SSA-CS are apparently a very new metaheuristic algorithm. Moreover, the proposed method is the cost-effective power production of the microgrids and effective utilization of renewable energy sources without wasting the available energy. Here, the energy sources in particular PV system, WT, MT and battery with PHS are utilized to generate the power of the MG system. In the proposed approach, the required power demand of the energy system is predicted by the ANN technique. After that, the production cost minimization is done in view of the anticipated load demand by utilizing the optimization approaches to be a specific SSA-CS algorithm. The result of the proposed approach is actualized in the MATLAB/Simulink working platform. The performance of the proposed approach is examined by comparing the current methodologies such as SSA and PSO with the proposed SSA-CS approach. The simulation results show that the proposed method generates maximum power and furthermore the proposed framework has less production cost in light of the power demand.     

Implementation of repowering optimization for an existing photovoltaic‐pumped hydro storage hybrid system: A case study in Sichuan,China

For a remote area or an isolated island, where the grid has not extended, a standalone hybrid energy system can provide cheap and adequate power for local users. However, with the development of society, the load demand will increase and the original system cannot completely meet the load demand. This situation occurs in Xiaojin, Sichuan, China. The existing photovoltaic‐pumped hydro storage (PV‐PHS) hybrid system in this area as the original system cannot completely meet the load requirements at present. The term “repowering” aims to maximize the reliability of power supply and the utilization of the PV‐PHS hybrid energy system that differs from traditional planning optimization to build all components. The repowering strategy is to integrate wind turbines (WTs) and battery into the original system. For the repowering system, a power management strategy is proposed to determine the operating modes of the PHS and battery. Three objectives, which are minimizing percentage of the demand not supplied, levelized cost of energy, and curtailment rate of renewable energy, are considered in the optimization model. Simulation is conducted by single‐objective, biobjective, and triobjective particle swarm optimization (PSO) techniques. For the single‐objective optimization, the comparison of PSO and genetic algorithm (GA) is made. For the double‐objective optimization, multiobjective PSO (MOPSO) is compared with weighted sum approach (WSA), and fuzzy satisfying method is utilized to find the win‐win solution. The results reveal that the repowering strategy can help to achieve maximum reliability of power supply after load demand increases significantly, and the battery plays an important role in such a hybrid system.     

Analysis of reactive power strategies in HVDC‐connected wind power plant clusters

Offshore wind power plants (WPPs) built near each other but far from shore usually connect to the main grid by a common high‐voltage DC (HVDC) transmission system. In the resulting decoupled offshore grid, the wind turbine converters and the high‐voltage DC voltage‐source converter share the ability to inject or absorb reactive power. The overall reactive power control dispatch influences the power flows in the grid and hence the associated power losses. This paper evaluates the respective power losses in HVDC‐connected WPP clusters when applying 5 different reactive power control strategies. The case study is made for a 1.2‐GW–rated cluster comprising 3 WPP and is implemented in a combined load flow and converter loss model. A large set of feasible operating points for the system is analyzed for each strategy. The results show that a selection of simulations with equal wind speeds is sufficient for the annual energy production comparison. It is found that the continuous operation of the WPPs with unity power factor has a superior performance with low communication requirements compared with the other conventional strategies. The optimization‐based strategy, which is developed in this article, allows a further reduction of losses mainly because of the higher offshore grid voltage level imposed by the high‐voltage DC voltage‐source converter. Reactive power control in HVDC‐connected WPP clusters change significantly the overall power losses of the system, which depend rather on the total sum of the injected active power than on the variance of wind speeds inside the cluster.     

A fuzzy control strategy for power smoothing and grid dynamic response enrichment of a grid‐connected wind energy conversion system

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.     

直驱永磁风力发电系统电网侧变换器的模糊功率控制

针对基于储能的并网永磁直驱风力发电系统的运行特点,提出了一种对电网侧变换器的模糊功率控制策略,当电网发生电压瞬时跌落时使电网侧变换器运行在模糊功率控制模式,依据电网电压跌落深度及风机输出功率大小通过模糊控制器来确定发出无功电流的大小,从而使风电系统能够适度地向电网提供一定的无功功率来支撑电网电压。仿真结果表明,所提出的控制策略正确、有效。     

A robust power control strategy to enhance LVRT capability of grid‐connected DFIG‐based wind energy systems

This paper presents a new robust and effective control strategy to mitigate symmetrical voltage dips in a grid‐connected doubly fed induction generator (DFIG) wind energy conversion system without any additional hardware in the system. The aim is to control the power transmitted to the grid so as to keep the electrical and mechanical quantities above their threshold protection values during a voltage dip transient. To achieve this, the references of the powers are readjusted to adapt the wind energy conversion system to the fault conditions. Robust control strategies, combining the merits of sliding mode theory and fuzzy logic, are then proposed in this paper. These controllers are derived from the dynamic model of the DFIG considering the variations in the stator flux generated by the voltage drop. This approach is found to yield better performance than other control design methods which assume the flux in the stator to remain constant in amplitude. This control scheme is compliant with the fault‐ride‐through grid codes which require the wind turbine generator to remain connected during voltage dips. A series of simulation scenarios are carried out on a 3‐MW wind turbine system to demonstrate the effectiveness of the proposed control schemes under voltage dips and parameter uncertainty conditions.     

Energy‐cost‐aware flow shop scheduling considering intermittent renewables,energy storage,and real‐time electricity pricing

The industrial sector is one of the major energy consumers that contribute to global climate change. Demand response programs and on‐site renewable energy provide great opportunities for the industrial sector to both go green and lower production costs. In this paper, a 2‐stage stochastic flow shop scheduling problem is proposed to minimize the total electricity purchase cost. The energy demand of the designed manufacturing system is met by on‐site renewables, energy storage, as well as the supply from the power grid. The volatile price, such as day‐ahead and real‐time pricing, applies to the portion supplied by the power grid. The first stage of the formulated model determines optimal job schedules and minimizes day‐ahead purchase commitment cost that considers forecasted renewable generation. The volatility of the real‐time electricity price and the variability of renewable generation are considered in the second stage of the model to compensate for errors of the forecasted renewable supply; the model will also minimize the total cost of real‐time electricity supplied by the real‐time pricing market and maximize the total profit of renewable fed into the grid. Case study results show that cost savings because of on‐site renewables are significant. Seasonal cost saving differences are also observed. The cost saving in summer is higher than that in winter with solar and wind supply in the system. Although the battery system also contributes to the cost saving, its effect is not as significant as the renewables.     

Fractional‐order sliding mode control for hybrid drive wind power generation system with disturbances in the grid

The proposal of hybrid drive grid‐connected wind turbine based on speed regulating differential mechanism (SRDM) has been made in this paper to generate constant‐frequency power without fully‐ or partially‐rated frequency converters so as well improve electric power quality. However, disturbances in the power grid including sudden load fluctuation and sub‐synchronous resonance (SSR) can lead to the pulsating torque to act on the shaft section between SG and exciter at the main generator collector, such that the speed regulating accuracy of SRDM is seriously affected. As a result, this paper synthesizes a new‐type fractional‐order sliding mode controller (FOSMC) with a load torque observer (LTO) for the high‐accuracy speed control of permanent magnet synchronous motor (PMSM) in SRDM. Taking advantage of ridge regression algorithm, related parameters including rotational inertia and viscous friction coefficient of speed regulating system are calculated accurately. Finally, comparative experiments are carried out under four cases of mean of 5, 10, 13, and 21 m/s wind speeds to verify the satisfactory performances of designed FOSMC with LTO. Comparative experimental results show that FOSMC with LTO can effectively eliminate undesirable chattering effect. Additionally, under operating conditions of changing wind speeds, SSR, and sudden load fluctuation in power grid, the output speed of SRDM that corresponds directly to the frequency output of SG can be steadily and accurately regulated by using proposed control scheme. SRDM equipped with designed controller enables the power frequency to meet the National Standard of PR China perfectly.     

Optimizing 100%‐renewable grids through shifting residential water‐heater load

A low‐carbon electricity supply for Australia was simulated, and the installed capacity of the electrical grid was optimized by shifting the electricity demand of residential electric water heaters (EWHs). The load‐shifting potential of Australia was estimated for each hour of the simulation period using a nationwide aggregate EWH load model on a 90 × 110 raster grid. The electricity demand of water heaters was shifted from periods of low renewable resource and high demand to periods of high renewable resource and low demand, enabling us to effectively reduce the installed capacity requirements of a 100%‐renewable electricity grid. It was found that by shifting the EWH load by just 1 hour, the electricity demand of Australia could be met using purely renewable electricity at an installed capacity of 145 GW with a capacity factor of 30%, an electricity spillage of 20%, and a generation cost of 15.2 ¢/kWh. A breakdown of the primary energy sources used in our scenario is as follows: 43% wind, 29% concentrated solar thermal power, and 20% utility photovoltaic. Sensitivity analysis suggested that further reduction in installed capacity is possible by increasing the load‐shifting duration as well as the volume and insulation level of the EWH tank.     

Modeling and performance analysis of renewable hydrogen energy hub connected to an ac/dc hybrid microgrid

This paper proposes a system modeling and performance analysis of a renewable hydrogen energy hub (RHEH) connected to an ac/dc hybrid microgrid (MG). The proposed RHEH comprises a photovoltaic (PV)-based renewable energy source (RES) as the primary source, a proton exchange membrane fuel cell (PEMFC) as the secondary power source, and a proton exchange membrane electrolyzer (PEMELZ) that can generate and store hydrogen in a hydrogen tank. All these resources are directly connected at the dc bus of the ac/dc microgrids. The PEMFC operates and utilizes the hydrogen from the hydrogen tank when the energy generated by RES cannot meet the load demand. A coordinated power flow control approach has been developed for the RHEH to mitigate the mismatch between generation and demand in the ac/dc microgrid and produce renewable hydrogen when renewable power is in excess. The paper also proposes a modified hybrid Perturb & Observe-Particle Swarm Optimization (Hybrid PO-PSO) algorithm to ensure the maximum power point tracking (MPPT) operation of the PV and the PEMFC. The operation of the proposed RHEH is validated through simulations under various critical conditions. The results show that the proposed RHEH is effective to maintain the system power balance and can provide power-to-hydrogen and hydrogen-to-power when required.     

A generic demand‐side management model for smart grid

The demand‐side management (DSM) is one of the most important aspects in future smart grids: towards electricity generation cost by minimizing the expensive thermal peak power plants. The DSM greatly affects the individual users' cost and per unit cost. The main objective of this research article is to develop a generic demand‐side management (G‐DSM) model for residential users to reduce peak‐to‐average ratio (PAR), total energy cost, and waiting time of appliances (WTA) along with fast execution of the proposed algorithm. We propose a system architecture and mathematical formulation for total energy cost minimization, PAR reduction, and WTA. The G‐DSM model is based on genetic algorithm (GA) for appliances scheduling and considers 20 users having a combination of appliances with different operational characteristics. Simulation results show the effectiveness of G‐DSM model for both single and multiple user scenarios. Copyright © 2015 John Wiley & Sons, Ltd.     

Robust multi‐model control of an autonomous wind power system

This article presents a robust multi‐model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT‐PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi‐model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright © 2006 John Wiley & Sons, Ltd.     

A novel peak load shaving algorithm via real‐time battery scheduling for residential distributed energy storage systems

As population grows and energy consumption increases, generation, transmission, and energy distribution costs also increase. Sudden and unpredicted demand increase at peak periods might lead to failure and even damage the power grid. This is a challenge for stability and reliability of the grid. Peak load shaving is considered as an effective approach while transition from peak load periods. In this paper, peak load shaving is modeled mathematically through storing energy on demand side and solved using optimization method. Using the results obtained from solving the optimization problem, a simple effective algorithm is proposed for peak load shaving via real‐time scheduling of distributed battery storage systems without complicated calculations. All characteristics required for systemic design of peak load shaving for residential, commercial, and industrial loads are presented. This method can be used in the presence of photovoltaic arrays or other renewable or nonrenewable distributed energy resources simultaneously, and it can be adapted to different conditions and demands. Here, real measured data of a residential state, an office building with photovoltaics, a hotel, and a small office are used for simulation, and GAMS is used for analysis.     

Zero non‐detection zone assessment for anti‐islanding protection in rotating machines based distributed generation system

The challenges for a reliable operation of electrical power system have increased due to the presence of multi‐distributed generation units (DGs) in the distribution systems in order to meet the increase of the load demand. Detection of unintentional islanding situation is very important as non‐detection of islanding situation could result in a cascaded failure of the system. If the islanding situation remains undetected, the instability in the islanded part can lead to a complete failure of the electrical power system. This paper introduces a new passive scheme for islanding detection, which is suitable for multi‐distributed generation units based on rotating machines. The proposed method is based on the measurements of the system voltage and frequency to compute two indices called the islanding index and harmonics index. The islanding index is the main index used to discriminate and identify the islanding situation. However, the harmonics index in conjunction with a strategy called speed reduction strategy assists the islanding index to discriminate between islanding situation in case of a close power match and system disturbances. The simulation studies were conducted in MATLAB/SIMULINK environment, and various cases have been considered, such as normal operation, islanding operation, sudden load change, DG tripping, separation of some DG units, faults, etc. The novelty of the proposed strategy is that it provides fast detection and has zero nondetection zone compared with the existing detection methods. Moreover, the proposed strategy has no effect on the power quality, and the maximum detection time is almost 350 ms at a close power match. The results indicate that the proposed scheme is successful in discrimination of the islanding conditions from other grid disturbances, revealing its great potential to be able to detect islanding events. Finally, the proposed method is applied only for rotating machine based DGs, such as wind turbines. Wind farms' power generation system based on doubly‐fed induction generators is introduced in this paper as an example of DGs units.     

A novel method for obtaining virtual inertial response of DFIG‐based wind turbines

This paper investigates virtual inertia control of doubly fed induction generator (DFIG)‐based wind turbines to provide dynamic frequency support in the event of sudden power change. The relationships among DFIGs' virtual inertia, rotor speed and network frequency variation are analysed, and a novel virtual inertia control strategy is proposed. The proposed control strategy shifts the maximum power point tracking (MPPT) curve to the virtual inertia control curves according to the frequency deviation so as to release the ‘hidden’ kinetic energy and provide dynamic frequency support to the grid. The calculation of the virtual inertia and its control curves are also presented. Compared with a PD regulator‐based inertial controller, the proposed virtual inertia control scheme not only provides fast inertial response in the event of sudden power change but also achieves a smoother recovery to the MPPT operation. A four‐machine system with 30% of wind penetration is simulated to validate the proposed control strategy. Simulation results show that DFIG‐based wind farms can provide rapid response to the frequency deviation using the proposed control strategy. Therefore, the dynamic frequency response of the power grid with high wind power penetration can be significantly improved. Copyright © 2015 John Wiley & Sons, Ltd.