Equivalent Method of Integrated Power Generation System of Wind, Photovoltaic and Energy Storage in Power Flow Calculation and Transient Simulation

针对工程实际开展风光储联合发电系统在潮流计算和机电暂态仿真中的等值方法研究，旨在为大容量风光储联合发电系统的并网仿真分析奠定基础。将潮流计算的等值分为单元机组和集电系统2部分来研究。单元机组等值采用根据不同控制模式选取不同节点类型的方法，针对集电系统等值提出基于损耗不变原则的方法。等值模型和详细模型的算例结果表明，潮流计算等值方法具有较好的精度。在机电暂态仿真动态等值中，基于实际工程计算的最严重工况分析原则，提出运行在满出力点的单机“倍乘”等值模型，为工程计算中的风光储联合发电系统动态等值提供了一种解决方案。

Probabilistic small signal stability analysis of power system with wind power and photovoltaic power based on probability collocation method

Recently, with increasing improvements in the penetration of wind power and photovoltaic power in the world, probabilistic small signal stability analysis(PSSSA) of a power system consisting of multiple types of renewable energy has become a key problem. To address this problem, this study proposes a probabilistic collocation method(PCM)-based PSSSA for a power system consisting of wind farms and photovoltaic farms. Compared with the conventional Monte Carlo method, the proposed method meets the accuracy and precision requirements and greatly reduces the computation; therefore, it is suitable for the PSSSA of this power system. Case studies are conducted based on a 4-machine 2-area and New England systems, respectively. The simulation results show that, by reducing synchronous generator output to improve the penetration of renewable energy, the probabilistic small signal stability(PSSS) of the system is enhanced. Conversely, by removing part of the synchronous generators to improve the penetration of renewable energy, the PSSS of the system may be either enhanced or deteriorated.

Dynamic and Power Generation Features of A Wind-Wave Hybrid System Consisting of A Spar-Type Wind Turbine and An Annular Wave Energy Converter in Irregular Waves

Combining wave energy converters(WECs)with floating offshore wind turbines proves a potential strategy to achieve better use of marine renewable energy.The full coupling investigation on the dynamic and power generation features of the hybrid systems under operational sea states is necessary but limited by numerical simulation tools.Here an aero-hydro-servo-elastic coupling numerical tool is developed and applied to investigate the motion,mooring tension,and energy conversion performance of a hybrid system consisting of a spar-type floating wind turbine and an annular wave energy converter.Results show that the addition of the WEC has no significant negative effect on the dynamic performance of the platform and even enhances the rotational stability of the platform.For surge and pitch motion,the peak of the spectra is originated from the dominating wave component,whereas for the heave motion,the peak of the spectrum is the superposed effect of the dominating wave component and the resonance of the system.The addition of the annular WEC can slightly improve the wind power by making the rotor to be in a better position to face the incoming wind and provide considerable wave energy production,which can compensate for the downtime of the offshore wind.

Research and practice of designing hydro/ photovoltaic hybrid power system in microgrid

Small-hydro power station is often used in remote areas beside a river,but it doesn't match electricity demand so well,especially in dry seasons. A photovoltaic (PV) system with battery is a suitable option to complement the electricity gap. In this paper,a new structure of megawatt-class PV system integrating battery at DC-bus (DC: direct current) is proposed to be used in hydro/PV hybrid power system,and 4 main designing considerations and several key equipments are discussed. In 2011,a 2 MWp PV station with the proposed structure was built up in Yushu,China. From stability analysis,the station shows a strong stability under load cut-in/off and solar irradiance's fluctuation.

Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

IoT Enabled Microgrid Framework Using a Novel Dispersal Diffusion Artificial Neural Network Controller for PV Systems and Wind Energy to Minimize Electrical Faults

A system based on a PV-Wind will ensure better efficiency and flexibility using lower energy production.Today,plenty of work is being focussed on Doubly Fed Induction Generators(DFIG)utilized in wind energy systems.DFIG is found to be the best option in the Wind Energy Conversion Systems(WECS)to mitigate the issues caused by power converters.In this work,a new Artificial Neural Network(ANN)is proposed with the Diffusion and Dispersal strategy that works on Maximum Power Point Tracking(MPPT)along with Wind Energy Conversion System(WECS)to minimize electrical faults.The controller focus was not just to increase performance but also to reduce damage owing to any phase to phase fault or Phase to phase to ground fault.To ensure optimal MPPT for the proposed WECS,ANN achieves the optimal PI controller parameters for the indirect control of active and reactive power of DFIG.The optimal allocation and size of the DGs within the distributed system and for MPPT control are obtained using a population of agents.The generated solutions are evaluated and on being successful,the agents test their hypothesis again to create a positive feedback mechanism.Simulations are carried out,and the proposed IoT framework efficiency indicates performance improvement and faster recovery against faults by 9 percent for phase to ground fault and by 7.35 percent for phase to phase fault.

Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system(DGs)that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner(UPQC).In addition to supplying active power to the utility grid,the system of hybrid wind photovoltaic functions as a UPQC,compensating reactive power and suppressing the harmonic load currents.Additionally,the load is supplied with harmonic-free,balanced and regulated output voltages.Since PVWind-UPQC is established on a dual compensation scheme,the series inverter works like a sinusoidal current source,while the parallel inverter works like a sinusoidal voltage source.Consequently,a smooth alteration from interconnected operating modes to island operating modes and vice versa can be achieved without load voltage transients.Since PV-Wind-UPQC inverters handle the energy generated through the hybrid wind photovoltaic system and the energy demanded through the load,the converters should be sized cautiously.A detailed study of the flow of power via the PV-Wind-UPQC is imperative to gain a complete understanding of the system operation and the proper design of the converters.Thus,curves that allow the sizing of the power converters according to the power flow via the converters are presented and discussed.Simulation results are presented to assess both steady state and dynamic performances of the grid connected hybrid system of PV-Wind-UPQC.This investigation is verified by simulating and analyzing the results with Matlab/Simulink.

High Wind Power Penetration Large-Scale Hybrid Renewable Energy System Design for Remote Off-Grid Application

This study looks into the resource assessment, technology economics and modeling of different energy alternatives and proposes a rechargeable battery storage-based large-scale wind/photovoltaic hybrid power system to meet an average electrical load demand of 2.4 MW and peak load of 2.9 MW for a remote rural district in Ethiopia called Geladin. The district is 682 km away from nearby grid. The site enjoys high solar and wind resources that can be harnessed for electric power generation to electrify the community. HOMER simulation software is used for optimal sizing and techno-economic analysis. The diesel generator is used as back up to fill the gaps in case both resources are out. Average monthly solar irradiation data of 6.2 kWh/m2 is determined from measured sunshine duration data by implementing a suitable specific model for the site. NASA satellite based estimated wind speed data of 10 years average at hub height of 50 m for the site in question is extracted from the SWERA (Solar and Wind Energy Resource Assessment) database (with annual average of 6.1 m/s) and its weigh-bull distribution parameter, k of 1.98 is estimated which indicates a fair wind speed distribution of the site to generate electric power using wind turbine. The proposed optimal system results electricity generation indicates that 92% from wind turbine, 3% from photovoltaic, 5% from diesel generator and managed to obtain a much lower cost of energy (COE = 0.11USD/kWh) than other alternatives investigated in this study such as grid extension and diesel generator.

Analysis of Technical Properties of Wind and Solar Photovoltaic Power

Most of electricity power in China comes from coal and hydropower. Already, China must import nearly half of its oil. Concerns about power capacity shortages and air pollution are all adding urgency and pressure to switch to alternative technologies and renewable energy. Among renewable energy sources, wind power and solar photovoltaic power are playing key roles in China, and are the fastest-growing power generation technologies. So this paper focuses on them and analyzes the corresponding technical properties of them. First of all, wind power transforms the kinetic energy from the wind into electricity by using wind turbines. Thus the basic components of wind turbines are described. Wind speed is an important factor to wind energy. So the features of wind speed are analyzed, and the wind energy is calculated. Second, the technical properties of solar photovoltaic power are discussed, including photovoltaic cells and modules, battery, inverter and photovoltaic controller. Photovoltaic energy is also analyzed and calculated. Third, the environmental impacts of wind power and solar photovoltaic power are presented. Finally, the relevant conclusions are drawn.

Performance of a Wind-Diesel Hybrid Power System with STATCOM as a Reactive Power Compensator

The paper deals with automatic reactive power control of an isolated wind-diesel hybrid power system. The power is generated by diesel engine and wind turbine as prime movers with electrical power conversion by permanent-magnet synchronous generator (PMSG) and permanent-magnet induction generator (PMIG) respectively. The mathematical model of the system developed is based on reactive power flow equations. The paper investigates the dynamic performance of the hybrid system for 1% step increase in reactive power load with 1% step increase in input wind power.

Simulation of Dynamic Response of Small Wind-Photovoltaic-Fuel Cell Hybrid Energy System

Renewable energy systems are of importance as being modular, nature-friendly and domestic. Among renewable energy systems, a great deal of research has been conducted especially on photovoltaic effect, wind energy and fuel cell in the recent years. This paper describes dynamic modeling and simulation results of a small wind-photovoltaic-fuel cell hybrid energy system. The hybrid system consists of a 500 W wind turbine, a photovoltaic, a proton exchange membrane fuel cell (PEMFC), ultracapacitors, an electrolyzer, a boost converter, controllers and a power converter that simulated using MATLAB solver. This kind of hybrid system is completely stand-alone, reliable and has high efficiency. In order to minimize sudden variations in voltage magnitude ultracapacitors are proposed. Power converter and inverter are used to produce ac output power. Dynamics of fuel-cell component such as double layer capacitance are also taken into account. Control scheme of fuel-cell flow controller and voltage regulators are based on PID controllers. Dynamic responses of the system for a step change in the electrical load and wind speed are presented. Results showed that the ability of the system in adapting itself to sudden changes and new conditions. Combination of PV and wind renewable sources is made the advantage of using this system in regions which have higher wind speeds in the seasons that suffers from less sunny days and vice versa.

An Optimization Capacity Design Method of Wind/Photovoltaic/Hydrogen Storage Power System Based on PSO-NSGA-II

The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters.To solve the above problem,the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms.Firstly,an integrated energy system consisting of the photovoltaic,wind turbine,electrolysis cell,hydrogen storage tank,and energy storage is established.Meanwhile,the minimum economic cost,the maximum wind and PV power consumption rate,and the minimum load shortage rate are considered to be the objective functions.Then,a hybrid method combined the particle swarm combined with non-dominated sorting genetic algorithms-II is proposed to solve the optimal allocation problem.According to the optimal result,the economic cost is 6.3 million RMB,and the load shortage rate is 9.83%.Finally,four comparative experiments are conducted to verify the superiority-seeking ability of the proposed method.The comparative results indicate that the proposed method possesses a strongermerit-seeking ability,resulting in a solution satisfaction rate of 87.37%,which is higher than that of the unimproved non-dominated sorting genetic algorithms-II.

Reliability Assessment Considering the Coordination of Wind Power, Solar Energy and Energy Storage

风光储联合发电系统并网后必须采取策略与系统之间实现协调调度与运行才可在保证可靠性的前提下最大化利用可再生能源，但现有的可靠性评估中还缺少对大规模风光储联合发电系统协调运行的考虑。针对此问题，基于序贯蒙特卡罗仿真方法，建立了风电、光伏和储能系统的发电可靠性评估模型，并提出了新的协调调度策略。模型综合考虑了风速、太阳光辐照度、环境温度以及2种新能源发电技术的能量变换特性和储能系统的充放电约束等因素。这些模型被应用到IEEERTS79中，通过在Matlab中编制程序进行仿真计算，考察不同的协调运行策略、联合发电系统容量配置以及储能特性对于系统裕度的影响。评估结果可为联合发电系统并网规划与设计提供参考。

Research on the IL-Bagging-DHKELM Short-Term Wind Power Prediction Algorithm Based on Error AP Clustering Analysis

With the continuous advancement of China’s“peak carbon dioxide emissions and Carbon Neutrality”process,the proportion of wind power is increasing.In the current research,aiming at the problem that the forecasting model is outdated due to the continuous updating of wind power data,a short-term wind power forecasting algorithm based on Incremental Learning-Bagging Deep Hybrid Kernel Extreme Learning Machine(IL-Bagging-DHKELM)error affinity propagation cluster analysis is proposed.The algorithm effectively combines deep hybrid kernel extreme learning machine(DHKELM)with incremental learning(IL).Firstly,an initial wind power prediction model is trained using the Bagging-DHKELM model.Secondly,Euclidean morphological distance affinity propagation AP clustering algorithm is used to cluster and analyze the prediction error of wind power obtained from the initial training model.Finally,the correlation between wind power prediction errors and Numerical Weather Prediction(NWP)data is introduced as incremental updates to the initial wind power prediction model.During the incremental learning process,multiple error performance indicators are used to measure the overall model performance,thereby enabling incremental updates of wind power models.Practical examples show the method proposed in this article reduces the root mean square error of the initial model by 1.9 percentage points,indicating that this method can be better adapted to the current scenario of the continuous increase in wind power penetration rate.The accuracy and precision of wind power generation prediction are effectively improved through the method.

An optimal strategy for coordinating and dispatching “source-load” in power system based on multiple time scales

Due to the phenomenon of abandoning wind power and photo voltage(PV)power in the“Three Northern Areas”in China,this paper presents an optimal strategy for coordinating and dispatching“source-load”in power system based on multiple time scales.On the basis of the analysis of the uncertainty of wind power and PV power as well as the characteristics of load side resource dispatching,the optimal model of coordinating and dispatching“source-load”in power system based on multiple time scales is established.It can simultaneously and effectively dispatch conventional generators,wind plant,PV power station,pumped-storage power station and load side resources by optimally using three time scales:day-ahead,intra-day and real-time.According to the latest predicted information of wind power,PV power and load,the original generation schedule can be rolled and amended by using the corresponding time scale.The effectiveness of the model can be verified by a real system.The simulation results show that the proposed model can make full use of“source-load”resources to improve the ability to consume wind power and PV power of the grid-connected system.

Sliding Mode Controller for Three-Phase Hybrid Active Power Filter with Photovoltaic Application

This paper presents a new three-phase hybrid active power filter configuration that interconnects a passive high-pass filter in parallel with an active power filter and a photovoltaic system. The proposed configuration can improves the filtering performance of the conventional active power filter, as well as simultaneously supply the power from the photovoltaic arrays to the load and utility. This paper will describe the proposed hybrid active power filter control using sliding mode with photovoltaic system. The proposed technique effectively filters harmonics under 1 kHz but also higher frequency to achieve wideband harmonics compensation. The THD of source current is reduced from 30.09% to 1.95%. The result indicates that the sliding mode controller can track the reference signals and have good dynamic characteristics.

A Novel Serial Hybrid Three-level NPC Topology for Multi-MW Medium Voltage Wind Power Converters

提出一种新型的串联混合三电平中点钳位（neutralpoint clamped,NPC）拓扑,该拓扑是基于传统三电平NPC拓扑的改进和优化,引入大功率IGBT的串联应用。该新型拓扑中,桥臂的两个外管分别用两个低压IGBT串联,两个内管均用高压IGBT。在多兆瓦级中压风电变流器中,大功率IGBT的开关损耗很大,从而限制了开关频率。提出的新型拓扑通过低压IGBT的串联来减小功率器件的损耗,从而提高开关频率,同时可减小输出滤波器的尺寸。通过传统三电平拓扑和新型串联混合三电平拓扑IGBT损耗的对比,说明新拓扑的优势。通过改变门极驱动电阻实现串联IGBT的均压,对新拓扑的应用具有重大意义。最后通过新拓扑的单相样机验证新拓扑的正确性和可行性。

Direct driven wind energy conversion system based on hybrid excitation synchronous machine

A novel direct-drive type wind power generation system based on hybrid excitation synchronous machine（HESM）is introduced in this paper.The generator is connected to an uncontrollable rectifier,and a fully controlled voltage-sourceinverter is used to connect the system to utility grid.An intermediate DC bus exists between the rectifier and inverter.A new control strategy is proposed which achieves the maximum power point tracking（MPPT） with the control of excitation current of HESM and stabilizes the DC link voltage with the control of inverter output current simultaneously.Specially-designed buck circuit is used to control the excitation current of HESM,and grid voltage-oriented vector control strategy is employed to realize the decoupling of the inverter output power.Simulation results and experiment in 3 kW lab prototype show an excellent static and dynamic performance of the proposed system.

Frequency Control Approach and Load Forecasting Assessment for Wind Systems

Frequency deviation has to be controlled in power generation units when there arefluctuations in system frequency.With several renewable energy sources,wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature.Whenever there is a mismatch between generation and demand,the frequency deviation may arise from the actual frequency 50 Hz(in India).To mitigate the frequency deviation issue,it is necessary to develop an effective technique for better frequency control in wind energy systems.In this work,heuristic Fuzzy Logic Based Controller(FLC)is developed for providing an effective frequency control support by modeling the complex behavior of the system to enhance the load forecasting in wind based hybrid power systems.Frequency control is applied to reduce the frequency deviation due tofluctuations and load prediction information using ANN(Artificial Neural Network)and SVM(Support Vector Machine)learning models.The performance analysis of the proposed method is done with different machine learning based approaches.The forecasting assessment is done over various climates with the aim to decrease the prediction errors and to demote the forecasting accuracy.Simulation results show that the Mean Absolute Percentage Error(MAPE),Root Mean Square Error(RMSE)and Normalized Mean Absolute Error(NMAE)values are scaled down by 41.1%,9.9%and 23.1%respectively in the proposed method while comparing with existing wavelet and BPN based approach.

Hybrid Power System Options for Off-Grid Rural Electrification in Northern Kenya

For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emissions, which adversely affect the environment and increase diesel fuel prices, which inflate the prices of consumer goods. The Kenya government has taken steps towards addressing this issue by proposing The Hybrid Mini-Grid Project, which involves the installation of 3 MW of wind and solar energy systems in facilities with existing diesel generators. However, this project has not yet been implemented. As a contribution to this effort, this study proposes, simulates and analyzes five different configurations of hybrid energy systems incorporating wind energy, solar energy and battery storage to replace the stand-alone diesel power systems servicing six remote villages in northern Kenya. If implemented, the systems proposed here would reduce Kenya’s dependency on diesel fuel, leading to reductions in its carbon footprint. This analysis confirms the feasibility of these hybrid systems with many configurations being profitable. A Multi-Attribute Trade-Off Analysis is employed to determine the best hybrid system configuration option that would reduce diesel fuel consumption and jointly minimize CO2 emissions and net present cost. This analysis determined that a wind-diesel-battery configuration consisting of two 500 kW turbines, 1200 kW diesel capacity and 95,040 Ah battery capacity is the best option to replace a 3200 kW stand-alone diesel system providing electricity to a village with a peak demand of 839 kW. It has the potential to reduce diesel fuel consumption and CO2 emissions by up to 98.8%.