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.

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.

Optimal Scheduling Strategy of Source-Load-Storage Based onWind Power Absorption Benefit

In recent years,the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing,but the peak regulation capacity of the power grid in the three north regions of China is limited,resulting in insufficient local wind power consumption capacity.Therefore,this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid’s wind power consumption capacity.The objective of the uppermodel is tominimize the peak-valley difference of the systemload,which ismainly to optimize the system load by using the demand response resources,and to reduce the peak-valley difference of the system load to improve the peak load regulation capacity of the grid.The lower scheduling model is aimed at maximizing the system operation benefit,and the scheduling model is selected based on the rolling schedulingmethod.The load-side schedulingmodel needs to reallocate the absorbed wind power according to the response speed,absorption benefit,and curtailment penalty cost of the two DR dispatching resources.Finally,the measured data of a power grid are simulated by MATLAB,and the results show that:the proposed strategy can improve the power grid’s wind power consumption capacity and get a large wind power consumption benefit.

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。

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.

Application of Power Electronics Converters in Renewable Energy

Against the backdrop of global energy shortages and increasingly severe environmental pollution,renewable energy is gradually becoming a significant direction for future energy development.Power electronics converters,as the core technology for energy conversion and control,play a crucial role in enhancing the efficiency and stability of renewable energy systems.This paper explores the basic principles and functions of power electronics converters and their specific applications in photovoltaic power generation,wind power generation,and energy storage systems.Additionally,it analyzes the current innovations in high-efficiency energy conversion,multilevel conversion technology,and the application of new materials and devices.By studying these technologies,the aim is to promote the widespread application of power electronics converters in renewable energy systems and provide theoretical and technical support for achieving sustainable energy development.

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.

Effect of photovoltaic panel electric field on the wind speed required for dust removal from the panels

Methods to remove dust deposits by high-speed airflow have significant potential applications,with optimal design of flow velocity being the core technology.In this paper,we discuss the wind speed required for particle removal from photovoltaic(PV)panels by compressed air by analyzing the force exerted on the dust deposited on inclined photovoltaic panels,which also included different electrification mechanisms of dust while it is in contact with the PV panel.The results show that the effect of the particle charging mechanism in the electric field generated by the PV panel is greatly smaller than the effect of the Van der Waals force and gravity,but the effect of the particle charged by the contact electrification mechanism in the electrostatic field is very pronounced.The wind speed required for dust removal from the PV panel increases linearly with the PV panel electric field,so we suggest that the nighttime,when the PV electric field is relatively small,would be more appropriate time for dust removal.The above results are of great scientific importance for accurately grasping the dust distribution law and for achieving scientific removal of dust on PV panels.

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.

Simulation Study of Three Types of Distributed Power Based on EMTDC

In order to analyze the performances of directly-driven permanent magnet synchronous generator wind turbine (PMSG) connecting to the grid, photovoltaic array and microtubine, dynamic models of them are established. The validity of the established models and proposed control strategies are demonstrated by simulation system under the software package PSCAD/EMTDC.

Coordinated voltage control of renewable energy power plants in weak sending-end power grid

The utilization of renewable energy in sending-end power grids is increasing rapidly,which brings difficulties to voltage control.This paper proposes a coordinated voltage control strategy based on model predictive control(MPC)for the renewable energy power plants of wind and solar power connected to a weak sending-end power grid(WSPG).Wind turbine generators(WTGs),photovoltaic arrays(PVAs),and a static synchronous compensator are coordinated to maintain voltage within a feasible range during operation.This results in the full use of the reactive power capability of WTGs and PVAs.In addition,the impact of the active power outputs of WTGs and PVAs on voltage control are considered because of the high R/X ratio of a collector system.An analytical method is used for calculating sensitivity coefficients to improve computation efficiency.A renewable energy power plant with 80 WTGs and 20 PVAs connected to a WSPG is used to verify the proposed voltage control strategy.Case studies show that the coordinated voltage control strategy can achieve good voltage control performance,which improves the voltage quality of the entire power plant.

Test Facility for Low Potential Pumped Storage Power Plants and Hydrokinetic Turbines

The electric energy which is generated by wind power plants depends on the wind speed and exceeds with strong permissible wind speed the electric energy requirements of the country. In order not to reduce this electrical energy, it must be stored. The sensible energy storage is currently the pumped storage power plants. As the mountain ranges for conventional pumped storage power plants with drop heights of H 〉 600 m are strictly limited, the development of low potential pumped storage power plants has begun. Increasing the capacity of pumped storage power plants with regard to the wind power plants is urgently needed. In this paper, it is shown using the example of an unneeded port facility, how a port facility can be used after low conversion as a test facility for low potential pumped storage power plants and at the same time for the testing of hydro-kinetic turbines. This type of pump storage power plants does not save the energy due to large drop heights, but primarily due to the large volume flow of water.

Capacity-operation collaborative optimization of the system integrated with wind power/photovoltaic/concentrating solar power with S-CO_(2) Brayton cycle

This paper proposes a new power generating system that combines wind power(WP),photovoltaic(PV),trough concentrating solar power(CSP)with a supercritical carbon dioxide(S-CO_(2))Brayton power cycle,a thermal energy storage(TES),and an electric heater(EH)subsystem.The wind power/photovoltaic/concentrating solar power(WP-PV-CSP)with the S-CO_(2) Brayton cycle system is powered by renewable energy.Then,it constructs a bi-level capacity-operation collaborative optimization model and proposes a non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)nested linear programming(LP)algorithm to solve this optimization problem,aiming to obtain a set of optimal capacity configurations that balance carbon emissions,economics,and operation scheduling.Afterwards,using Zhangbei area,a place in China which has significant wind and solar energy resources as a practical application case,it utilizes a bi-level optimization model to improve the capacity and annual load scheduling of the system.Finally,it establishes three reference systems to compare the annual operating characteristics of the WP-PV-CSP(S-CO_(2))system,highlighting the benefits of adopting the S-CO_(2) Brayton cycle and equipping the system with EH.After capacity-operation collaborative optimization,the levelized cost of energy(LCOE)and carbon emissions of the WP-PV-CSP(S-CO_(2))system are decreased by 3.43%and 92.13%,respectively,compared to the reference system without optimization.

Assessment of wind and photovoltaic power potential in China

Decarbonization of the energy system is the key to China’s goal of achieving carbon neutrality by 2060.However,the potential of wind and photovoltaic(PV)to power China remains unclear,hindering the holistic layout of the renewable energy development plan.Here,we used the wind and PV power generation potential assessment system based on the Geographic Information Systems(GIS)method to investigate the wind and PV power generation potential in China.Firstly,the high spatial-temporal resolution climate data and the mainstream wind turbines and PV modules,were used to assess the theoretical wind and PV power generation.Then,the technical,policy and economic(i.e.,theoretical power generation)constraints for wind and PV energy development were comprehensively considered to evaluate the wind and solar PV power generation potential of China in 2020.The results showed that,under the current technological level,the wind and PV installed capacity potential of China is about 56.55 billion kW,which is approximately 9 times of those required under the carbon neutral scenario.The wind and PV power generation potential of China is about 95.84 PWh,which is approximately 13 times the electricity demand of China in 2020.The rich areas of wind power generation are mainly distributed in the western,northern,and coastal provinces of China.While the rich areas of PV power generation are mainly distributed in western and northern China.Besides,the degree of tapping wind and PV potential in China is not high,and the installed capacity of most provinces in China accounted for no more than 1%of the capacity potential,especially in the wind and PV potential-rich areas.

Jointly improving energy efficiency and smoothing power oscillations of integrated offshore wind and photovoltaic power: a deep reinforcement learning approach

This paper proposes a novel deep reinforcement learning(DRL)control strategy for an integrated offshore wind and photovoltaic(PV)power system for improving power generation efficiency while simultaneously damping oscilla-tions.A variable-speed offshore wind turbine(OWT)with electrical torque control is used in the integrated offshore power system whose dynamic models are detailed.By considering the control system as a partially-observable Markov decision process,an actor-critic architecture model-free DRL algorithm,namely,deep deterministic policy gradient,is adopted and implemented to explore and learn the optimal multi-objective control policy.The potential and effectiveness of the integrated power system are evaluated.The results imply that an OWT can respond quickly to sudden changes of the inflow wind conditions to maximize total power generation.Significant oscillations in the overall power output can also be well suppressed by regulating the generator torque,which further indicates that complementary operation of offshore wind and PV power can be achieved.

Performance Analysis of Grid Connected and Islanded Modes of AC/DC Microgrid for Residential Home Cluster

This paper presents performance analysis on hybrid AC/DC microgrid networks for residential home cluster. The design of the proposed microgrid includes comprehensive types of Distributed Generators (DGs) as hybrid power sources (wind, Photovoltaic (PV) solar cell, battery, fuel cell). Details about each DG dynamic modeling are presented and discussed. The customers in home cluster can be connected in both of the operating modes: islanded to the microgrid or connected to utility grid. Each DG has appended control system with its modeling that will be discussed to control DG performance. The wind turbine will be controlled by AC control system within three sub-control systems: 1) speed regulator and pitch control, 2) rotor side converter control, and 3) grid side converter control. The AC control structure is based on PLL, current regulator and voltage booster converter with using of photovoltaic Voltage Source Converter (VSC) and inverters to connect to the grid. The DC control system is mainly based on Maximum Power Point Tracking (MPPT) controller and boost converter connected to the PV array block and in order to control the system. The case study is used to analyze the performance of the proposed microgrid. The buses voltages, active power and reactive power responses are presented in both of grid-connected and islanded modes. In addition, the power factor, Total Harmonic Distortion (THD) and modulation index are calculated.

Wind and Photovoltaic Power Time Series Data Aggregation Method Based on an Ensemble Clustering and Markov Chain

Reducing the input wind and photovoltaic power time series data can improve the efficiency of time sequential simulations.In this paper,a wind and photovoltaic power time series data aggregation method based on an ensemble clustering and Markov chain(ECMC)is proposed.The ECMC method can effectively reduce redundant information in the data.First,the wind and photovoltaic power time series data were divided into scenarios,and ensemble clustering was used to cluster the divided scenarios.At the same time,the Davies-Bouldin Index(DBI)is adopted to select the optimal number of clusters.Then,according to the temporal correlation between wind and photovoltaic scenarios,the wind and photovoltaic clustering results are merged and reduced to form a set of combined typical day scenarios that can reflect the characteristics of historical data within the calculation period.Finally,based on the Markov Chain,the state transition probability matrix of various combined typical day scenarios is constructed,and the aggregation state sequence of random length is generated,and then,the combined typical day scenarios of wind and photovoltaic were sampled in a sequential one-way sequence according to the state sequence and then are built into a representative wind and photovoltaic power time series aggregation sequence.A provincial power grid was chosen as an example to compare the multiple evaluation indexes of different aggregation methods.The results show that the ECMC aggregation method improves the accuracy and efficiency of time sequential simulations.

Modelselection,adaptation,and combination for transfer learning in wind and photovoltaic power forecasts

There is recent interest in using model hubs–a collection of pre-trained models–in computer vision tasks.To employ a model hub,we first select a source model and then adapt the model for the target to compensate for differences.There still needs to be more research on model selection and adaption for renewable power forecasts.In particular,none of the related work examines different model selection and adaptation strategies for neural network architectures.Also,none of the current studies investigates the influence of available training samples and considers seasonality in the evaluation.We close these gaps by conducting the first thorough experiment for model selection and adaptation for transfer learning in renewable power forecast,adopting recent developments from the field of computer vision on 667 wind and photovoltaic parks from six datasets.We simulate different amounts of training samples for each season to calculate informative forecast errors.We examine the marginal likelihood and forecast error for model selection for those amounts.Furthermore,we study four adaption strategies.As an extension of the current state of the art,we utilize a Bayesian linear regression for forecasting the response based on features extracted from a neural network.This approach outperforms the baseline with only seven days of training data and shows that fine-tuning is not beneficial with less than three months of data.We further show how combining multiple models through ensembles can significantly improve the model selection and adaptation approach such that we have a similar mean error with only 30 days of training data which is otherwise only possible with an entire year of training data.We achieve a mean error of 9.8 and 14 percent for the most realistic dataset for PV and wind with only seven days of training data.