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。

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.

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.

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 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.

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.

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。

Unit Commitment under the Environment of Wind Power and Large-Scale Bilateral Transactions

Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considering the executive priority of different power components to establish a multi-objective coordination unit commitment model. Through an example to verify the effectiveness of the model in promoting wind power consumption, guaranteeing trade execution, and improving power generation efficiency, and analyzed the interactions to each other among the factors of wind power, trading and blocking. According to the results, when wind power causes reverse power flow in the congestion line, it will promote the implementation of contracts, the influence of wind power accommodation to trade execution should be analyzed combined with the grid block, the results can provide reference for wind power planning.

Coordinated control strategy for wind power accommodation based on electric heat storage and pumped storage

To solve the severe problem of wind power curtailment in the winter heating period caused by ＂power determined by heat＂ operation constraint of cogeneration units, this paper analyzes thermoelectric load, wind power output distribution and fluctuation characteristics at different time scales, and finally proposes a two level coordinated control strategy based on electric heat storage and pumped storage. The optimization target of the first level coordinated control is the lowest operation cost and the largest wind power utilization rate. Based on prediction of thermoelectric load and wind power, the operation economy of the system and wind power accommodation level are improved with the cooperation of electric heat storage and pumped storage in regulation capacity. The second level coordinated control stabilizes wind power real time fluctuations by cooperating electric heat storage and pumped storage in control speed. The example results of actual wind farms in Jiuquan, Gansu verifies the feasibility and effectiveness of the proposed coordinated control strategy.

Analysis on the Influence Factors of Wind Power Accommodation

With the increase of wind power capacity in China, the situation of curtailment of wind power is getting worse. An annual sequence production simulation model is established with maximum wind power consumption as the objective function. The calculation of specific power grid operation in 2013 verifies the precision of this model. The impact of different factors on wind power accommodation as well as the impact of power grid reserve, wind resources and load on wind power curtailment is analyzed. The calculation results quantify the impact of different factors from power system to the accommodation of wind power and provide reference to solving the problem of wind power curtailment.

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.

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.

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.

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.

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.

Comprehensive evaluation model of wind power accommodation ability based on macroscopic and microscopic indicators

This article explores and establishes comprehensive evaluation index system of wind power accommodation ability considering microscopic index and macroscopic index, and the index system includes conventional evaluation indexes such as forecast deviation, simultaneity factor and anti-peak rate, also newly introduced evaluation indexes such as installed capacity, power adequacy and accommodation space. Bayesian weight modified method is used for solving index weights of 8 wind power accommodation indexes. The paper puts forward a comprehensive evaluation model of wind power accommodation ability based on improved radar chart method, and this model changes traditional radar chart fan-shaped sector to quadrilateral evaluation region, and increasing angle bisector can solve the problem that evaluation results are not unique. It constructs new area and perimeter vectors of radar chart, which make the evaluation results give consideration to level of aggregation and balance degree of evaluation objectives, and case study results show that this model has a certain practical value.

Nash-Q learning-based collaborative dispatch strategy for interconnected power systems

The large-scale utilization and sharing of renewable energy in interconnected systems is crucial for realizing"instrumented,interconnected,and intelligent"power grids.The traditional optimal dispatch method can not coordinate the economic benefits of all the stakeholders from multiple regions of the transmission network,comprehensively.Hence,this study proposes a large-scale wind-power coordinated consumption strategy based on the Nash-Q method and establishes an economic dispatch model for interconnected systems considering the uncertainty of wind power,with optimal windpower consumption as the objective for redistributing the shared benefits between regions.Initially,based on the equivalent cost of the interests of stakeholders from different regions,the state decision models are respectively constructed,and the noncooperative game Nash equilibrium model is established.The Q-learning algorithm is then introduced for high-dimension decision variables in the game model,and the dispatch solution methods for interconnected systems are presented,integrating the noncooperative game Nash equilibrium and Q-learning algorithm.Finally,the proposed method is verified through the modified IEEE 39-bus interconnection system,and it is established that this method achieves reasonable distribution of interests between regions and promotes large-scale consumption of wind power.