Multi-Lever EarlyWarning forWind and Photovoltaic Power Ramp Events Based on Neural Network and Fuzzy Logic

With the increasing penetration of renewable energy in power system,renewable energy power ramp events(REPREs),dominated by wind power and photovoltaic power,pose significant threats to the secure and stable operation of power systems.This paper presents an early warning method for REPREs based on long short-term memory(LSTM)network and fuzzy logic.First,the warning levels of REPREs are defined by assessing the control costs of various power control measures.Then,the next 4-h power support capability of external grid is estimated by a tie line power predictionmodel,which is constructed based on the LSTMnetwork.Finally,considering the risk attitudes of dispatchers,fuzzy rules are employed to address the boundary value attribution of the early warning interval,improving the rationality of power ramp event early warning.Simulation results demonstrate that the proposed method can generate reasonable early warning levels for REPREs,guiding decision-making for control strategy.

Power Ramping Schemes for M2M and H2H Co-existing Scenario

To analyze and reduce the impact of Machine-to-Machine (M2M) Devices (MDs) on the traditional Human-to-Human (H2H) users for the blending scenario, where both M2M and H2H services coexist in the current Universal Mobile Telecommunication System (UMTS) and perform the Random Access (RA) procedure simultaneously, a comprehensive RA analysis model of RA is proposed in this paper. Further, a power ramping strategy based on the logarithm for M2M is proposed. The efficiency of both the existing and proposed scheme is assessed through a simulation across several metrics, including average target power, throughput, blocking probability, and delay statistics. Numerical results show that the proposed algorithm can ensure a minimal impact on H2H communication while maintaining the throughput of the M2M communication. Meanwhile, because of its low energy consumption, this algorithm has a significant guide value for real-world applications.

A Review of State-of-the-art Flexible Power Point Tracking Algorithms in Photovoltaic Systems for Grid Support:Classification and Application

To maximize conversion efficiency,photovoltaic(PV)systems generally operate in the maximum power point tracking(MPPT)mode.However,due to the increasing penetra tion level of PV systems,there is a need for more developed control functions in terms of frequency support services and voltage control to maintain the reliability and stability of the power grid.Therefore,flexible active power control is a manda tory task for grid-connected PV systems to meet part of the grid requirements.Hence,a significant number of flexible pow er point tracking(FPPT)algorithms have been introduced in the existing literature.The purpose of such algorithms is to real ize a cost-effective method to provide grid support functional ities while minimizing the reliance on energy storage systems.This paper provides a comprehensive overview of grid support functionalities that can be obtained with the FPPT control of PV systems such as frequency support and volt-var control.Each of these grid support functionalities necessitates PV sys tems to operate under one of the three control strategies,which can be provided with FPPT algorithms.The three control strate gies are classified as:①constant power generation control(CP GC),②power reserve control(PRC),and③power ramp rate control(PRRC).A detailed discussion on available FPPT algo rithms for each control strategy is also provided.This paper can serve as a comprehensive review of the state-of-the-art FPPT algorithms that can equip PV systems with various grid support functionalities.

基于爬坡特征与改进PRAA的深远海风电功率短期预测研究

深远海海域情况复杂,海面风速极易受海洋中尺度事件影响。所造成的异常数据点和Bump事件将导致爬坡检测准确率下降,影响深远海风电功率短期预测精度。因此,提出了一种同时考虑爬坡事件以及深远海气象因素的深远海风电功率短期预测方法。首先,设计基于状态标记和滑动窗口改进的参数和分辨率自适应算法(parameter and resolution adaptive algorithm,PRAA)实现爬坡事件检测并完成特征量提取;其次,分析深远海风速、风向及温度等多因素关联关系,扩充深远海气象因素特征样本维度,并通过主成分分析法(principal component analysis,PCA)深度挖掘潜在特征;最后,基于某海上风电场的实测数据,采用考虑爬坡和深远海气象因素的轻量梯度提升机(light gradient boosting machine,LightGBM)算法完成深远海风电功率的短期预测,仿真结果验证了所提方法的有效性。

联合储能系统提升机组快速爬坡能力研究

针对"火电灵活性改造试点项目"目标要求的提升机组爬坡能力开展研究。首先,结合试验结果分析了现有火电机组具备的AGC响应能力,其与预期目标之间仍存在一定的差距。在对机组协调优化控制技术、基于机组自身蓄能的负荷调节技术和基于储能的负荷调节技术进行分析论述的基础上,提出利用联合储能系统提升机组AGC响应能力,并对其运行特点、热力特性、项目投资等进行了分析。联合储能系统可实现与纯电池储能方案接近的调节品质,具有投资较低、安全性更高等特点,值得推广。

Statistical scenarios forecasting method for wind power ramp events using modified neural networks

Wind power ramp events increasingly affect the integration of wind power and cause more and more problems to the safety of power grid operation in recent years.Several forecasting techniques for wind power ramp events have been reported.In this paper,the statistical scenarios forecasting method is proposed for wind power ramp event probabilistic forecasting based on the probability generating model.Multi-objective fitness functions are established considering cumulative density functions and higher order moment autocorrelation functions with respect to the consistency of distribution and timing characteristics,respectively.Parameters of probability generating model are calculated by the iterative optimization using the modified genetic algorithm with multi-objective fitness functions.A number of statistical scenarios captured bands are generated accordingly.Eventually,ramp event probability characteristics are detected from scenarios captured bands to evaluate the ramp event forecasting method.A wind plant of Bonneville Power Administration with actual wind power data is selected for calculation and statistical analysis.It is shown that statistical results with multi-objective functions are more accurate than the results with single objective functions.Moreover,the statistical scenarios forecasting method can accurately estimate the characteristics of wind power ramp events.The results verify that the proposed method can guide the generation method of statistical scenarios and forecasting models for ramp events.

Bayesian Network Based Imprecise Probability Estimation Method for Wind Power Ramp Events

Although wind power ramp events(WPREs)are relatively scarce,they can inevitably deteriorate the stability of power system operation and bring risks to the trading of electricity market.In this paper,an imprecise conditional probability estimation method for WPREs is proposed based on the Bayesian network(BN)theory.The method uses the maximum weight spanning tree(MWST)and greedy search(GS)to build a BN that has the highest fitting degree with the observed data.Meanwhile,an extended imprecise Dirichlet model(IDM)is developed to estimate the parameters of the BN,which quantificationally reflect the ambiguous dependencies among the random ramp event and various meteorological variables.The BN is then applied to predict the interval probability of each possible ramp state under the given meteorological conditions,which is expected to cover the target probability at a specified confidence level.The proposed method can quantify the uncertainty of the probabilistic ramp event estimation.Meanwhile,by using the extracted dependencies and Bayesian rules,the method can simplify the conditional probability estimation and perform reliable prediction even with scarce samples.Test results on a real wind farm with three-year operation data illustrate the effectiveness of the proposed method.

池式钠冷快堆DCS优化对SBO事故安全影响的研究

池式钠冷快堆技术在我国快速发展。随着相关技术发展和工程经验的积累,为了在保障机组安全运行的基础上提升全寿期经济性,在新建快堆项目上以“集中显示、分布控制”技术思路为指引,对分布式控制系统(DCS)架构进行优化,以压缩DCS规模和相关电缆用量。对DCS的支持系统--交流不间断电源(UPS)和机柜间通风系统同步进行了优化,提升了DCS电源保障程度。优化通风系统运行方式并核算确认事故条件下环境温度满足DCS机柜运行要求。基于快堆固有安全性,分析上述优化内容对机组全厂断电(SBO)工况下的反应堆安全功能的影响,确保反应堆、人员、环境的安全。研究成果应用于池式钠冷快堆的新建项目,压缩了DCS整体成本,为同类堆型的DCS架构设计及相关安全影响分析提供参考。

Improved Method of Contention-Based Random Access in LTE System

Random access is the necessary process to establish the wireless link between the user equipment （UE） and network. The performance of the random access directly affects the performance of the network. In this work, we propose a method on the basis of the existing alternatives. In this method, we estimate the system load in advance to adjust the number of terminals. An access threshold is set to control the number of terminals which want to access the base station at an acceptable level. At the same time, we havean improvement on the existing power climbing strategy. We suppose that the power ramping is not always necessary for the re-access. And the selection ofpower ramping steps is studied in this paper. Simulations based on MATLAB are employed to evaluate the effectiveness of the proposed solution and to make comparisons with existing alternatives.

5G波束调整优先策略的网络侧干预方案研究

5G随机接入中,第一次波束失败后UE终端可以选择再次发起随机接入。再次随机接入时可以选择更换新的波束进行接入,也可以选择对原波束进行功率攀升调整后随机接入。但是优先采用哪一种策略,5G标准协议并没有进行规定,所以其优先策略完全由UE自主决定,网络侧无法参与。不同的场景下因地制宜地采用不同的策略其效果是完全不同的,因此再次随机接入的优先策略必须依场景的不同而不同。本文正是基于该目的,通过对随机接入过程和原理的分析,结合空口信息的内容,提出网络侧利用MIB消息中的闲置的比特对UE的随机接入波束调整策略进行事先干预,指示UE终端调整波束调整优先策略,从而使得UE终端能更快更好地接入网络,同时提高随机接入成功率。

Use of a New Algorithm with an Internally Cooled Electrode for Radiofrequency Ablation of Small Hepatocellular Carcinomas

Purpose: To investigate the efficacy of a new algorithm to increase the volume of tissue ablation via gradual ramp-up of power using an internally cooled electrode for ablating hepatomas 3 cm or less. Materials and Methods: 44 patients with 62 hepatomas were treated from March 4, 2004 to May 24, 2009. Ablation with a gradual ramp-up of power was performed using a single needle with an internally cooled electrode. Evaluation for tumor response was performed with 4-phase CT at 24 hours and 3 months. All immediate and follow-up complications were recorded. Results: Complete tumor ablation was achieved in 86%. The ablation volumes were 16 cm3 +/- 12 cm3 for tumors 3 +/- 12 cm3 for tumors 2 - 3 cm. Out of 68 total ablation sessions, there were 2 major complications (pleural effusions) requiring intervention (thoracentesis). Conclusion: Compared with existing techniques using a constant full-power setting, ablation of small hepatomas using an algorithm of gradual ramp-up of power provides comparable rate of complete tumor ablation, adequate ablation volumes, and a low rate of complications that require treatment.

Wind Power Generation Variations and Aggregations

Climate and weather-propelled wind power is characterized by significant spatial and temporal variability.It has been substantiated that the variability of wind power,in addition to contributing hugely to the instability of power grids,can also send the balancing costs of electricity markets soaring.Existing studies on the same establish that curtailment of such variability can be achieved through the geographic aggregation of various widespread production sites;however,there exists a dearth of comprehensive evaluation concerning different levels/scales of such aggregation,especially from a global perspective.This paper primarily offers a fundamental understanding of the relationship between the wind power variations and aggregations from a systematic viewpoint based on extensive wind power data,thereby enabling the benefits of these aggregations to be quantified from a state scale ranging up to a global scale.Firstly,a meticulous analysis of the wind power variations is undertaken at 6 different levels by converting the 7-year hourly meteorological re-analysis data with a high spatial resolution of 0.25◦×0.25◦(approximate 28 km×28 km)into a wind power series globally.Subsequently,the proposed assessment framework employs a coefficient of variation of wind power as well as a standard deviation of wind power ramping rate to quantify the variations of wind power and wind power ramping rate to exhibit the characteristics and benefits yielded by the wind power aggregation at 6 different levels.A system planning example is adopted to illustrate the correlation between the coefficient of variation reduction of wind power and investment reduction,thereby emphasizing the benefits pertaining to significant investment reduction via aggregation.Furthermore,a wind power duration curve is used to exemplify the availability of wind power aggregated at different levels.Finally,the results provide insights into devising a universal approach towards the deployment of wind power,principally along the lines of Net-Zero.