“Section to Point” Correction Method for Wind Power Forecasting Based on Cloud Theory

As an intermittent energy, wind power has the characteristics of randomness and uncontrollability. It is of great significance to improve the accuracy of wind power forecasting. Currently, most models for wind power forecasting are based on wind speed forecasting. However, it is stuck in a dilemma called “garbage in, garbage out,” which means it is difficult to improve the forecasting accuracy without improving the accuracy of input data such as the wind speed. In this paper, a new model based on cloud theory is proposed. It establishes a more accurate relational model between the wind power and wind speed, which has lots of catastrophe points. Then, combined with the trend during adjacent time and the laws of historical data, the forecasting value will be corrected by the theory of “section to point” correction. It significantly improves the stability of forecasting accuracy and reduces significant forecasting errors at some particular points. At last, by analyzing the data of generation power and historical wind speed in Inner Mongolia, China, it is proved that the proposed method can effectively improve the accuracy of wind speed forecasting

Research on Optimal Allocation of Multi-Energy Complementary Project of Wind-Solar-Thermal Integration

Multi-energy complementary project of wind-solar-thermal integration can play a coordinating and mutually beneficial role among different generations, and is one of the implementation paths for safe and efficient use of renewable energy, and achieving carbon neutrality and carbon peak. How to reasonably match the installed capacity of thermal power, wind power, photovoltaic power and the transmission capacity, to ensure the full consumption and efficient utilization of wind power and photovoltaic power, is the core issue of the multi-energy complementary project of wind-solar-thermal integration. Based on the analysis of the output characteristics and multi-energy complementary characteristics of different generations, an optimal allocation model of multi-energy complementary project of wind-solar-thermal integration was constructed with the objective of minimizing the total cost and maximizing the matching degree between the sending curve and the receiving load curve. The installed capacity of wind power, photovoltaic power and the transmission capacity were optimized at the planning level, and the thermal power operation mode, output curve and transmission curve were optimized at the operation level. According to the case analysis, the optimal allocation model can optimize and determine the installed capacity of wind power, photovoltaic power and the transmission capacity, so that different generations can coordinate with each other on monthly and daily time scales. The transmission curve is more friendly to the receiving-end grid, and the horizontal multi-energy complementary and longitudinal generation-load coordination are realized

Review of Power System Prediction Technologies Based on Large Language Models

ObjectivesWith the large-scale integration of renewable energy, new-type power systems require greater flexibility and higher prediction accuracy for prediction technology. Traditional prediction methods have limitations in handling dynamic and complex scenarios, highlighting the need for prediction technologies tailored to these systems. Large language models (LLMs), as generative artificial intelligence technologies, have capabilities in multimodal data integrating, few-shot learning, and multitask handling, enabling more intelligent and precise solutions for the prediction of power systems. Therefore, this study focuses on analyzing the current applications and advantages of LLMs in power system prediction.MethodsFirst, the fundamental architecture, training methods, and current application status of LLMs are discussed. Then, their principles and implementations in prediction are explained, with emphasis on advantages and prospects in load prediction, renewable generation prediction, and electricity price prediction. Finally, challenges in LLM-based prediction applications are analyzed from three aspects: data quality management, privacy protection, and computational resources, and feasible solutions are proposed.ConclusionsThrough comparative analysis of various forecasting tasks, LLMs demonstrate superior capabilities in few-shot learning and multimodal data processing compared to traditional methods, making them more adaptable to complex and variable prediction scenarios. Effective application of LLMs can provide innovative solutions for electricity market prediction

Electrodiagnostic evaluation of carpal tunnel syndrome

Carpal tunnel syndrome (CTS) is the most common nerve entrapment. Electrodiagnostic (EDX) studies are a valid and reliable means of confirming the diagnosis. This monograph addresses the various EDX techniques used to evaluate the median nerve at the wrist. It also demonstrates the limitations of EDX studies with a focus on the sensitivity and specificity of EDX testing for CTS. The need to use reference values for populations such as diabetics and active workers, where normative values differ from conventional cutoffs used to confirm suspected CTS, is presented. The value of needle electromyography (EMG) is examined. Muscle Nerve, 2011Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87013/1/22208_ftp.pd

The preaching of Hugh Latimer A reappraisal

SIGLEAvailable from British Library Document Supply Centre- DSC:D172904 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

This is Your Brain on Football: Making Sense of Parents' Decision to Allow Their Child to Play Tackle Football

Parents make decisions on behalf of their children on a daily basis. Some parents in the United States face the unique decision of whether or not to allow football participation for their child at a very young age. Using sensemaking theory, I examined how parents assessed the risks involved in making the decision to allow their child to play tackle football. I interviewed 24 participants in the form of 12 parental couples who had children playing middle school football and coded their responses to identify themes and strategies for risk assessment. Themes that emerged were decision-agency (parent and child agency), risk assessment (downplaying risk, acknowledgement of risk with rationalizations, zero risk assessment), and decision-making concepts (cultural influence, familial identity, social influences, information sources). I expanded on the sensemaking supposition of individual identity by arguing that familial identity can also impact decision-making. A key finding to this study was the typology of parents that emerged including football families-parent agency, hesitant family- parent agency, and child focused family-child agency. The type of family reflected families' reception to community culture, impact of social influence, and openness to information sources. Family type also impacted the risk assessment process and belief of control over outcomes in football participation

Research on capacity planning of thermal power units in deep peak regulation auxiliary service

Abstract Deep peak regulation service is an important transaction type in China’s power auxiliary service. The thermal power units’ participation in the quotation decision of deep peak regulation auxiliary service is related to their own benefits and the smooth operation of the whole deep peak regulation auxiliary service system. In order to study the influence of capacity planning of thermal power units on the transaction income and market equilibrium of market players in deep peak regulation, this paper builds static models of thermal power units participating in deep regulation transactions with complete information and incomplete information based on game theory and virtual game opponent analysis method, and gives the solution method of game equilibrium. In addition, based on the depth of the province peak shaving auxiliary services related data to do the game model of case analysis, obtained in the condition of incomplete information static equilibrium in depth peakload auxiliary services unit the best boot output range and corresponding interval unit best deep callback service decisions, in this paper, the rationality of the model and its equilibrium solution is verified, It is hoped that the research of this paper has some reference value for the capacity planning decision of thermal power units participating in depth peak regulation.</jats:p