Study on Meta-Modeling Method for Performance Analysis of Digital Power Plant

Author:

Zhou Dengji1,Wei Tingting1,Ma Shixi1,Zhang Huisheng1,Huang Di2,Jiang Ping3,Lu Zhenhua1

Affiliation:

1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

2. State Grid Jiangsu Electric Power Company Research Institute, Nanjing 211103, China

3. PetroChina West East Gas Pipeline Company, Shanghai 200122, China

Abstract

Abstract Digital power plant is the theory and method to improve the operating quality of power plant by quantifying, analyzing, controlling, and deciding the physical and working objects of power plants in the whole life cycle. And the foundation of digital power plant is system modeling and performance analysis. However, there are some problems in the process of modeling establishment and performance analysis. For instance, each component has different dimensions and different types of mathematical description, and the data or information used for modeling are defined differently and belong to different enterprises, who do not want to share their information. Meta-modeling is a potential method to solve these problems. It defines the specification to describe different kinds of elements and the relationship between different elements. In this paper, the collaborative modeling and simulation platform for digital power plant has been established based on the meta-modeling method and the performance of the target power plant has been analyzed from different aspects via field data. The meta-modeling method consists of three parts: syntax definition, model development, and algorithm definition. In the comparative study between the meta-model and the traditional model, maximum average errors of the two methods are 8.72% and 4.74%, which reveals the high accuracy of the meta-modeling-based model. The result shows that the modeling and simulation platform for power plants can be used to reduce costs, decrease equipment failure rate, and improve plant output, so as to guarantee the safety and increase economics.

Funder

Aeronautical Science Foundation of China

Major Project for Aero Engines and Gas Turbines

National Natural Science Foundation of China

Publisher

ASME International

Subject

Geochemistry and Petrology,Mechanical Engineering,Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

Reference30 articles.

1. Srinivasan, J., and Chotai, S.,2017, “Digital Power Plant System and Method,” U.S. Patent Application No. 15/251,626.

2. Micro Task Evaluation of Analog vs. Digital Power Plant Control Room Interfaces;Hildebrandt,2016

3. Smart Power Generation Project System Design and Case Discussions;Lei;Electr. Power Inf. Commun. Technol.,2017

4. Progress in Dynamic Simulation of Thermal Power Plants;Alobaid;Prog. Energy Combust. Sci.,2017

5. Optimal Operational Scheduling of Renewable Energy Sources Using Teaching–Learning Based Optimization Algorithm by Virtual Power Plant;Kasaei;ASME J. Energy Resour. Technol.,2017

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Block Chain based P2P energy trading strategy in power retail market for MVPPs;2023 IEEE 4th China International Youth Conference On Electrical Engineering (CIYCEE);2023-12-08

2. Dynamic simulation of gas turbines via feature similarity-based transfer learning;Frontiers in Energy;2020-12

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3