{"title":"Modeling of comprehensive power load of fishery energy internet considering fishery meteorology","authors":"Xueqian Fu , Tong Gou","doi":"10.1016/j.inpa.2023.02.008","DOIUrl":null,"url":null,"abstract":"<div><p>Accurate calculation for comprehensive power load of fishery energy internet plays<!--> <!-->a<!--> <!-->significant<!--> <!-->role<!--> <!-->in reasonable using of energy and reducing environmental pollution. However, as fishery power load is of greatly unique meteorology sensitivity, it continues to be a difficult problem. Therefore, the research of fishery meteorology is an important part of the rational development of fishery resources, the protection of production safety, and the pursuit of high and stable yield. This paper makes a deep study on the power load of the fishery energy internet under the influence of fishery meteorology and takes onshore fish pond as the research object. First of all, the power load is divided into three parts: oxygen enrichment power load, feeding power load, and water replenishment and drainage power load. The impact mechanism of fishery meteorology (including temperature, surface wind speed, precipitation, relative humidity, etc.) on it is described, and then the overall power load is obtained through modeling and integration. Finally, taking the Yuguang Complementary Project in Zhouquan Town, Tongxiang, Zhejiang Province, China as an example, using the meteorological data of its typical spring day and using the MATLAB tool to solve, the hourly comparison of the three types of power loads, the comprehensive power load demand, the full-day electricity charge forecast and the total annual power consumption are calculated. The annual power consumption per hectare and per kilogram of output calculated by simulation are basically consistent with the order of magnitude of the survey data, which proves the validity of the model proposed. The model established in this paper is an original work, and the exploration of fishery energy internet can draw lessons from it.</p></div>","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"10 4","pages":"Pages 581-591"},"PeriodicalIF":7.7000,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214317323000185/pdfft?md5=60703d47eaa2c71c14378ed8888ee383&pid=1-s2.0-S2214317323000185-main.pdf","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Processing in Agriculture","FirstCategoryId":"1091","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214317323000185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 1
Abstract
Accurate calculation for comprehensive power load of fishery energy internet plays a significant role in reasonable using of energy and reducing environmental pollution. However, as fishery power load is of greatly unique meteorology sensitivity, it continues to be a difficult problem. Therefore, the research of fishery meteorology is an important part of the rational development of fishery resources, the protection of production safety, and the pursuit of high and stable yield. This paper makes a deep study on the power load of the fishery energy internet under the influence of fishery meteorology and takes onshore fish pond as the research object. First of all, the power load is divided into three parts: oxygen enrichment power load, feeding power load, and water replenishment and drainage power load. The impact mechanism of fishery meteorology (including temperature, surface wind speed, precipitation, relative humidity, etc.) on it is described, and then the overall power load is obtained through modeling and integration. Finally, taking the Yuguang Complementary Project in Zhouquan Town, Tongxiang, Zhejiang Province, China as an example, using the meteorological data of its typical spring day and using the MATLAB tool to solve, the hourly comparison of the three types of power loads, the comprehensive power load demand, the full-day electricity charge forecast and the total annual power consumption are calculated. The annual power consumption per hectare and per kilogram of output calculated by simulation are basically consistent with the order of magnitude of the survey data, which proves the validity of the model proposed. The model established in this paper is an original work, and the exploration of fishery energy internet can draw lessons from it.
期刊介绍:
Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining