Loading…
Statistical analysis of CSP plants by simulating extensive meteorological series
The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | |
container_issue | 1 |
container_start_page | |
container_title | |
container_volume | 1850 |
creator | Pavón, Manuel Fernández, Carlos M. Silva, Manuel Moreno, Sara Guisado, María V. Bernardos, Ana |
description | The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI. |
doi_str_mv | 10.1063/1.4984554 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>proquest_scita</sourceid><recordid>TN_cdi_scitation_primary_10_1063_1_4984554</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2116115280</sourcerecordid><originalsourceid>FETCH-LOGICAL-p288t-89488da7a918b2e3bdcc54e7c0f0e62bb940aa54bd23bdbb0f61340abde134f3</originalsourceid><addsrcrecordid>eNp9kEFLAzEQhYMoWKsH_0HAm7A1k83uZo9StAoFC-3BW0h2syVlu1kzabH_3q0tePP0YOZ7w7xHyD2wCbA8fYKJKKXIMnFBRpBlkBQ55JdkxFgpEi7Sz2tyg7hhjJdFIUdksYw6Ooyu0i3VnW4P6JD6hk6XC9q3uotIzYGi2-7aAezW1H5H26HbW7q10frgW7_-daMNzuItuWp0i_burGOyen1ZTd-S-cfsffo8T3ouZUxkKaSsdaFLkIbb1NRVlQlbVKxhNufGlIJpnQlT82FnDGtySIeRqe2gTTomD6ezffBfO4tRbfwuDP-j4gA5QMYlG6jHE4WVO-b0neqD2-pwUHsfFKhzWaqvm_9gYOrY7p8h_QE8pm1_</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>2116115280</pqid></control><display><type>conference_proceeding</type><title>Statistical analysis of CSP plants by simulating extensive meteorological series</title><source>American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)</source><creator>Pavón, Manuel ; Fernández, Carlos M. ; Silva, Manuel ; Moreno, Sara ; Guisado, María V. ; Bernardos, Ana</creator><contributor>Obaidli, Abdulaziz Al ; Richter, Christoph ; Calvet, Nicolas</contributor><creatorcontrib>Pavón, Manuel ; Fernández, Carlos M. ; Silva, Manuel ; Moreno, Sara ; Guisado, María V. ; Bernardos, Ana ; Obaidli, Abdulaziz Al ; Richter, Christoph ; Calvet, Nicolas</creatorcontrib><description>The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/1.4984554</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Feasibility studies ; Irradiance ; Meteorological parameters ; Statistical analysis</subject><ispartof>AIP conference proceedings, 2017, Vol.1850 (1)</ispartof><rights>Author(s)</rights><rights>2017 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>309,310,314,776,780,785,786,23911,23912,25120,27903,27904</link.rule.ids></links><search><contributor>Obaidli, Abdulaziz Al</contributor><contributor>Richter, Christoph</contributor><contributor>Calvet, Nicolas</contributor><creatorcontrib>Pavón, Manuel</creatorcontrib><creatorcontrib>Fernández, Carlos M.</creatorcontrib><creatorcontrib>Silva, Manuel</creatorcontrib><creatorcontrib>Moreno, Sara</creatorcontrib><creatorcontrib>Guisado, María V.</creatorcontrib><creatorcontrib>Bernardos, Ana</creatorcontrib><title>Statistical analysis of CSP plants by simulating extensive meteorological series</title><title>AIP conference proceedings</title><description>The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI.</description><subject>Feasibility studies</subject><subject>Irradiance</subject><subject>Meteorological parameters</subject><subject>Statistical analysis</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2017</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNp9kEFLAzEQhYMoWKsH_0HAm7A1k83uZo9StAoFC-3BW0h2syVlu1kzabH_3q0tePP0YOZ7w7xHyD2wCbA8fYKJKKXIMnFBRpBlkBQ55JdkxFgpEi7Sz2tyg7hhjJdFIUdksYw6Ooyu0i3VnW4P6JD6hk6XC9q3uotIzYGi2-7aAezW1H5H26HbW7q10frgW7_-daMNzuItuWp0i_burGOyen1ZTd-S-cfsffo8T3ouZUxkKaSsdaFLkIbb1NRVlQlbVKxhNufGlIJpnQlT82FnDGtySIeRqe2gTTomD6ezffBfO4tRbfwuDP-j4gA5QMYlG6jHE4WVO-b0neqD2-pwUHsfFKhzWaqvm_9gYOrY7p8h_QE8pm1_</recordid><startdate>20170627</startdate><enddate>20170627</enddate><creator>Pavón, Manuel</creator><creator>Fernández, Carlos M.</creator><creator>Silva, Manuel</creator><creator>Moreno, Sara</creator><creator>Guisado, María V.</creator><creator>Bernardos, Ana</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20170627</creationdate><title>Statistical analysis of CSP plants by simulating extensive meteorological series</title><author>Pavón, Manuel ; Fernández, Carlos M. ; Silva, Manuel ; Moreno, Sara ; Guisado, María V. ; Bernardos, Ana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p288t-89488da7a918b2e3bdcc54e7c0f0e62bb940aa54bd23bdbb0f61340abde134f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Feasibility studies</topic><topic>Irradiance</topic><topic>Meteorological parameters</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pavón, Manuel</creatorcontrib><creatorcontrib>Fernández, Carlos M.</creatorcontrib><creatorcontrib>Silva, Manuel</creatorcontrib><creatorcontrib>Moreno, Sara</creatorcontrib><creatorcontrib>Guisado, María V.</creatorcontrib><creatorcontrib>Bernardos, Ana</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pavón, Manuel</au><au>Fernández, Carlos M.</au><au>Silva, Manuel</au><au>Moreno, Sara</au><au>Guisado, María V.</au><au>Bernardos, Ana</au><au>Obaidli, Abdulaziz Al</au><au>Richter, Christoph</au><au>Calvet, Nicolas</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Statistical analysis of CSP plants by simulating extensive meteorological series</atitle><btitle>AIP conference proceedings</btitle><date>2017-06-27</date><risdate>2017</risdate><volume>1850</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/1.4984554</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0094-243X |
ispartof | AIP conference proceedings, 2017, Vol.1850 (1) |
issn | 0094-243X 1551-7616 |
language | eng |
recordid | cdi_scitation_primary_10_1063_1_4984554 |
source | American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list) |
subjects | Feasibility studies Irradiance Meteorological parameters Statistical analysis |
title | Statistical analysis of CSP plants by simulating extensive meteorological series |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-28T04%3A23%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_scita&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Statistical%20analysis%20of%20CSP%20plants%20by%20simulating%20extensive%20meteorological%20series&rft.btitle=AIP%20conference%20proceedings&rft.au=Pav%C3%B3n,%20Manuel&rft.date=2017-06-27&rft.volume=1850&rft.issue=1&rft.issn=0094-243X&rft.eissn=1551-7616&rft.coden=APCPCS&rft_id=info:doi/10.1063/1.4984554&rft_dat=%3Cproquest_scita%3E2116115280%3C/proquest_scita%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-p288t-89488da7a918b2e3bdcc54e7c0f0e62bb940aa54bd23bdbb0f61340abde134f3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2116115280&rft_id=info:pmid/&rfr_iscdi=true |