Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente
dc.citation.epage | 174 | en_US |
dc.citation.spage | 167 | en_US |
dc.citation.volumeNumber | 105 | en_US |
dc.contributor.author | Yuan, S. | en_US |
dc.contributor.author | Kocaman, A.S. | en_US |
dc.contributor.author | Modi, V. | en_US |
dc.date.accessioned | 2018-04-12T11:10:31Z | |
dc.date.available | 2018-04-12T11:10:31Z | |
dc.date.issued | 2017 | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.description.abstract | For electric grids that rely primarily on liquid fuel based power generation for energy provision, e.g. one or more diesel gensets, measures to allow a larger fraction of intermittent sources can pay-off since the displaced is high cost diesel powered generation. This paper presents a case study of Sao Vicente, located in Cape Verde where a particularly high fraction of wind capacity of 5.950�MW (75% of the average demand) is installed, with diesel gensets forming the dispatchable source of power. This high penetration of intermittent power is managed through conservative forecasting and curtailments. Two potential approaches to reduce curtailments are examined in this paper: 1) an improved wind speed forecasting using a rolling horizon ARIMA model; and 2) energy storage. This case study shows that combining renewable energy forecasting and energy storage is a promising solution which enhances diesel fuel savings as well as enables the isolated grid to further increase the annual renewable energy penetration from the current 30.4% up to 38% while reducing grid unreliability. In general, since renewable energy forecasting ensures more accurate scheduling and energy storage absorbs scheduling error, this solution is applicable to any small size isolated power grid with large renewable energy penetration. | en_US |
dc.description.provenance | Made available in DSpace on 2018-04-12T11:10:31Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2017 | en |
dc.embargo.release | 2019-05-01 | en_US |
dc.identifier.doi | 10.1016/j.renene.2016.12.061 | en_US |
dc.identifier.issn | 0960-1481 | |
dc.identifier.uri | http://hdl.handle.net/11693/37335 | |
dc.language.iso | English | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.renene.2016.12.061 | en_US |
dc.source.title | Renewable energy | en_US |
dc.subject | ARIMA model | en_US |
dc.subject | Isolated grid | en_US |
dc.subject | Monte Carlo simulation | en_US |
dc.subject | Rolling horizon | en_US |
dc.subject | Storage | en_US |
dc.subject | Wind speed forecasting | en_US |
dc.subject | Diesel fuels | en_US |
dc.subject | Energy storage | en_US |
dc.subject | Forecasting | en_US |
dc.subject | Fuel economy | en_US |
dc.subject | Fuel storage | en_US |
dc.subject | Intelligent systems | en_US |
dc.subject | Monte Carlo methods | en_US |
dc.subject | Scheduling | en_US |
dc.subject | Wind | en_US |
dc.subject | ARIMA modeling | en_US |
dc.subject | Electric grids | en_US |
dc.subject | Isolated grids | en_US |
dc.subject | Large wind penetrations | en_US |
dc.subject | Renewable energies | en_US |
dc.subject | Renewable energy penetrations | en_US |
dc.subject | Rolling horizon | en_US |
dc.subject | Wind speed forecasting | en_US |
dc.subject | Electric power transmission networks | en_US |
dc.subject | adsorption | en_US |
dc.subject | cost analysis | en_US |
dc.subject | diesel | en_US |
dc.subject | electricity generation | en_US |
dc.subject | electricity supply | en_US |
dc.subject | energy budget | en_US |
dc.subject | energy resource | en_US |
dc.subject | forecasting method | en_US |
dc.subject | Monte Carlo analysis | en_US |
dc.subject | numerical method | en_US |
dc.subject | numerical model | en_US |
dc.subject | renewable resource | en_US |
dc.subject | smart grid | en_US |
dc.subject | wind velocity | en_US |
dc.subject | Cape Verde [Macaronesia] | en_US |
dc.subject | Sao Vicente [Cape Verde] | en_US |
dc.title | Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente | en_US |
dc.type | Article | en_US |
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