| Title |
Wind power volatility alleviation considering battery systems and responsive loads: A stochastic framework |
| Authors |
Khazali A. , RODRÍGUEZ CORTÉS, PEDRO |
| External publication |
No |
| Means |
Int. Conf. Renew. Energy Res. Appl., ICRERA |
| Scope |
Conference Paper |
| Nature |
Científica |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080961617&doi=10.1109%2fICRERA47325.2019.8996615&partnerID=40&md5=08510d99085f754ccf88ae40dac90e71 |
| Publication date |
01/01/2019 |
| Scopus Id |
2-s2.0-85080961617 |
| DOI |
10.1109/ICRERA47325.2019.8996615 |
| Abstract |
The uncertain characteristic of wind farms is the main issue of these generation sources despite their various advantages. When wind generation sources are supposed to participate in day-ahead markets as ordinary generation units, obtaining optimal offers to assure the profitability is a great challenge. In electricity markets deviating from the prescheduled generation can lead to penalties which jeopardize the benefits of the generation unit. Energy storage systems and demand response programs can be regarded as tools to overcome the interruptible operation and volatility of wind and provide wind farm owners flexibility to follow day-ahead scheduling generation. In this paper, based on stochastic programming a new formulation is presented for submitting optimal offers of a wind farm considering storage system and demand response programs for day ahead markets. The suggested approach is studied on a 10MW wind farm accompanied with a 1MW (2MWh) battery and a 0.9 MW demand response aggregator. © 2019 IEEE. |
| Keywords |
Commerce; Electric batteries; Electric energy storage; Electric utilities; Stochastic programming; Wind power; Day ahead market; Day-ahead scheduling; Demand response programs; Energy storage systems; |
| Universidad Loyola members |
|
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