Open AccessValue‐stack aggregator optimal planning considering disparate DERs technologies
Author(s) -
Mohamed Amr A.,
Sabillon Carlos,
Golriz Ali,
Venkatesh Bala
Publication year - 2021
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12205
Subject(s) - news aggregator , distributed generation , revenue , computer science , value proposition , capacity planning , energy planning , environmental economics , business , renewable energy , economics , engineering , finance , marketing , electrical engineering , operating system
Abstract Federal energy regulatory commission (FERC) Order #2222 prescribes that distributed energy resources (DERs) with 100 kW or more capacity in aggregate should be allowed to participate in organized electricity markets. Most aggregation is via a combination of disparate DER technologies such as solar, wind, storage, electric vehicles, and smart load units. Another stumbling block to enabling participation of DERs in organized electricity markets is the energy limitation. However, there is a lack of aggregator models in the literature that gainfully allow aggregation of disparate DER technologies that are energy limited. To address this shortcoming, we proposed a disparate DER aggregator (DDA) planning model here, that overcomes energy limitation of DERs. The DDA planning model considers multiple revenue streams of (1) capacity credits; (2) energy revenues; and (3) ancillary services revenues. The proposed DDA planning model enables disparate DER technologies to collate and provide a firm power capacity and participate in the market capacity auction and receive capacity credits. This comprehensive DDA planning model considers the dynamic/temporary aggregations with other facilities through peer‐to‐peer (P2P) trade, and maximization of the net present value (NPV) revenues over the planning horizon. The developed model is tested on sample and practical large‐scale case studies. Additional sensitivity analyses are performed, demonstrating the favourable performance and the business potential of the developed DDA planning model.