Please use this identifier to cite or link to this item:
https://hdl.handle.net/10321/3408
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chidzonga, Richard | en_US |
dc.contributor.author | Gomba, Masimba | en_US |
dc.contributor.author | Nleya, Bakhe | en_US |
dc.date.accessioned | 2020-06-18T07:15:33Z | - |
dc.date.available | 2020-06-18T07:15:33Z | - |
dc.date.issued | 2020-04-30 | - |
dc.identifier.citation | Chidzonga, R., Gomba, M. and Nleya, B. 2020. Energy demand and trading optimization in isolated microgrids. Presented at: Conference on Information Communications Technology and Society (ICTAS). Available: doi:10.1109/ictas47918.2020.233994 | en_US |
dc.identifier.uri | http://hdl.handle.net/10321/3408 | - |
dc.description.abstract | Future generation or smart grid (SG) will incorporate ICT technologies as well as innovative ideas for advanced integrated and automated power systems. The bidirectional information and energy flows within the envisaged advanced SG together with other aiding devices and objects, promote a new vision to energy supply and demand response. Meanwhile, the gradual shift to the next generation fully fledged SGs will be preceded by individual isolated microgrids voluntarily collaborating in the managing of all the available energy resources within their control to achieve optimality in both demand and distribution. In so doing, innovative applications will emerge that will bring numerous benefits as well as challenges in the SG. This paper introduces a power management approach that is geared towards optimizing power distribution, trading, as well as storage among cooperative microgrids (MGs). The initial task is to formulate the problem as a convex optimization problem and ultimately decompose it into a formulation that jointly considers user utility as well as factors such as MG load variance and associated transmission costs. It is deduced from obtained analytical results that the formulated generic optimization algorithm characterizing both overall demand and response by the cooperative microgrids assist greatly in determining the required resources hence leading to cost effectiveness of the entire system. | en_US |
dc.format.extent | 5 p. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Eenergy cooperative microgrids | en_US |
dc.subject | Energy storage system | en_US |
dc.subject | Smart Grid | en_US |
dc.title | Energy demand and trading optimization in isolated microgrids | en_US |
dc.type | Conference | en_US |
dc.date.updated | 2020-05-05T10:18:46Z | - |
dc.relation.conference | Conference on Information Communications Technology and Society (ICTAS) | en_US |
dc.identifier.doi | 10.1109/ictas47918.2020.233994 | - |
local.sdg | SDG03 | - |
local.sdg | SDG07 | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.openairetype | Conference | - |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
Appears in Collections: | Research Publications (Engineering and Built Environment) |
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File | Description | Size | Format | |
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Chidzonga_ICTAS_5Pg_2020.pdf | 452.62 kB | Adobe PDF | View/Open |
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