Please use this identifier to cite or link to this item:
https://hdl.handle.net/10321/4678
DC Field | Value | Language |
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dc.contributor.author | Gomba, Masimba | en_US |
dc.contributor.author | Chidzonga, Richard | en_US |
dc.contributor.author | Nleya, Bakhe | en_US |
dc.contributor.author | Khumalo, Philani | en_US |
dc.date.accessioned | 2023-03-22T07:15:48Z | - |
dc.date.available | 2023-03-22T07:15:48Z | - |
dc.date.issued | 2020-01 | - |
dc.identifier.citation | Gomba, M. et al. 2020. Balancing between demand and trading in microgrids. 2020 International SAUPEC/RobMech/PRASA Conference. Presented at: 2020 International SAUPEC/RobMech/PRASA Conference. doi:10.1109/saupec/robmech/prasa48453.2020.9041018 | en_US |
dc.identifier.isbn | 9781728141626 | - |
dc.identifier.uri | https://hdl.handle.net/10321/4678 | - |
dc.description.abstract | The envisaged future generation power 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 optimally serve 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 aggregated demand and response from the cooperative microgrids assist greatly in determining the required resources hence enabling operational cost viability 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.relation.ispartof | 2020 International SAUPEC/RobMech/PRASA Conference | en_US |
dc.subject | Energy cooperative microgrids | en_US |
dc.subject | Energy storage system | en_US |
dc.subject | Smart grid | en_US |
dc.title | Balancing between demand and trading in microgrids | en_US |
dc.type | Conference | en_US |
dc.date.updated | 2023-03-20T05:26:10Z | - |
dc.identifier.doi | 10.1109/saupec/robmech/prasa48453.2020.9041018 | - |
local.sdg | SDG03 | - |
local.sdg | SDG07 | - |
item.openairetype | Conference | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | Research Publications (Engineering and Built Environment) |
Files in This Item:
File | Description | Size | Format | |
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Gomba et al_2020.pdf | Article | 536.86 kB | Adobe PDF | View/Open |
IEEE Copyright clearance.docx | Copyright clearance | 227.39 kB | Microsoft Word XML | View/Open |
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