Combined economic emission based resource allocation for electric vehicle enabled microgrids. Issue 6 (30th November 2020)

• Record Type: Journal Article
• Authors: Umoren, Ifiok Anthony; Shakir, Muhammad Zeeshan
• Is Part Of: IET smart grid. Volume 3:Issue 6(2020)
• Page Start: 768
• Page End: 776
• Publication Date: 2020-11-30
• Subjects: power generation economics -- resource allocation -- battery powered vehicles -- optimisation -- distributed power generation; carbon emissions -- CEE optimisation problem -- bi‐objective optimisation problem -- emission limit -- charging station limit -- carbon price -- bi‐objective problem -- EV battery degradation cost -- EVaaS participation -- combined economic emission based resource allocation -- electric vehicle -- microgrids -- distributed energy resources -- dispersed EVs -- combined economic emission optimisation model -- EV as a service framework; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2020.0105
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : As electric vehicles (EVs) are currently under‐utilised, the features of deploying EVs as distributed energy resources (DERs), based on an EV as a service (EVaaS) framework, are exploited and a resource allocation scheme is proposed for optimum association of dispersed EVs with critical load for demand fulfilment in microgrids. The proposed approach is based on a combined economic emission (CEE) optimisation model where both energy costs and carbon emissions are taken into account. The CEE optimisation problem is then formulated as a bi‐objective optimisation problem, considering a number of practical constraints, such as energy demand, cost budget, emission limit and charging station limit. Carbon price is introduced to convert the bi‐objective problem into a single objective function. The authors included EV battery degradation cost to ensure EV owners are not worse off after EVaaS participation. The feasibility of the proposed model is demonstrated in simulation studies. The approach has been extended to evaluate the trade‐off between EVaaS and conventional DERs. Numerical results demonstrate the efficiency of the proposed resource allocation scheme.