Combined economic emission based resource allocation for electric vehicle enabled microgrids

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.

Electric Vehicle as a Service (EVaaS): Applications, Challenges and Enablers

“…Smart charging and discharging, where EVs charge their batteries from RESs and discharge them during peak demand, is reported to offer the best possible utilization of RESs for cost and emission reductions in the smart grid [105][106][107]. It can improve operational performance in stand-alone operation mode and increase the quantity of RESs installed in islanded microgrids [101].…”

Optimal operation of microgrid with consideration of V2G's uncertainty

“…The evaluation of V2G electricity and its reliability can be regarded as a reliability constraint for EVA to achieve V2G, which is applied to the scheduling model of the microgrid. Therefore, in Section 4, instead of a bi‐objective optimization model combining EVs and microgrid operators in [18], we select a simple microgrid scheduling model and give an example of the application of the method proposed in Section 3 in microgrid operation. Please note that the economic benefits of the grid, EV users, and aggregators are outside of the scope of this paper.…”