Abstract
In this paper, a two-layer distributed optimization platform employing the alternating direction method of multipliers (ADMM) method is developed as an exchange problem to solve the electric vehicle charging management problem (EVCMP). The proposed model establishes a coordination layer between the EV aggregators, which increases the optimization’s overall efficiency while preserving aggregators’ independence. Numerical tests validate that the proposed coordinated distributed platform (CDP) enhances the load profile’s smoothness compared to the locally coordinated and uncoordinated charging platforms. Moreover, CDP also decreases the total EV charging costs by 35%, compared to the uncoordinated charging approach.
Highlights
Considering the current structure of the EV charging market in which different entities such as nonprofits and profit aimed charging companies, automakers, and utilities are the owners of charging equipment and responsible for controlling the charging and discharging processes [3], the role of EV aggregator (EVA) in EV charging management problem (EVCMP) is undeniable
We reformulate the optimization problem as a mixed-integer quadratic programming (MIQP) problem and develop the battery degradation cost proposed in [18, 26, 28] to analyze the significant effect of EV discharging capability on meeting the EVAs and EVs goals and capacity constraints
This paper extends the scope of the authors’ previous work [29] in three fronts: (i) it explains the proposed platform’s theory and mathematical background in more detail; (ii) it conducts a comprehensive evaluation focusing on analyzing the effects of the V2G and energy constraints on EV and EVAs’ metrics in coordinated distributed platform (CDP); (iii) it demonstrates the convergence rate of primal and dual residuals of the CDP
Summary
It is expected that the number of public and private chargers for EVs (excluding two/three-wheelers) grows from 870 thousand and 6.4 million today to almost 11 and 135 million in 2030, respectively [1]. These chargers provide around 470 TWh of energy, which will account for 1%, 3%, and 4% percent of electricity consumption in the US, Europe, and China, respectively [1]. The coordination methods used to solve EVCMP are classified in centralized and distributed approaches [5]. EVs and EVAs are both responsible for solving their optimization problem according to the global optimization constraints. Shahab Afshar et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS while fulfilling the individual EVA constraints in a distributed optimization platform
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