Abstract
With the pervasiveness of electric vehicles and an increased demand for fast charging, stationary high-power fast-charging is becoming more widespread, especially for the purpose of serving pure electric buses (PEBs) with large-capacity onboard batteries. This has resulted in a huge distribution capacity demand. However, the distribution capacity is limited, and in some urban areas the cost of expanding the electric network capacity is very high. In this paper, three battery energy storage system (BESS) integration methods—the AC bus, each charging pile, or DC bus—are considered for the suppression of the distribution capacity demand according to the proposed charging topologies of a PEB fast-charging station. On the basis of linear programming theory, an evaluation model was established that consider the influencing factors of the configuration: basic electricity fee, electricity cost, cost of the energy storage system, costs of transformer and converter equipment, and electric energy loss. Then, a case simulation is presented using realistic operation data, and an economic comparison of the three configurations is provided. An analysis of the impacts of each influence factor in the case study is discussed to verify the case results. The numerical results indicate that the appropriate BESS configuration can significantly reduce the distribution demand and stationary cost synchronously.
Highlights
The energy and environmental crises have become increasingly serious with the advancement of human society: an escalating energy demand, the exhaustive nature of fossil fuels, and CO2 emissions are among the major threats [1]
This research can be applied widely to evaluate the economics for the high-power pure electric buses (PEBs) fast charging stations to suppress distribution capacity demand using a battery energy storage system (BESS)
This paper focuses on the influence of equipment loss on the BESS configuration and neglects the thermal loss of cables
Summary
The energy and environmental crises have become increasingly serious with the advancement of human society: an escalating energy demand, the exhaustive nature of fossil fuels, and CO2 emissions are among the major threats [1]. The authors in [12] presented a coordinated charging strategy for electric taxis in a temporal and spatial domain, and a Particle Swarm Optimization (PSO) algorithm was used to balance the charging load dispatch among different stations, as well as the charging times for the electric taxis These studies have concentrated on private EVs or electric taxis with distribution capacity constraints, and their aim has been to improve charging costs. An integer nonlinear programming model that incorporated the investment cost, lifespan, and time-of-use electricity price was proposed to estimate the value of an energy storage system (ESS) for the electric bus fast charging station, and the effectiveness of two kinds of Li-ion battery was compared [22]. This research can be applied widely to evaluate the economics for the high-power PEB fast charging stations to suppress distribution capacity demand using a BESS.
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