1. Introduction

2. DCFC Station Architecture and Modeling

2.1. System Modeling

The architecture of the DCFC station model has been referred from [28,41,42,44,45,46], and updated for this work. The details of the components with their respective models are given in the Table 1. An overview of the system model architecture is shown in Figure 2. The model design is augmented considering a multi-source DCFC station including a grid connection, PV model, and SLB packs.

The battery pack model includes electrical, thermal and degradation performance. The aging method estimates the capacity and internal resistance of the batteries based on the cycle and calendar life using the realistic operating conditions of the battery estimated by the battery electro-thermal model. A thermal management model is emulating a liquid cooling system and related control. The battery model has been incorporated with a Battery Management System (BMS) model to keep the battery’s parameters in the safe operating region (voltage, current, temperature, state of charge limits) [46]. The battery capacity and internal resistance are degraded overtime on the basis of the current, state of charge and temperature of operation. The model used in this work includes both calendar and cycling aging and is inspired to the empirical aging model reported in [45] The PV model is based on the real solar irradiation and weather data from Columbus, Ohio, year 2020 [47] and the PV panel used is BP 3 SERIES 235 Watt [48]. The EV model acts as a load when EVs are present, power converters model provides efficiency based on system power and voltage. The EV load is modeled as a series of pulses distributed in time, as developed in [41]. The grid model outputs the power based on the request from the Energy Management Controller (EMC). The grid’s initial boundary conditions are set up to maintain the system parameters within defined ranges of several predetermined scenarios.

Table 1. Details of the models used in DCFC station model architecture.

Table 1. Details of the models used in DCFC station model architecture.

Components	Model used	References
SLB	Zero-order Equivalent Circuit Model	[28,42]
SLB Thermal	Lumped Parameter Thermal Model	[28,42]
SLB BMS	State flow	[46]
SLB Aging	Daikin’s battery aging model	[28,42,45]
PV	5 parameter model	[49]
AC-DC and DC-DC	Efficiency based model	[41]
EV Load	Event based profile	[41]

An EMC is included to enable a proper operation of the station over the lifetime and ensuring power readily available for EVs under realistic system constraints. To select the power source, EMC collects the battery information in terms of $SOC$, temperature $T_{SLB}$ and voltage $V_{SLB}$ from the SLB model, PV available power $P_{PV}$ and the load request $P_{EV}$ from EVs at time t to define the power reference for SLB, PV and grid ($P_{SLB}$, $P_{PV}$, $P_g$, respectively). The other tasks are to fully utilize the PV energy and maintaining the battery SOC within a certain operating range. The EMC operates in such a way to maintain SLB charging while maximizing PV utilization when EVs are not present at the station. If there is surplus PV energy available, net metering [43] will be used. The SLB charge is allowed only if EVs are not present. The control strategy allows SLB to be charged through PV whenever solar irradiation is available. If the PV power is more than the minimum charging power threshold of SLB $\left(P_{SLB,ch}^m\right)$, all the available PV power is given to the SLB charging and no power is used from the grid. However, if the PV power is less than the charging power threshold $\left(P_{SLB,ch}^m\right)$, the grid supplements the SLB charging up to the minimum charging power of SLB. Note that $\left(P_{SLB,ch}^m\right)$ varies with the selection of scenarios, discussed in the Section 3 and is considered as the maximum power used from the grid $\left(P_g^M\right)$. When the PV is available and SLB is fully charged (SOC > 95%), the PV residual power is fed into the grid and will be operated in net metering mode. The details of SLB and EV charging controls are given in Table 2 and Table 3, respectively.

For EV and SLB charging mode, the power balance equation is given in (1).

$$P_{SLB}+P_{PV}+P_g=P_{EV}$$

(1)

During EV charging, three types of control strategies for EV charging are considered. These strategies change the dependence on the grid and PV for EV charging and the ways they are used to support SLBs during EV charging.

• CONTROL A: Charge EV only from SLB. In this control strategy, the EVs are directly charged from the SLBs and no other source is used.
• CONTROL B: Charge EV from SLB and PV. In this control strategy the PV power, if available, has the priority when an EV request to be charged with the aim of maximizing the energy from renewable resources. The PV power is equal to the Maximum Power Point $P_{MPP}$ [50]. Then, the remaining power required by the EVs is supplied by the SLB. There is no use of grid energy to charge EVs in this control.
• CONTROL C: Charge EV from SLB, grid and PV. In this control strategy the PV power, if available, has the priority when an EV request to be charged with the aim of maximizing the energy from renewable resources. The PV power is equal to the Maximum Power Point $P_{MPP}$. Then, the remaining power required by the EVs is supplied by the SLB and the grid. The grid power supplies the maximum interconnection power $P_{POI}$.

2.2. Economic Modeling

In this sub-section, the cost of ownersip of the EV DCFC station is evaluated and the economic value of the station is assessed through Net Present Value (NPV) method. The breakdown of cost structure by owning, maintaining, and operating a DCFC station is considered for both the traditional and proposed station models which is later compared in the results section. The cost can be categorized as capital cost (CAPEX), operating cost (OPEX), and revenue. The description of components for the DCFC cost is shown in Figure 3 which includes all major cost components of the proposed DCFC station.

The capital investment cost, or CAPEX, is based on the price of the materials and the cost of their installation related to DCFC’s components. Because it is challenging to predict the site and land needs, permitting and civil costs are outside the scope of this work. The operational cost, also known as OPEX, is the variable cost that fluctuates with time and consumption depending on how the sources are used, such as the cost of the electricity in terms of energy and power. The cost of charging station maintenance, which primarily consists of SLB replacement needs, is also included. The replacement of PV modules and station maintenance is not taken into account as the components’ and PV life exceeds the project’s total life. Taxes are paid for electricity use and EV charging, warranties and location-based taxes are not taken into account. The station’s expenses are its CAPEX and OPEX costs, while revenue represents cash inflow from the EV charging events, and various revenue sources such as solar credits and battery resale earnings.

The cost parameters with their descriptions and references are listed in the Table 4, Table 5 and Table 6. A detailed survey of recent literature and data has been performed to accurately evaluate the values of each cost component and for each of the cost categories. The data have been collected from a multitude of publications from industry, national laboratories, academia, and energy reports.

The Balance of System (BOS) is part of the CAPEX that includes components of a BESS excluding the battery pack’s cost. The segregation is done from the BESS to cost per unit basis in terms of energy for BESS $(\$/\mathrm{kWh})$ and in terms of power for BOS $(\$/\mathrm{kW})$. BOS includes BMS, Thermal Management System (TMS), wiring and cabling, connectors isolation system and protection circuits, and Fire Management System (FMS). Re-purposing or re-integrating the SLBs also added cost to the CAPEX value.

The parameters for the demand charges and the electricity charges have been referenced from the Ohio Electricity Tariff rules [51]. The values of the bill have been normalized to obtain $/kWh value for the energy or electricity consumption in terms of kWh used and in $/kW for the demand charges to account for the power in kW used.

The revenues have three contributors, the earnings from EV charging, the earnings from selling the batteries after the end of the project with the energy capacity remaining, and finally the earnings from Solar Renewable Credits (SREC) for the extra energy produced from PV and sold to the grid (in compliance with net metering rules of Ohio [43]). The SREC values are based on Locational Marginal Price (LMP) in real cases and change dynamically like a stock market. Hence for simplicity, an average value has been considered from Ohio’s history of SREC prices over a year [52,53].

From the values of CAPEX, OPEX, and Revenues, the following equations are used. $n_{PV}$ is the number of PV panel arrays in parallel (number of panels in series is decided as per the battery pack max voltage) and $n_{SLB}$ is the number of battery packs in parallel. Sizing details are explained in Section 3.

$$\begin{array}{cc}\hfill C_{CAPEX}=& C_{SLB}+C_{PV}+C_{ACDC}+C_{DCDC}+C_{intg}^{SLB}\hfill \\ \hfill & +C_{mod}^{SLB}+C_{BOS}+C_{POI}+C_{trans}+C_{EVSE}\hfill \end{array}$$

(2)

$$C_{SLB}=C_{SLB,u}·n_{SLB}·E_{SLB,pack}$$

(3)

$$C_{PV}=C_{PV,u}·n_{PV}·P_{PV,modl}^M$$

(4)

$$C_{OPEX}=C_{op,bill}+C_{op,SLB}$$

(5)

The operational cost is divided into two parts which includes the cost of paying the electricity bills which constitute demand charges and energy charges as given in (6).

$$C_{op,bill}=C_{dch}+C_{ech}$$

(6)

The other part of the operational cost is due to the SLBs when they need the replacement. Equation (7) breaks down the replacement cost of batteries.

$$C_{op,SLB}=C_{repl}^{SLB}+C_{intg,repl}^{SLB}$$

(7)

$C_{repl}^{SLB}$ gives the cost of replacing the SLBs after their End of Life (EOL) and $C_{intg,repl}^{SLB}$ gives the operational cost of integrating the replaced SLB packs.

$$C_{REVX}=C_{EVch}+C_{sell}^{SLB}+C_{SREC}$$

(8)

The revenues is represented as $C_{REVX}$ given in Equation (8) has 3 contributors as the earnings from EV charging $C_{EVch}$, the earnings from selling the batteries after the end of the project with the energy capacity remaining $C_{sell}^{SLB}$, and finally the earnings from Solar Renewable Credits for the extra energy produced from PV and sold to the grid $C_{SREC}$.

Table 4. CAPEX cost parameters with their description, unit, variables and values.

Table 4. CAPEX cost parameters with their description, unit, variables and values.

Description	Symbol	Unit	Value	References
Unit Cost of SLB	$C_{SLB,u}$	$/kWh	63.2	[27,28,54,55,56,57,58]
Unit Cost of PV	$C_{PV,u}$	$/kW	410	[27,29,30,54,55,56,57,58]
Unit Cost of AC-DC	$C_{ACDC,u}$	$/kW	108.5	[27,29,54,55,56,57,58]
Unit Cost of DC-DC	$C_{DCDC,u}$	$/kW	100	[27,29,54,55,56,57,58]
Unit Cost of SLB integration	$C_{intg,u}^{SLB}$	$/kWh	55	[59,60,61,62,63]
Unit Cost of SLB modification	$C_{mod,u}^{SLB}$	$/kW	50	[59,60,61,62,63]
Unit Cost of BOS	$C_{BOS,u}$	$/kW	40	[54,55,56,57,58]
Unit Cost of AC connection	$C_{conn,u}$	$/kW	100	[54,55,56,57,58]
Unit Cost of Distribution transformer	$C_{trans,u}$	$/kW	250	[64,65,66]
Unit Cost of EVSE	$C_{EVSE,u}$	$/kW	100	[54,55,56,57,58]

Table 5. OPEX cost parameters with their description, unit, variables and values.

Table 5. OPEX cost parameters with their description, unit, variables and values.

Description	Symbol	Unit	Value
Unit Cost of SLB replacement	$C_{repl,u}^{SLB}$	$/kWh	63.2	[27,28,54,55,56,57,58]
Unit Cost of replaced SLB integration	$C_{repl,u}^{SLB}$	%/kWh	55	[59,60,61,62,63]

Table 6. Revenue cost parameters with their description, unit, variables and values.

Table 6. Revenue cost parameters with their description, unit, variables and values.

Description	Symbol	Unit	Value	References
Unit Cost of EV charging	$C_{EVch,u}$	$/kWh	0.32	[67,68,69]
Unit Cost of selling battery with remaining capacity	$C_{sell,u}^{SLB}$	%/kWh	63.2	[27,28,54,55,56,57,58]
Unit Cost of Solar Renewable Energy Credits (SREC)	$C_{SREC,u}$	$/kWh	0.03	[52,53]

Table 7. Unit costs in various scenarios.

Table 7. Unit costs in various scenarios.

The relations of unit cost and the total cost values are shown below in Table 8. The variables with ‘E’ denote the energy and ‘P’ is the power. The superscript ‘M’ is the maximum value. The variable $E_{SLB,pack}$ is the energy capacity of each pack which is 23 kWh, and $E_{SLB}^M$ is the maximum energy capacity of all SLB packs together (based on the number of SLB packs $n_{SLB}$) on which the total cost of SLB $C_{SLB}$ is based on. Similarly, $P_{PV,modl}^M$ is the maximum power for a single PV module, and the total cost of PV $C_{PV}$ depends on the total number of modules used $n_{PV}$. The $RR$ is the replacement index of the SLBs defining the number of replacements.

Table 8. Relation of Cost Parameters.

Table 8. Relation of Cost Parameters.

Description	Symbol	Equation
Cost of SLB	$C_{SLB}$	$C_{SLB,u}·n_{SLB}·E_{SLB,pack}$
Cost of PV	$C_{PV}$	$C_{PV,u}·n_{PV}·P_{PV,modl}^M$
Cost of AC-DC	$C_{ACDC}$	$C_{ACDC,u}·P_{POI}$
Cost of DC-DC	$C_{DCDC}$	$C_{DCDC,u}·150$
Cost of SLB integration	$C_{intg}^{SLB}$	$C_{intg,u}^{SLB}·n_{SLB}·E_{SLB,pack}$
Cost of SLB modification	$C_{mod}^{SLB}$	$C_{mod,u}^{SLB}·n_{SLB}·E_{SLB,pack}$
Cost of BOS	$C_{BOS}$	$C_{BOS,u}·150$
Cost of AC connection	$C_{conn}$	$C_{conn,u}·P_{POI}$
Cost of Distribution transformer	$C_{trans}$	$C_{trans,u}·P_{POI}$
Cost of EVSE	$C_{EVSE}$	$C_{EVSE,u}·150$
Cost of SLB replacement	$C_{repl}^{SLB}$	$C_{repl,u}^{SLB}·E_{SLB,pack}·n_{SLB}·RR$
Cost of integrating replaced SLB	$C_{intg}^{SLB}$	$C_{intg,u}^{SLB}·C_{repl}^{SLB}$
Revenue from EV Charging	$C_{EVch}$	$C_{EVch,u}·P_g^M$
Revenue from selling battery with remaining capacity	$C_{sell}^{SLB}$	$C_{sell,u}^{SLB}·Q_{SLB}^{rem}$
Revenue from SREC	$C_{SREC}$	$C_{SREC,u}·E_{g,NET}(E_{g,NET}<0)$

Revenue from SREC is earned when Net Metered energy is negative (supplied back to the grid).

Net Present Value (NPV) is the present value of the cash flows at the required rate of return of a project compared to the initial investment. It is calculated by estimating future cash flows related to a project. Then, these cash flows are discounted to present value using a discount rate representing the project’s capital costs, operating costs, and desired rate of return. NPV gives the overall value of the project from the investment and earnings point of view [70]. The NPV is calculated as:

$$NPV=\sum _n^{t=0}{\displaystyle \frac{C_{cash}^t}{{(1+d)}^t}}$$

(9)

where $C_{cash}^t$ is net cash inflow-outflows during a single period t. t is the number of time periods, and years in our case and the d is the discount factor. To account for the NPV cash flow, it is important to consider the following parameters:

• Discount Factor: Accounts for the change in the power of money over the years.
• Electricity Charges Inflation: Due to the change in means of resources and overall inflation, electricity charges inflate over the years. From the historical trend of electricity rates in the US and in Ohio, the inflation percentage has been taken as constantly growing per year. To account for both demand and energy charges inflation, the rate of inflation has been considered the same.
• Revenue Inflation: Same consideration and the percentage growth of inflation has been taken as the electricity charges inflation due to dependence of revenue earned in $/kWh by charging EVs has electricity charges as a major contributor apart from the other earnings to recover the cost of the station.
• Battery Prices: Battery prices are forecasted to decrease over the years due to more supply and demand matching and technology getting better. This is depreciation or negative inflation and its value has been chosen as a rate from forecast reports and historical data studies.

The inflation parameters are given in Table 9, that are the early percentage inflation rates multiplied with their cost parameters after the zeroth year (the year of investment). The investment has a 0th-year cash value that is negative. The discounted normalization is added to the OPEX and Revenue to determine the real cost incurred and earned. The deferred difference between OPEX and Revenue for each year is used to determine the present value of money. The cash flow $C_{cash}^t$ is derived as the product of the project’s cash in the prior year and its present value for the current year. The cash flow fluctuates each year according to the present value, which depends on earnings and expenditures.

3. Design Space Exploration

Figure 4. Design Space Exploration architecture.

Figure 4. Design Space Exploration architecture.

• Traditional DCFC: A conventional DC fast charging station that charges EVs directly from the grid without assistance from other sources is evaluated in this scenario for its economic value. General Service Primary (GS-P) is chosen as the preferable tariff in the Traditional DCFC Scenario. This scenario offers a baseline for comparing the solutions created and assessing the benefits of deploying multi-source DCFC stations.
• Scenario A1 strategy: Eliminate the Demand Charges from the proposed DCFC by grid load and interconnection power reduction. Non-Demand Metered (GS-1) is chosen in order to eliminate the demand charges; this tariff does contain energy and fixed charges but there are no demand charges as long as the power is limited to 10 kW.
• Scenario A2 strategy: Reduce the overall electricity consumption. The goal in this case is to lower overall electricity use, which could also include demand charges. There have been two sub-classifications created for this scenario in order to examine the potential for consuming the maximum power from the grid $P_g^M$.

  (a)

  Scenario 2.1: $P_g^M$ is taken as the maximum power possible from the grid based on $P_{POI}$. Given that demand charges are determined by the maximum power drawn from the grid rule, this scenario may result in significant demand costs. However, because there is more power available to utilize, it can aid in the quick charging of EVs and SLBs, depending on the control mechanism employed.

  (b)

  Scenario 2.2: $P_g^M$ is restricted to the least amount of power required from the grid to stay in the GS-S tariff incurring the demand charges (taken as 11kW) despite the $P_{POI}$ connection level. This strategy helps to allow high grid and PV connections while restricting the demand charges.

• Scenario A3 strategy: The proposed solution for enhancing the DCFC system involves adding SLBs and PV systems with minimal changes made to the conventional DCFC stations. By connecting the station to the primary level voltage range, the use case of the proposed DCFC system can be expanded without altering the grid-level functionality of the existing DCFCs. The solution entails adding the required sources and equipment, such as Energy Management Controllers and additional DCDC converters, for the PV and SLB systems to the station.

4. Results

• Economic performance:

  (a)

  CAPEX: CAPEX is the total capital investment done for the project. It is accounted for before the project starts operating and gives a measure of the investment cost required for the selected design parameters.

  (b)

  OPEX: OPEX or Operating cost includes all the money paid to operate and maintain the charging station. Due to varying energy output from PV and grid and the dependence of SLB replacements on their size, different configurations may have different operating costs. So it is a good measure to decide the financial requirements weighing the operating vs capital costs.

  (c)

  Revenue: The revenue through EV charging is fixed but different PV and SLB configurations may have additional revenue streams through Net Metering and SLB refund at the end of the investment.

  (d)

  Demand charge: Higher instantaneous power consumption from the grid results in higher demand charges which can vary the project goals.

  (e)

  Energy charges: Higher energy consumption from the grid causes higher energy charges and by increasing the PV sizing, energy consumption can reduce.

  (f)

  Net Present Value: This is the final economic comparison tool that provides an indication of the value of the project after its completion and involves all the related costs discussed in the economic modeling section. The higher the NPV, the higher the financial value of the project, and a negative NPV signifies that the project is not profitable at the end of its life.

• Station performance: These metrics assess the effects of using different configurations for different strategies on the charging station itself. It allows the project deployment to consider the performance in terms of energy usability and load on the grid.

  (a)

  Net grid energy: This metric is the difference of total grid energy used in a month with the energy supplied back to the grid from PV through Net metering [43]. The negative net grid energy is the extra PV energy that could be used in earning solar credits. The less the net energy is, the less the grid energy consumption and less electricity bill.

  $$E_{g,NET}=E_g^{total}-\left(E_{PV}^{total}-E_{PV}^{used}\right)$$

  (10)

  (b)

  The higher the direct PV utilization, the more suitable it is, as in some locations, net metering is not available and in Ohio, net metering is only permitted up to 120% of the total monthly grid energy used. Direct PV utilization is the use of its energy to match the station’s self-consumption. It is crucial to assess which control and configuration strategies are effective because the extra energy created might not be utilized efficiently. The percentage of used PV energy over all available PV energy is used to compute utilization.

  $$E_{PV}^{util}={\displaystyle \frac{E_{PV}^{used}}{E_{PV}^{total}}}$$

  (11)

  (c)

  Maximum power load on the grid: The other aspect of this project is to reduce the load on the grid and this metric helps in determining the maximum power used from the grid as follows. It is given as $P_g^M$.

• SLB performance: These metrics evaluate the performance of the SLBs for each configurations and scenarios. Due to the interdependence of multiple sources, the current, power, and energy vary the usage of the battery in the station resulting in different aging, electrical and thermal characteristics of the SLBs.

  (a)

  State of Charge (SOC): SOC estimate provides the status of batteries and has to be maintained within defined limits during the operation. The higher SOC though has the benefits of charge available for loads but keeping SOC too high or low increase the rate of calendar aging [42]. As a function of current and capacity, and relates to the battery’s electrical performance, it gives a good depiction to contrast different configurations and scenarios.

  (b)

  Remaining Capacity and Increase in Internal Resistance [42]: This metric gives an indication of State of Health estimation in terms of the energy and capacity deterioration that combines all the calendar and cyclic aging characteristics. The remaining capacity is an indication of how much the battery’s actual capacity is remaining out of the total capacity it has before replacement. The more the battery has been used, the less the remaining capacity it shall have. The internal resistance on the other hand increases with aging and causes power reduction. These both have different effects in terms of battery utilization and replacements for different configurations and are evaluated in the results.The remaining capacity is a metric that indicates the State of Health (SoH) of a battery, which takes into account both calendar and cyclic aging characteristics that lead to energy and capacity deterioration. As the battery is used over time, its remaining capacity decreases, reflecting the amount of actual capacity remaining compared to the battery’s original total capacity. Additionally, internal resistance increases with aging, which can cause a reduction in power. These factors have different effects on battery utilization and replacement for different configurations, and are evaluated in the results.

  (c)

  Number and Life of SLB replacements: The other important factor for deploying the charging station is to understand how quickly and when the SLBs need replacement. And this can help in predicting future decisions on the usage and economic investments.

5. Conclusions

Abbreviations

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