Comprehensive Analysis of Ultra-Fast Charging Station (UFCS) Configurations: Simulations and Optimizations

The transition to electric vehicles (EVs) necessitates advanced charging infrastructure to meet increasing demand. The Ultra-Fast Charging Station (UFCS) emerges as a critical solution in this context, promising rapid charging capabilities. This article presents a thorough analysis of various configurations of the UFCS—specifically, the baseline grid-only scenario and two variations featuring solar photovoltaics (PV) and Battery Energy Storage Systems (BESS). Each setup underwent optimization using Genetic Algorithms (GA) to maximize Net Present Value (NPV), underpinned by demand forecasting through deep learning techniques based on Gated Recurrent Units (GRU).

Baseline Scenario: Grid-Only UFCS

In the initial configuration, the UFCS relies solely on the grid for electricity supply. Demand forecasting indicates an average daily requirement of approximately 9,669 kWh on weekdays and 7,776 kWh on weekends, translating to an annual consumption of about 3.33 million kWh. The revenue generated from EV charging in the first year is projected at €2,332,743.58, with costs for grid electricity amounting to €581,852.90. This scenario yields a Net Present Value of €27.29 million over a 20-year period, serving as a benchmarking reference for subsequent configurations.

Scenario 1: PV Integration

The first experimental configuration leverages photovoltaic energy to reduce grid dependency. The simulation employs Conergy PowerPlus 300 Wp monocrystalline modules. According to GRU-based forecasts, representative days like August 13 (weekday) and August 9 (weekend) illustrate notable energy dynamics:

• Surplus PV Energy: 90,462.30 kWh on weekdays and 78,070.07 kWh on weekends.
• Grid Energy Purchased: 166,045.23 kWh on weekdays and 96,859.92 kWh on weekends.

Graphs illustrate the PV generation against load demand and reveal a considerable amount of surplus energy. Specifically, the results reflect increased energy self-sufficiency, especially on weekends, though significant amounts of PV energy remain unutilized.

Insights from Scenario 1:

While the integration of PV systems leads to a reduction in reliance on grid electricity and contributes to financial savings, it also highlights a critical issue: a temporal mismatch exists between solar energy generation (which peaks during the day) and the charging demand from EVs (which is spread throughout the day and typically higher in the evening). As a result, much of the generated PV energy can go underutilized.

Scenario 2: PV and BESS Integration

The second scenario addresses energy surplus effectively through the incorporation of a Battery Energy Storage System (BESS), which stores excess energy for future use. The outcomes reveal significant enhancements:

• Battery-Stored Energy: 358,308.80 kWh (weekday) and 354,529.78 kWh (weekend).
• Remaining Surplus Energy: 89,956.64 kWh (weekday) and 77,213.23 kWh (weekend).
• Grid Energy Deficit: 165,598.63 kWh (weekday) and 96,103.16 kWh (weekend).

Visual representations of surplus and stored energy, along with daily battery state-of-charge metrics, highlight improvements in energy utilization and reduced dependence on grid electricity. With this configuration, the ability to balance the demand-supply gap is markedly enhanced, particularly during high solar output periods.

Energy Reliability Assessment

To assess the robustness of the UFCS, metrics such as the Energy Sufficiency Ratio (ESR) and Autonomy Ratio (AR) are vital. During weekdays, the ESR indicates that 57.4% of total energy demand is satisfied through local renewable sources, while this figure increases to 78.95% on weekends. Although the AR is slightly reduced on weekends, it underscores the UFCS’s potential for operational independence.

Optimization and Economic Results

The heart of the evaluation lies in the optimization outcomes across all configurations. The Genetic Algorithm implemented in MATLAB aims to maximize NPV over a 20-year horizon, factoring in energy demand forecasts, GRU-based PV output, and associated costs.

For the baseline grid-only UFCS, the NPV stands at €27.29 million. The PV-only system sees this figure rise to €33.48 million—an increase of €6.19 million—illustrating the financial viability of renewable integration, despite remaining challenges with energy utilization.

The PV + BESS configuration further solidifies economic outcomes, achieving an NPV of €33.97 million, which is a gain of €0.49 million over the PV-only setup and €6.68 million relative to the baseline. This configuration demonstrates not only improved energy reliability but also a reduction in surplus curtailment, making it a compelling solution for UFCS deployment.

Sensitivity Analysis

To investigate how evolving market conditions impact system performance, a sensitivity analysis explores future cost reductions for PV and BESS technologies. Adjusted cost assumptions result in an optimal configuration achieving an NPV of €34.05 million, signifying increasing economic attractiveness aligned with declining component costs. This forward-looking approach allows for dynamic infrastructure planning.

Comparative Analysis and Novelty

This study highlights several advancements over previous research in renewable-powered UFCS solutions. Key differentiators include the integration of advanced forecasting methods (like GRU) for precise energy predictions, the dual modeling of weekday/weekend EV charging demand to reflect real-world usage, and rigorous economic optimization that extends beyond short-term analysis. Additionally, the introduction of energy reliability metrics, such as ESR and AR, is a notable contribution to understanding grid independence in energy systems.

Through a holistic approach that combines dynamic forecasting, sophisticated energy modeling, and economic feasibility analysis, this framework represents a significant leap forward in developing sustainable, resilient, and economically viable UFCS architectures. It promises to provide a replicable blueprint for future infrastructure projects aimed at supporting the growing EV market while mitigating grid pressure and enhancing sustainability objectives.