MATLAB simulations can account for uncertainties in EV charging patterns by employing stochastic modeling techniques, such as Monte Carlo simulations or probabilistic load flow analysis, to assess the probabilistic impact on distribution system voltage profiles.
- Monte Carlo Simulations:
- Generate random samples representing different EV charging scenarios based on probability distributions of charging patterns (e.g., Gaussian distributions).
- For each sample, simulate the EV charging load on the distribution system using MATLAB.
- Perform load flow analysis for each scenario to calculate the voltage profiles throughout the system.
- Aggregate the results from multiple simulations to analyze the probabilistic impact on voltage profiles, considering voltage violations or deviations from desired levels.
- Probabilistic Load Flow Analysis:
- Define probability distributions for key parameters affecting EV charging, such as charging demand, plug-in times, and charging durations.
- Utilize MATLAB's probabilistic load flow analysis tools or develop custom algorithms to solve load flow equations considering uncertain parameters.
- Generate multiple scenarios by sampling from the defined probability distributions.
- Solve load flow equations for each scenario to determine voltage profiles under different charging conditions.
- Analyze the ensemble of results to understand the probabilistic impact on distribution system voltage profiles, including voltage violations and system reliability metrics.
