Modeling and Simulating a Renewable Energy System for Performance Analysis

720 Words, 30 Min Read

AssetStudio's AeROS and Weibull-Toolbox programs were used in this article

Introduction

From a reliability standpoint, solar energy systems are generally resilient to failures. However, from an operational perspective, their stability is compromised due to dependence on weather conditions.

This presentation outlines a simulation-based approach to quantify how variations in (1) input energy, (2) load demand, and (3) storage utilization impact the availability of output energy.

The Scenario

The system under study consists of a solar energy setup with battery storage, supplemented by traditional grid power to ensure uninterrupted supply to a load. Figure 1 illustrates the digital twin representation of this system, with energy units normalized for simplicity.

The digital twin includes:

  1. A schematic diagram defining the flow of energy
  2. The energy profile of the source Source (Solar)
  3. The battery settings (Capacity, charging/discharging rate)
  4. The energy consumption profile for the Load
  5. The logic to activate the backup Grid (Meter) when Storage (Battery) is depleted
Digital twin of the solar system
Figure 1: The digital twin of the solar system, modeled using AeROS™ software

Performance Analysis of Renewable Energy Systems Using AeROS™

Solar Panel Power Generation

The solar panel can only produce energy between 8:00 to 17:00 (9 hours) daily. The power is averaged over 9 hours.

Solar panel power generation profile
Figure 2: Solar panel power generation profile

The Daily Average Power (units/hour), between 8:00 and 17:00 hours, was recorded over the past 30 days.

Daily Average Power dataset
Table 1: Dataset of Daily Average Power from 8:00 to 17:00 hours expressed in unit/hour

Load Power Consumption

The load consumes:

  • 60 units/hour from 8:00 to 17:00
  • 30 units/hour for the remaining hours
Load power consumption profile
Figure 3: Load power consumption profile

Key Questions

  • How much power must be drawn from the grid?
  • What is the battery’s usage profile?

The Approach

We start by creating an input energy profile for the Source (Solar) node as mentioned in Figure 2.

Statistical Modeling of Daily Average Power

The Daily Average Power dataset is fitted to a Weibull distribution (β=7, η=100 units/hour).

Weibull distribution fit
Figure 4: Weibull distribution fit for Daily Average Power
Probability-Weibull and PDF plots
Figure 5: The Probability-Weibull and PDF plots

The mean Daily Average Power is 93.3 units/hour.

The Power Generation Profile for the Source (Solar) is created with Daily Average Power distribution.

Solar node power generation profile
Figure 6: Solar node power generation with Weibull-distributed amplitudes

Storage Capacity

The Storage (Battery) node is designed to store this amount of energy over 9 hours, which is 840 units (of energy).

Grid Activation Logic

Finally, the Grid (Meter) is set to standby and will be activated when the battery is depleted, and reset back to standby when the battery is being charged above, say, 2%.

A 720 hours (1 month) simulation run with 1000 executions is conducted.

Simulation settings
Figure 7: Simulation settings

The Results

The simulation aggregates performance metrics over 1,000 executions, providing averaged results.

AeROS software provides an interesting visualization of operating profiles of individual nodes over the simulated period, as shown here.

Operating profiles
Figure 8: The operating profile of the last execution of the simulation
  • Regular Nodes (Load, Grid (Meter)): Can be in Operating, Standby, or Out-of-Service states. Since no failures are modeled, they remain operational. The blue area indicates power consumption.
  • Storage (Battery): Displays charging/discharging cycles.
  • Profile Nodes (Source (Solar), Load Profile): User-defined operating profiles with blue areas representing power flow.
Regular Node statistics
Figure 9: Statistics for Regular Nodes (Load, Grid (Meter))

Grid Power Dependency

From the above figure, Grid (Meter) node supplies 4,416 units of energy over a month.

Grid power supply summary

The Grid (Meter) node is turned on when the battery is depleted. Although it can supply 60 units/hour, only 30 units/hour are consumed. This is because the battery depletion occurs after daylight, and the Load consumption is reduced to 30 units/hour.

Battery Utilization

Battery storage usage
Figure 10: Storage (Battery) node results for a month of operations
  • Full Storage Days: Nearly zero
  • Depleted Storage Days: 5.7 days/month
  • Average Storage Level: ~18%

Energy Breakdown & Cost Analysis

  • Total Load Consumption: 29,700 units/month
  • Solar Contribution: 25,284 units (29,700 – 4,416 from grid)
  • Estimated Cost: $4,416/month (assuming $1/unit)

If you are planning to double the capacity of the solar panel, how much more savings would this yield? How long would it take to recover your investment? These can be explored by adjusting the digital twin and re-running simulations.

Conclusion

This case study demonstrates a statistical approach to assess the operational dynamics of a solar power system, considering supply variability, demand fluctuations, and storage design. The AeROS™ tool enables cost-benefit analysis, scenario testing, and design optimization for such systems.

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