What best practices can you use to evaluate renewable energy options with energy modeling software?

1 Choose the right software

There are many energy modeling software applications available, each with different features, capabilities, and limitations. Some are more suitable for specific types of renewable energy systems, such as solar photovoltaic (PV), wind, biomass, or geothermal. Others are more general and can handle multiple options. You should choose the software that best fits your project goals, scope, and budget. You should also consider the ease of use, data availability, validation, and support of the software.

2 Define your objectives and criteria

Before you start modeling, you should have a clear idea of what you want to achieve and how you will measure it. For example, do you want to reduce your energy consumption, carbon footprint, or operating costs? Do you want to increase your energy independence, resilience, or comfort? Do you have any regulatory, financial, or technical constraints? You should define your objectives and criteria in quantifiable and realistic terms, and use them to guide your modeling process and evaluate your results.

4 Perform sensitivity and uncertainty analysis

Energy modeling is not an exact science, and there are always some assumptions, uncertainties, and errors involved. To account for these factors, you should perform sensitivity and uncertainty analysis on your model and results. Sensitivity analysis helps you identify the most influential parameters and variables on your model outcomes, and how they vary under different scenarios. Uncertainty analysis helps you estimate the range and probability of your model outcomes, and how they are affected by data errors or variability.

5 Compare and optimize your options

Once you have modeled your renewable energy options, you should compare and optimize them according to your objectives and criteria. You should use relevant indicators and metrics, such as energy production, savings, payback, emissions, or net present value. You should also consider the trade-offs and interactions between different options, such as their compatibility, integration, or impact on the grid. You should use optimization techniques, such as multi-objective optimization or genetic algorithms, to find the best combination of options for your project.

6 Validate and communicate your results

The final step is to validate and communicate your results to your stakeholders, such as clients, investors, or regulators. You should validate your results by comparing them with actual or expected performance data, or by using independent or alternative models. You should also communicate your results clearly and effectively, using graphs, tables, charts, or reports. You should highlight the benefits and challenges of your renewable energy options, and provide recommendations and feedback for improvement.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?