Here are the steps involved in building energy modeling business process to accurately predict a building's energy performance and identify potential improvements between client and building energy modeling consulting firm:
1. Energy Modeling Step #1:
Define project scope: The first step in the process is to define the project scope with the client. This involves identifying the building to be modeled, the type of building (e.g., commercial, residential), and the objectives of the project. It is important to establish clear goals for the project upfront to ensure that everyone is on the same page.
2. Energy Modeling Step #2:
Collect building data: The next step is to collect data about the building. This information is critical for creating an accurate and reliable energy model. Data required includes, but is not limited to:
· Building design elements, such as orientation, shape, and envelope components
· Building systems, including HVAC, lighting, and water heating equipment
· Operational factors, like occupancy schedules, equipment usage, and maintenance practices
· Local climate data, such as temperature, humidity, and solar radiation
Ensuring the data is as comprehensive and accurate as possible will make the energy model’s results more reliable and useful for making informed decisions.
3. Energy Modeling Step #3:
Develop energy model: Once the data has been collected, the building energy consulting firm will use software to develop an energy model of the building.
This process involves:
Inputting the building information, design elements, and operational factors into the software
Defining building systems, such as HVAC, lighting, and water heating equipment
Configuring simulation settings, such as weather data, simulation period, and analysis types
Running simulations to predict energy usage under various conditions, including different weather scenarios, occupancy patterns, or system configurations
The energy model simulates the building's energy performance based on the data collected and can be used to predict how the building will perform under different scenarios.
4. Energy Modeling Step #4:
Analyzing results : The energy model generates a wealth of results, providing insights into the building’s projected energy consumption and potential areas for improvement. This involves comparing the predicted energy consumption to the actual energy consumption of the building over a period of time. Adjustments are made to the model until it accurately reflects the building's energy performance.
5. Energy Modeling Step #5:
Identify potential improvements: With an accurate energy model in place, the consulting firm can begin to identify potential improvements to the building's energy performance. This may involve analyzing different scenarios, such as changes to the HVAC system, lighting upgrades, or changes to occupancy schedules.
6. Energy Modeling Step #6:
Recommend improvements: Based on the analysis, the consulting firm will make recommendations for improvements to the building's energy performance. These recommendations may include specific changes to the building's systems or operations, as well as strategies for reducing energy consumption and costs.
7. Energy Modeling Step #7:
Evaluate cost-effectiveness: The consulting firm will also evaluate the cost-effectiveness of the recommended improvements. This involves analyzing the costs of implementing the improvements against the expected energy savings over time.
8. Energy Modeling Step #8:
Present findings to client: Finally, the consulting firm will present their findings and recommendations to the client. This may include a report detailing the energy model, analysis, and recommendations, as well as a presentation to explain the findings and answer any questions the client may have.
Overall, the building energy modeling business process involves gathering data, developing an energy model, calibrating the model, analyzing potential improvements, recommending changes, evaluating cost-effectiveness, and presenting findings to the client. This process helps to accurately predict a building's energy performance and identify opportunities for improving energy efficiency and reducing costs.