Share a brief overview of your proposed tool or solution (1 page max) that outlines the essentials of your plan. It should include:
I focused on the integration of renewable energy systems and advanced building technologies to optimize cost and energy efficiency in building design.
Intended users
- Building Owners
- Facility Managers
- Energy Consultants
- Sustainability Coordinators
- Construction Project Managers
Need you’re trying to provide a solution or support for
Building owners, facility managers, energy consultants, and sustainability coordinators are increasingly seeking to reduce operational costs and carbon emissions through the integration of renewable energy systems and advanced building technologies. However, they face significant challenges in (1)Balancing Initial Investments and Long-Term Savings: High upfront costs of renewable energy systems (e.g., solar panels, wind turbines) and advanced building technologies (e.g., smart HVAC systems, energy-efficient lighting) often deter investment. Difficulty in justifying these investments without clear data on long-term savings and return on investment (ROI). (1)Evaluating Cost-Effectiveness: Lack of tools to provide quick, comparative analyses of different energy-efficient design options. Difficulty in understanding the financial and environmental impact of integrating these systems. (2)Optimizing Building Performance: Difficulty in identifying the optimal mix of renewable energy systems and advanced building technologies to maximize energy efficiency and occupant comfort. So, a cost-benefit analysis tool integrated with energy simulation and optimization algorithms can provides clear data on potential energy savings, Life Cycle Cost Analysis (LCAA), ROI, and payback periods, enables quick comparisons of design scenarios with visual reports on energy savings and cost benefits and uses optimization algorithms to recommend the best combination of renewable energy systems and technologies. This tool will empower users to make informed decisions, balance cost and energy efficiency, and meet regulatory requirements while enhancing building performance and sustainability.
Inputs
- Design Variables:
- Solar panel capacity (kW)
- Wind turbine capacity (kW)
- Old and New smart HVAC system efficiency (SEER rating)
- Energy-efficient lighting specifications
- Insulation levels and window types
- window-wall ratio
- Constants:
- Climate and solar radiation data
- Energy prices
- Building codes and regulations
- Financing options
- heating and cooling degree days
- Costs including initial construction costs for various systems and materials, maintenance and replacement costs, discount rate for NPV calculations, local utility rates (electricity and gas prices)
- Sustainability standards
- building geometry
Underlying logic of the model you’ll implement
Energy Simulation:
- Use simplified formulas to estimate energy consumption for heating, cooling, and lighting.
- Calculate potential energy production from renewable sources (solar and wind) using local climate data.
- Q_heating = Overall heat transfer coefficient (BTU/hr·ft²·°F) * Surface area (ft²) * Temperature difference between inside and outside (°F) / Thermal resistance (h·ft²·°F/BTU), Q_cooling = Sensible heat gain + Latent heat gain (BTU/hr)
- Annual energy production (kWh) = Solar panel capacity (kW) * Average daily sun hours * 365 (wind is the same)
Cost Analysis:
- Initial Costs:
- Calculate initial installation costs for renewable energy systems and building technologies. = sum of Area or quantity of system*Unit cost of system
- Operational Savings:
- Estimate annual energy savings from reduced grid electricity and gas consumption.
- Maintenance Costs:
- Calculate annual maintenance and periodic replacement costs.
- ROI and Payback Period:
- Compute ROI and payback period using initial costs and annual savings.
Life Cycle Cost Analysis (LCCA):
- Life Cycle Costs:
- Calculate total costs over the building's lifecycle, including initial, operational, maintenance, and replacement costs.
- = Total initial installation cost + Present value of energy costs + Present value of maintenance costs + Present value of replacement costs - Present value of salvage value
- Net Present Value (NPV):
- Discount future costs and savings to present value using the given discount rate.
Optimization:
- Use algorithms to identify the most cost-effective combinations of design variables that minimize life cycle costs and maximize energy efficiency and savings.
- minimize the LCC, maximize the energy efficient within the standards, minimize the pay back period and maximize the return.
Outputs (the bold items are main outputs, others are the results during the process)
Energy Metrics:
- Annual energy consumption for heating, cooling, and lighting.
- Annual energy production from solar and wind systems.
Cost Metrics:
- Initial installation costs.
- Annual operational savings.
- Annual maintenance and replacement cost
- Total life cycle costs (LCC).
- Net Present Value (NPV) of costs and savings.
- Return on Investment (ROI).
- Payback period.
Optimized Design Recommendations:
- Recommendations of whether the building is suitable to use the renewable energy installation and the best combinations of renewable energy systems and advanced technologies for cost and energy efficiency.