×

Applications & Maps

Community Energy Systems

Energy

Building Optimization

Clean Energy

Energy Resilience

The Future of Community Energy Planning

HARC, along with project partners University of Houston and Fugro, are creating a user-friendly webtool to promote the deployment of District Energy Systems (DES) and community microgrids, known as community energy systems (CES).

The geographic information system (GIS)-based planning tool will allow end-users to assess the feasibility of multiple CES scenarios in a 3D environment. The ability to create a digital twin of the planning area and to incorporate down-scaled climate data and energy systems model, results in a robust, practical planning tool.

A feasibility analysis for a CES can be a time-consuming process. HARC’s tool provides an unbiased, simple-to-use feasibility assessment. End-users with no engineering knowledge will be able to analyze multiple economic scenarios for a CES and be prepared to work with design and engineering teams to build out their CES.

Training Videos

Click to view the training videos:

Keep up-to-date on the development of this tool by signing up for HARC’s newsletter.

Variables Terminology

  • Recommended Solution/Optimal Solution: The best solution determined by analyzing various factors and conditions.

KEY FINANCIAL INDICATORS

  • Investor Goals: The financial objectives established by the user.
  • Initial Invest.: The initial funding provided by the stakeholder for starting the project.
  • Loan: Funds borrowed from a financial institution to finance the project.
  • Annual Savings: The yearly financial savings achieved by the project when compared to the costs of a non-district system.
  • NPV: Net Present Value, the total value of a project’s future cash inflows and outflows, discounted to their present value.
  • IRR: Internal Rate of Return, the discount rate at which the project’s net present value becomes zero, used to evaluate the profitability of investments.
  • DPP: Discounted Payback Period, the time it takes for an investment to repay its initial cost, considering the time value of money.
  • Eq. Annuity: The annual payment amount that, if received each year, would have the same present value as the project’s total net present value.

PROJECT COST

  • Service: The cumulative operational costs over the life of the project.
  • Maintenance: The total maintenance expenses for the entire duration of the project.
  • System Replacements: The aggregate replacement cost of systems during the lifetime of the project.
  • Initial Project Cost: The initial financial outlay for starting the project.

RISK ANALYSIS

  • Risk analysis: An analysis involving 1000 simulated scenarios to assess project risks.
  • Value at Risk (Savings) MAXdNPV: The highest NPV among the 1000 simulated scenarios.
  • Value at Risk (Savings) MEANdNPV: The average NPV among the 1000 simulated scenarios.
  • Value at Risk (Savings) MINdNPV: The lowest NPV among the 1000 simulated scenarios.
  • Probability of Obtaining Savings: The likelihood of achieving a positive NPV in the simulations.
  • IRR over X% at 90% probability: The minimum IRR achieved in 90% of the simulated scenarios.
  • DPP under Y years at 90% probability: The longest payback period within 90% of the simulated scenarios.
  • Sensitivity: The outcome of analyzing how sensitive the IRR or DPP is to different assumptions.
  • IRR Goal (over X at 90%): The target IRR to be achieved in 90% of the cases during sensitivity analysis.
  • Incentive for IRR goals: The incentives needed to reach the set IRR targets.
  • DPP Goal (under Y at 90%): The DPP target for the project, set for sensitivity analysis.
  • Incentive for DPP goals: The incentives required to achieve the DPP targets.

KEY TECHNICAL INDICATORS

  • Demand: The total yearly electricity requirement of the project.
  • Generated On-Site: The amount of electricity produced directly at the project site.
  • From the Utility: The quantity of electricity supplied to the project by the utility grid.
  • Renewable Fraction: The portion of electricity generated from renewable energy sources.
  • Environ. Emissions: The total yearly carbon dioxide emissions from the project.
  • Onsite Fuel to Power Eff.: The efficiency ratio of fuel consumption to electricity generation.
  • Energy to Fuel Ratio: The efficiency ratio considering fuel consumption and the generation of both electricity and heat.
  • LCOE: Levelized Cost of Energy: The average cost per unit of energy produced.
  • Breakeven Point: The annual amount of electricity at which the cost of LCOE equals the grid electricity price.
  • Load Duration Curve: A graph showing the number of hours per year the electricity demand is above a specific threshold, illustrating the project’s demand variability.

POWER GENERATORS PERFORMANCE

  • Rated Capacity (kW): The optimal or user-selected capacity of a technology type for the project.
  • Max Capacity (kW): The highest output capacity achievable by the technology.
  • Avg Capacity (kW): The average output capacity of the technology across its operational period.
  • Annual Operating Hours: The total number of hours the technology operates in a year.
  • Lifespan based on Operation Hours (Years): The estimated operational lifespan of the technology for the project.
  • Starts: The number of times the technology starts up in a year.
  • Energy Generated (kWh/Year): The amount of electricity produced by the technology in a year.
  • Thermal Output (kWh/Year): The amount of thermal energy generated by the technology in a year.
  • Fuel (kWh/Year): The annual fuel consumption of the technology.
  • Efficiency (%): The percentage efficiency of the technology in converting fuel to energy.
  • Env Emissions (kg CO2/Year): The annual carbon dioxide emissions from the technology.

Related Research

array(4) { [0]=> object(WP_Term)#3238 (11) { ["term_id"]=> int(6) ["name"]=> string(6) "Energy" ["slug"]=> string(6) "energy" ["term_group"]=> int(0) ["term_taxonomy_id"]=> int(6) ["taxonomy"]=> string(8) "programs" ["description"]=> string(0) "" ["parent"]=> int(0) ["count"]=> int(99) ["filter"]=> string(3) "raw" ["term_order"]=> string(1) "5" } [1]=> object(WP_Term)#3239 (11) { ["term_id"]=> int(40) ["name"]=> string(21) "Building Optimization" ["slug"]=> string(21) "building-optimization" ["term_group"]=> int(0) ["term_taxonomy_id"]=> int(40) ["taxonomy"]=> string(8) "programs" ["description"]=> string(0) "" ["parent"]=> int(6) ["count"]=> int(22) ["filter"]=> string(3) "raw" ["term_order"]=> string(1) "6" } [2]=> object(WP_Term)#3349 (11) { ["term_id"]=> int(38) ["name"]=> string(12) "Clean Energy" ["slug"]=> string(12) "clean-energy" ["term_group"]=> int(0) ["term_taxonomy_id"]=> int(38) ["taxonomy"]=> string(8) "programs" ["description"]=> string(0) "" ["parent"]=> int(6) ["count"]=> int(34) ["filter"]=> string(3) "raw" ["term_order"]=> string(1) "7" } [3]=> object(WP_Term)#3236 (11) { ["term_id"]=> int(39) ["name"]=> string(17) "Energy Resilience" ["slug"]=> string(17) "energy-resilience" ["term_group"]=> int(0) ["term_taxonomy_id"]=> int(39) ["taxonomy"]=> string(8) "programs" ["description"]=> string(0) "" ["parent"]=> int(6) ["count"]=> int(38) ["filter"]=> string(3) "raw" ["term_order"]=> string(1) "8" } } 1985