The Smart Grid Investment Model (SGIM)TM

Background

The lack of publicly available, independent, objective and comprehensive smart grid financial cost benefit financial models applicable to individual electric coops and public utilities provided the motivation to develop the Smart Grid Investment Model (SGIM) through the Smart Grid Research Consortium (SGRC) developed at Texas A&M University in early 2010. The SGRC transitioned to an independent research and consulting firm in January 2011. The SGIM was applied for 15 individual utilities by early 2012. SGRC staff worked with utilities to assist in evaluating individual smart grid investments, investment strategies and to apply the model to evaluate vendor proposals, to track investment costs and benefits and to provide other smart grid financial evaluations.

The remainder of this page provides a brief description of the SGIM.

Smart Grid Investment Model (SGIM)TM Characteristics  

The Smart Grid Investment Model includes:

  • A 20-year, quarterly financial smart grid cost/benefit accounting framework with utility customer class, end-use electricity use detail
  • Utility-specific monthly kWh, peak kW, load profile forecasting models to determine smart grid hourly load program impacts by customer class and end-use
  • Explict representation of all important costs and benefits including avoided power purchase costs and avoided capacity investment costs for generation, transmission and distribution (as appropriate for each utility)
  • Cost/Benefit analysis of individual smart grid technologies and programs from the substation to behind-the-meter applications, including
    • Advanced communications and metering
    • Distribution automation
    • Volt/VAR and conservation voltage regulation
    • Customer reliability valuations
    • Pricing programs
    • Direct load control
    • Programmable communicating thermostats and similar customer-facing technologies
    • Other demand response technologies and programs
    • Impacts on utility management systems (OMS, DMS, etc.)
  • Intuitive, easy-to-use Excel-based software
  • Cost/benefit parameters, parameter ranges and guidelines to begin smart grid investment analysis at your utility
  • Scenario, what-if, and other analysis features required to develop cost-effective smart grid investment strategies

Modeling Approach

The Smart Grid Investment Modeling approach applies four basic steps to evaluate smart grid investment costs and benefits including:

  1. Identify each technology and program that fits within the smart grid purview,
  2. Identify benefits of each technology/program including cost savings, operational efficiency and reductions in customer kWh, peak kW and hourly load profiles over the next twenty years,
  3. Identify technology, installation, program and management costs based on utility and customer characteristics, and
  4. Compare benefits and costs to determine investment returns.

These steps are illustrated in the figure below.

Smart Grid Investment Model Schematic


Importance of Customer Class/End-Use Load Profiles

Smart grid-related reductions in peak period hourly loads are a critical contribution to smart grid investment benefits for most utilities. Technologies such as direct load control and programmable communicating thermostats as well as programs such as critical peak pricing reduce peak period loads resulting in reduced power purchase, generation and transmission costs. However, these financial benefits vary widely across utilities depending on weather characteristics, air conditioning and water heating saturations, customer premise characteristics and other factors. Furthermore, customer class electricity use characteristics change over time.

Few electric cooperatives and municipal utilities have customer class /end-use (e.g., air conditioning) load profile information or forecasting models required to incorporate this dynamic element in a comprehensive cost-benefit analysis. Consequently, a priority task in implementing the Smart Grid Investment Model for each utility is developing a monthly kWh, peak demand and customer class/end-use hourly load profile forecasting and smart grid technology/program analysis model.

This integration of energy and load profile forecasting models within a detailed smart grid cost benefit framework reflects a significant contribution to the current state-of-the-art in smart grid investment analysis applications. Utilities can evaluate investment options considering alternative growth scenarios, impacts of existing utility and demand response programs, and impacts of non-utility programs such as changes in appliance efficiency programs.

Example Smart Grid Peak Day Imacts

Intuitive Financial Analysis  

The Smart Grid Investment Model provides intuitive financial analysis results documented in a final report and presentation. The model uses an Excel workbook platform composed of tabbed worksheets including utility data, customer data, smart grid options, AMI benefits and costs, distribution automation benefits and costs and customer program benefits and costs. The SGIM is available, as an option, for implementation at client utilities including training and on-call support. All SGIM models are maintained by the SGRC for future use as the need arises to address new smart grid investment issues.

Standard cost benefit financial statistics including net present value, internal rate of return, quarterly costs and benefits and other data are provided along with intuitive chart presentations including discounted net benefits (cumulative benefits minus cumulative costs at each quarter in the future), cumulative benefits and cumulative costs as illustrated in the charts below.
Example Analysis Charts

More on the Smart Grid Investment Model business case analysis.