TOOLS
IDSM: Integrated Demand Side Management Model

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E3’s RESTORE model features an Integrated Demand Side Management (IDSM) tool which assesses the market potential and economics of distributed energy resources (DER) technologies. Winner of the 2014 Utility Analytics Institute Innovation Award, the IDSM feature identifies local market potential for each DER technology type for the study area, and then selects the least-cost portfolios that integrate DERs and meet utility reliability and cost-benefit criteria. The range of DERs that can be modeled with the IDSM tool includes distributed solar, storage, electric vehicles, and demand response technologies, among the others shown in the figure below.

Figure 1: Range of DERs Available for Modeling in the IDSM Tool

 

 

 

 

 

 

 

 

 

Modeling Overview

The objective of the IDSM tool is to predict economic customer adoption of specific DERs and select an optimal portfolio of those technologies based on their system benefits.

 

Figure 2: IDSM Tool Steps

 

 

 

 

The model takes as inputs any federal, state, or utility incentives, technology characteristics, costs and their trajectories, wholesale energy prices or retail rates, and technical potential of different resources, among other sources, to calculate the economic costs and benefits of the DER(s) to the modeled customers.

The IDSM tool then applies an industry-standard Bass Diffusion Model¹ to predict the future number of adopters of the technology. The Bass Diffusion Model uses the customer economics of adoption, the current installed capacities, and technical potential to predict future market shares of different DERs.

Figure 3: Illustrative Bass Diffusion Curve

 

Based on a variety of potential life-cycle benefits, including avoided bulk system capacity, energy, transmission capacity, distribution capacity, ancillary services, emissions, and other environmental externalities, the IDSM tool then evaluates the total system benefits of the modeled DERs and returns an optimal DER portfolio selection that meets user-specified system benefit objectives. See our examples below of how the IDSM tool has been customized and used in the past to deliver insights for our clients.

Figure 4: IDSM Feature Model Data Flow

 

Example Projects

  1. For Tata Power-DDL, a utility in Delhi, India, E3 explored the regulatory and business cases for a broader set of Distributed Energy Resource (DERs) including electric vehicles, demand response, storage, and energy efficiency. The project employed the IDSM tool to first assess the cost-effectiveness of various DER technologies, including electric vehicles, efficient air conditioners, efficient fans, solar panels, and Demand Response (DR) programs. The IDSM tool then simulated customer adoption decision-making processes and the final adoption level. Based on E3’s analysis, Tata Power-DDL decided to focus on a subset of DER programs and identified two DER pilots for the beginning of a distributed energy transition roadmap.
  2. Glendale Water and Power, a municipal utility, enlisted E3 to reach a goal of 10% adoption of customer solar and storage and additional 100 MW peak dispatchable and peak load-reducing capacity. E3 employed the IDSM tool to assess the predicted adoption to several different scenarios with varying utility incentives and rate designs. The scenarios were evaluated not only on whether they reached the 10% target but also on their ability to tribute the benefits of DERs equitably among more than a dozen different customer segments. System-wide impacts on emissions, ratepayer impacts, and utility avoided costs were calculated with the outputs of the IDSM tool.
  3. E3 assisted Silicon Valley Clean Energy (SVCE) in evaluating the adoption potential of Distributed Energy Resources in residential and commercial buildings through a detailed sub-segment breakdown using the IDSM tool. In addition to building electrification, the IDSM evaluation focused on various technologies, including rooftop solar, electric vehicles, and behind-the-meter storage. The results helped SVCE to understand the potential adoption range, which was an important part of the utility’s Integrated Resources Plan (IRP).

 

 

1. Bass, F.M., 1969. A new product growth for model consumer durables. Manag. Sci. 15 (5): 215–227. http://dx.doi.org/10.1287/mnsc.15.5.215.

 

 


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