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The report identifies significant barriers to deep energy efficiency retrofits in the U.S. commercial sector, primarily centered on financing, a lack of performance data, and split incentives. While 71% of surveyed stakeholders express high interest in deep retrofits, the private sector remains risk-averse, often requiring short payback periods of 2-4 years. The study concludes that providing targeted informational resources, such as case studies and improved energy modeling tools, is essential to reduce perceived risks and stimulate industry-wide activity.

The document details the cost assumptions for oil, natural gas, and coal used in the Union of Concerned Scientists (UCS) Reference case. The UCS model primarily adopts assumptions from the EIA's AEO 2008 High Energy Project Cost and High Energy Price cases but modifies the duration of cost escalations. Specifically, the UCS Reference case limits pipeline cost escalation to 2014 and construction cost escalation to 2010, whereas the EIA often projected these increases through 2030. The text compares these assumptions with the AEO 2009 Reference case, noting differences in projected price trajectories for crude oil, wellhead natural gas, and coal through 2030.

The Empire State Building underwent a deep energy retrofit involving the remanufacturing of 6,514 windows into 'superwindows', chiller plant upgrades, and the implementation of direct digital controls. By coordinating energy upgrades with a larger $550 million remodel, the project achieved a projected 38 percent energy use reduction and annual cost savings of $4.4 million, with an incremental simple payback period of three years.

The Long-range Energy Alternatives Planning System (LEAP), developed by the Stockholm Environment Institute, is an integrated modelling tool used in over 150 countries for energy policy analysis and greenhouse gas emission tracking. It supports both demand-side and supply-side methodologies, allowing users to create medium to long-term scenarios (typically 20 to 50 years) to evaluate the environmental and social impacts of various policy options. LEAP is distributed free of charge to academic, governmental, and non-profit organisations in the developing world and is used by more than 85 countries for reporting to the UNFCCC.

The research develops MARKAL-Equity to assess how different income terciles in Canada respond to the energy price increases associated with meeting Kyoto targets. Findings indicate that low-income households are the most vulnerable, experiencing the greatest reductions in energy service demand and consumption, and lacking the financial capacity to switch to more efficient technologies compared to middle- and high-income groups.

The document details CATF's costing approach for CCS retrofits, which utilizes a standalone gas-fired auxiliary boiler for steam to avoid coal plant heat rate penalties, contrasting this with the IPM platform v6's integrated approach. It provides specific capital and operational cost data for 200 MW and 400 MW coal retrofits, as well as NGCC retrofits, noting that while IPM costs favor very large plants through economies of scale, the CATF approach is more favorable for 400 MW units.

The document argues that while Canada has made progress in decarbonizing power supply, achieving net-zero requires Energy Systems Integration (ESI)—the coordination of energy systems across multiple pathways and scales. It examines five key ESI technologies (electric vehicles, heat pumps, demand response, distributed generation, and hydrogen) and finds that Canadian policy is currently too siloed, relying on voluntary 'soft' incentives rather than systemic market reforms or mandatory legislation. The author highlights significant gaps in information, governance, and implementation, suggesting that a holistic, pan-system approach to modelling and planning is essential to avoid sub-optimal infrastructure lock-in.

The report examines the current state of Energy Systems Integration (ESI) in Canada, focusing on five key technologies: electric vehicles, heat pumps, demand response, distributed generation, and hydrogen. It argues that while Canada has successfully decarbonized its electricity grid, further progress requires coordinating energy vectors and scales. The author identifies significant barriers, including fragmented governance, a lack of integrated modeling, and a policy landscape dominated by voluntary 'soft' incentives rather than systemic mandates. The document recommends replacing sectoral subsidies with market reforms that remunerate grid flexibility and implementing integrated modeling platforms to guide coordinated infrastructure investments.

The document outlines how energy modeling can be transformed from a late-stage accounting tool into a strategic design driver. It advocates for an integrated design process where modelers engage from the concept phase to influence fundamental decisions on building size, orientation, and passive loads. By utilizing 'theoretical minimum' energy models and Life Cycle Cost Analysis (LCCA), modelers can provide economic justifications for efficiency measures, potentially reducing both first costs and lifetime energy consumption.

The Reinventing Fire industry model uses a stock-flow framework and EIA Annual Energy Outlook 2010 data to simulate the adoption of energy-saving measures in the U.S. industrial sector from 2010 to 2050. It tracks energy consumption, fuel expenditures, and capital investment across various manufacturing and non-manufacturing industries. The model incorporates efficient technologies, combined heat and power (CHP), waste-heat-to-electricity, and integrative design for machine drives, while accounting for refining transformations as demand shifts toward biofuels and hydrogen.

The 'Renewable Qualified' variable allows users to specify the percentage of a process's output that is considered renewable, ranging from 0% to 100%. While typically used for wind, solar, hydro, and biomass, the document warns that users can manually mark any process as renewable regardless of feedstock, and notes that some hydro and biomass projects may not meet specific Renewable Portfolio Standard (RPS) qualifications.

The Time-Series Wizard is a three-page tool in LEAP used to create time-series expressions through various mathematical functions and data sources. Users can select from interpolation, step functions, and smooth curves for future data points, or use linear, exponential, and logistic projections to extrapolate from historical data. Data can be entered manually via keyboard, imported or linked from Microsoft Excel, or retrieved from the LEAP Cloud Database Server (LCDS), which provides international open-source data on energy, emissions, and development.

The Analysis View in LEAP allows users to build the structural framework of their energy model through a tree organized by categories such as Demand, Transformation, and Resources. Users enter data and modeling relationships using mathematical expressions in data entry tables, which support color-coding to distinguish between explicitly entered and inherited values. The view includes tools for scenario management, unit conversion, and expression validation, alongside a bottom pane for visualizing data via charts and tables, documenting references in a Notes tab, and constructing complex formulas in an Expression Builder.

The 'Minimum Share of Production' variable ensures a specific process supplies at least a defined percentage of a fuel's total annual production, regardless of cost-effectiveness, to model policy targets or contractual obligations.

The document provides technical instructions for setting up Transformation analyses in LEAP, detailing the hierarchical structure of modules and processes used to model energy conversion sectors. It outlines the four-step setup process—identifying modules, sequencing them by energy flow, setting properties, and entering technology data—while explaining the roles of feedstock, auxiliary, and output fuels in calculating primary resource requirements.

The document describes how LEAP uses scenarios as self-consistent storylines to model future energy systems under various socioeconomic and policy conditions. It details the relationship between scenarios and Current Accounts data, the inclusion of sensitivities, and the use of a hierarchical expression inheritance system to streamline data management.

The document describes the functionality of LEAP's Cost-Benefit View, which calculates capital, operating, and maintenance costs across energy systems, including optional environmental externalities. It emphasizes that the tool focuses on social opportunity costs rather than consumer prices or financial viability, and allows users to define costing boundaries to accommodate data limitations regarding upstream technologies.

The document defines feedstock fuels as those converted within a process, noting that process efficiency is the ratio of total output energy to total feedstock energy. It distinguishes feedstock fuels from auxiliary fuels, which are subsidiary energy inputs not converted in the process and therefore excluded from efficiency calculations. Most processes typically use a single feedstock fuel with a 100% share.

The document describes the functionality of annual emission constraints in LEAP, noting they are used to set maximum annual pollutant levels across an energy system during least cost optimization of a Transformation module.

The document describes the cost-benefit calculation capabilities of LEAP, detailing the types of costs it can track, the importance of defining system boundaries to avoid double counting, and the use of real and discounted currency units to determine Net Present Value (NPV) between scenarios.