Main Analytical Components

The three main analytical components of a comprehensive Detailed Feasibility Study are acquisition and analysis of metered and field-collected data, computer modeling, and utility bill reconciliation.

Extensive direct system metering and recording activities have a firm scientific basis, but also involve hands-on activities. It involves the practical determination of what to meter, where to meter it, how to meter it, and for how long. It involves activities such as selecting and installing probes and data acquisition systems. Examples include taping voltage and current, installing temperature probes into pipes, setting airflow measurement devices into ducts, over registers, and into exhaust hoods, and measuring power and energy, fuel flow, etc.

Critical to the design and application of an effective metering process is the understanding of how the acquired data will be used. Temperatures, flows, and power requirements of equipment must be analyzed in such a manner that reveals the actual operating characteristics and resource usage of existing equipment and allows for proper sizing of new equipment, development of optimal operating strategies, and determination of associated costs and achievable savings. This process can also be extended to the development of baselines and system performance prediction tools to use for savings verification programs.

The measurement process, be it baseline or postimplementation, continues for a period long enough to encompass the normal variation of the significant factors, or independent variables, which determine the loads and operation of each system. When system-specific metering techniques are used, the senior analyst will make a determination as to the duration of the metering activities. For equipment serving loads that operate consistently over time, short-term metering will be most appropriate. For systems whose loads fluctuate, such as those affected by weather, data should include the key variables that are believed to impact load variation. This data will be gathered through intermediate or even long-term metering, depending on variations, the magnitude of the project,

Technical Information



□ Mechanical, electrical, and architectural drawings; Site plans and floor plans

□ Billing histories for all metered usage (including purchased CHW, steam, and water)

□ Utility rates (copies of the current tariff books)

□ Records from facility-owned submeters

□ Demand profiles, if available (24 hour demands for selected day types)

□ Equipment inventory (e.g., from PM programs); Nameplate and manufacturer's data

□ Automation system documentation (points lists, manuals, diagrams, sequences)

□ Previous submittal packages and equipment operating manuals

□ Reports from previous studies

□ Operating logs, EMS computer trend logs, maintenance records, balancing reports

Operating Conditions

□ Space inventory by function, with location and floor area

□ Environmental control standards (temperature/humidity, ventilation, lighting)

□ Operating schedules (daily, weekly, seasonal hours of operation) for each space

□ Known maintenance or operational problems; Critical deferred maintenance items

□ Shortfalls in equipment capacity or distribution system bottlenecks

□ HVAC control strategies (system operating schedules, setback, and reset schedules)

□ Central equipment operations (sequencing of equipment and auxiliaries, fuel sources)

Operations Management

□ Maintenance practices (standard preventative or predictive maintenance intervals)

□ Work order scheduling systems; Staffing levels

□ Service contracts with outside firms

□ Long-range facility planning documents, such as a Master Plan

□ Design standards (vendors and materials, labeling/tagging, controls compatibility)

□ Applicable regulations and codes

□ Operating budgets (utilities and maintenance)

Financial Information

Incremental Operating Costs

□ Electricity, natural gas, purchased chilled water, other fuels

□ Steam or other heat sources at each thermal level (temperature) required

□ Environmental permitting and emissions controls costs

□ Cost of standby electricity (in electric generation feasibility studies)

□ Cost of capital/debt and cost of insurance

□ Cost/value of required or avoided floor space

□ Reliability and redundancy requirements and associated downtime costs


Investment Costs

□ Technical project support (engineering, planning, commissioning, M&V costs)

□ Costs of systems to be installed with quotes from vendors and subcontractors

□ Energy delivery infrastructure and generation equipment

□ Turnkey construction costs with construction management, demolition, disposal, etc.

□ Utility program incentives or penalties

□ Startup and debugging costs and cost of production downtime

□ Permitting, development, legal, and other consulting fees

Life-Cycle Cost Factors

□ Cost/value of electricity (internal use and, where applicable, power sales)

□ Natural gas and fuel supply cost, contract commitment, and contract security

□ Escalation of energy, water, and OM&R and replacement costs (and contracts)

□ Replacement costs and salvage value

□ Performance degradation

Fig. 41-3 Checklist of Review Items for Detailed Feasibility Study.

Fig. 41-3 Checklist of Review Items for Detailed Feasibility Study.

and the required degree of accuracy. The resultant data can be statistically analyzed to determine the effect of those independent variables on resource consumption and demand, deriving their coefficients in a multiple linear regression.

Since specific metered data is gathered during a given range of operating conditions, this analytical process allows for the development of an operating performance prediction tool to be used to reflect what the usage and demand, and therefore operating cost, would be under any given set of conditions. Examples of independent variables include weather conditions, occupancy, and process production quantity. From this, the baseline performance and usage for each system can be developed, which at any time is the original measured consumption given a set of values for the independent variables. The same process can be followed for establishing post-implementation performance.

Computer building load, system operation, and economic analysis simulation modeling using software such as DOE-2, TRACE©, or HAP© is also a valuable tool in the detailed study process. It allows for interactive analysis of multiple measures and simulation of the impact of proposed and actual changes in facility-wide systems and operations over time. It also allows for rapid testing of numerous potential options for each application type under varying conditions. Simulation modeling automatically accounts for measure interactivity, time-of-use utility rates, independent variables (such as weather), and the effect of a wide range of potential system optimization strategies. Simulations of conditions that can critically affect building and equipment loads (e.g., solar, partial shading, variable schedule-dependent activities, building mass, multiple HVAC optimization strategies, etc.) are straightforward with such modeling and can be arduous and less accurate with other methods. When based on the results of field inspection and calibrated with actual metered data, modeling will allow for consistently reproducible results of the effects of long-term system changes at the facility.

Utility bill reconciliation refers to the matching of analytical results, such as those provided by simulation software, with actual historical records. When adjusted for any given historical year's operation, utility rates, and weather, the baseline model should be able to reproduce the actual costs shown in the historical records. If the predicted and historical results agree (i.e., ± 5 to 10%) for a range of facility activity, the baseline model is validated. The analyst should seek to reconcile all utilities on a monthly, annual, and peak demand basis to ensure model validity.

When these three main analytical components are used together, the metered data and utility bill data provide a factual basis by which to calibrate the model so that results are fully grounded in reality. When so validated, the computer simulation model can then provide a high-powered tool capable of evaluating measures interactively to produce optimal system configurations and can rigorously analyze savings projections.

Figure 41-4 provides a summary of the work required for executing the Detailed Feasibility Study. The table includes the work performed to process and analyze the technical and financial information listed in Figure 41-3, and the results and/or deliverables of that work.

Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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