The legislation outlines a set of control functions critical for analyzing the building's various technical systems, such as heating, domestic hot water production, cooling, ventilation, lighting, sun shading, and the centralized technical building management. For each of these control functions, performance levels are assigned, ranging from zero to a maximum of four, alongside a corresponding Building Automation and Control (BAC) class, distinguishing between residential and non-residential buildings.
This framework helps in determining the building's automation level. The automation system is categorized into Class D, C, B, or A, based on the minimum performance level across all implemented functions. In this hierarchical system, the lowest class predominates. For instance, if all control functions meet the criteria for Class B, but one is rated Class C, the entire building is classified as Class C. This approach ensures a comprehensive assessment of the building's automation capabilities, highlighting the importance of each control function's performance level in achieving optimal efficiency and management.
Example performance levels from the ISO 52120 standard.
To estimate the total investment for meeting a higher ISO 52120 rating, the building was segmented into four key areas:
The presence or absence of equipment is determined based on the difference between the audit (which describes what is already present) and the desired automation class. The investment cost is determined from this bill of quantities (including the cost of necessary software). Additionally, the need for air handling units is also calculated, based on standard architecture of SE offerings.
To determine the Smart Readiness Indicator (SRI) scores, we developed tables for each domain, outlining the correlations between the control functions defined by the ISO 52120 standard and those relevant to the SRI. This effort was underpinned by an in-depth analysis of the various levels of control functions, adopting an engineering approach that goes beyond merely noting the presence or absence of external factors such as Building Management Systems (BMS), grid connections, renewable energy sources, storage systems, electric vehicle (EV) charging stations, and building certifications. Instead, it emphasized the complex interactions among multiple control functions.
The next step involved establishing connections with the SRI to calculate its related percentage scores, utilizing the SRI spreadsheet for this process. In aligning with the SRI, a deliberate choice was made to use Method B from the service catalog, taking full advantage of all control features available. In the calculation, these functions were applied to 100% of the building. However, the SRI allows for adjustments based on the percentage of presence, offering flexibility in the assessment. A revised SRI spreadsheet was introduced to evaluate how enhancements in the ISO classification affect the SRI percentage. This included selecting various SRI target classes for specific functions, based on the upgraded classifications provided by the standard.
The investment required to implement the Smart Readiness Indicator (SRI) accounts for external factors not considered in ISO 52120 calculations, such as EV charging stations and renewable energy systems with storage. These elements contribute to the desired SRI class but do not influence ISO ratings directly. Here's a simplified breakdown of the cost calculations and assumptions for achieving SRI targets:
The final investment cost includes the sum of expenses for EV charging stations, photovoltaic panels, and batteries, depending on their presence in the building. This total cost was then divided by the building's total area to derive a cost per square meter. It's important to note that this expense is in addition to the costs associated with achieving the ISO rating.
The energy efficiency of buildings is rated on a scale from A4 (highest efficiency, lowest energy consumption) to G (lowest efficiency, highest energy consumption). Our current tool does not the full assessment required by legislation, as it does not include information on the geometry of the buildings.
Instead, the SRI/EPC Estimator implements a heuristic approach that estimates energy consumption and class based on expected consumption for a given ISO 52120 class. This involves comparing a building's energy use and fuel mix against a predefined energy class table to estimate its baseline energy category.
To predict the building's energy class after implementing energy-saving measures, we first calculate the energy savings resulting from moving up ISO classes. These savings are quantified in annual energy savings (kWh/year) and tonnes of oil equivalent savings per year (toe/year), then normalized to energy savings per square meter by dividing by the building's total area. Subtracting these savings from the building's original energy consumption (kWh/year) provides an estimated post-intervention energy use, which is then compared to the energy class table to approximate the building's new energy class.
It's important to note that this method offers a rough estimate and doesn't replace a detailed energy performance analysis conducted by a certified professional. The estimated energy class after interventions serves as an initial guide to the potential for enhancing the building's energy efficiency.
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