The challenge of justifying industrial prop tech upgrades

Quantifying the benefits of industrial prop-tech upgrades, such as improved efficiency and cost savings, can be uncertain and vary significantly from projections. The process is further complicated by various risk factors, including supply chain disruptions and integration issues, as well as the need to align diverse stakeholder priorities and comply with regulatory standards. These elements collectively make it difficult to create a clear and compelling business case for such upgrades.

Business case challenges

Assessing the prop-tech business case for upgrading plant and equipment in an industrial setting can be challenging due to several factors:

1. Complexity of Costs: Upgrading involves not just the initial capital expenditure but also ongoing costs such as maintenance, training, and potential downtime during installation. These costs can be difficult to estimate accurately.
2. Uncertain Benefits: While upgrades can lead to improved efficiency and reduced operational costs, quantifying these benefits can be tricky. The actual performance improvements might vary from projections.
3. Stakeholder Alignment: Ensuring all stakeholders are on the same page is crucial. Different departments (e.g., operations, maintenance, finance) may have varying priorities and concerns.
4. Market Conditions: Fluctuating market conditions, such as changes in energy prices or demand, can impact the financial viability of the upgrade.

Using modelling software to address challenges

Deep Energy AI

By leveraging the power of AI and data-driven insights, Deep Energy AI provides a comprehensive and accurate assessment of the business case for upgrading plant and equipment, making the decision-making process more efficient and reliable.

Deep Energy AI can significantly aid in assessing the prop-tech business case for upgrading plant and equipment in an industrial setting by addressing the key factors:

1. Complexity of modelling costs: process and analyze data from your existing systems, helping to accurately estimate both initial and ongoing costs. This includes capital expenditure, maintenance, and operational costs.
2. Uncertain benefits: model various scenarios to predict potential benefits such as improved efficiency and cost savings. By simulating different upgrade options, it provides a clearer picture of the expected performance improvements.
3. Stakeholder alignment: facilitate communication among stakeholders by generating detailed reports and visualizations to ensure that all departments, from operations to finance, have a clear understanding of the costs, benefits, and risks involved.
4. Make informed decisions based on market trends and operating conditions: analyse energy prices and the effect on maximum demand, to assess their impact on the financial viability of the upgrade.

Assessing impacts on maximum demand - load profile augmentation

The software enables a load profile augmentation from template upload. The template adjusts the load profile accordingly to simulate the augmentation of electrical load on consumption (kWh) figures from the date range selected where the user can:

1. Define absolute (kW) or relative (decimal multiplier) in 5min, or 15min, up to an hour resolution.
2. Enable positive (load increase) and negative (load decrease) values.
3. Upload multiple augmentations to allow for part or whole of analysis period.

The tool then modifies the electrical load based on user input to calculate:

1. Interval by interval for accurate consumption, maximum demand, and costs from tariff info.
2. Benfit cost ratio and net present value of the investment from load profile augmentation, tariffs, capital expenditure, maintenance, and operational costs.
3. Apply sensitivity analysis with alternative scenarios as iterations quickly.
4. Apply different forecasts for inflation, discounted cash rate, electricity price and more.

Analysis of load profile comparison to baseline scenario in Deep Energy AI