Energy Analytics Background
If the cost of energy is important to your business, then you need energy analytics.
Commercial Energy Analytics are typically addressed in the context of a building or facility and the focus is almost always on energy consumption. Why is that? The answer is usually because energy consumption is the most common, and often the only metric available when it comes to reducing costs. But reducing consumption doesn't always reduce costs.
Energy Analytics, on the other hand, enables an enterprise to address energy cost (not just energy consumption) like any other direct expense associated with the process of making, moving or storing your products or services. These analytics take into account the factors affecting energy cost to the enterprise.
Energy analytics synthesize three distinct but inter-related pieces of information:
- Not just energy but how much energy and power an enterprise uses, when it’s used and where it’s used.
- What and how much an enterprise makes, moves or stores; where it performs this work, when it performs this work, and how this work changes and scales.
- What an enterprise pays, and how it procures, energy and power.
The simplistic approach to energy cost reduction focuses on basic energy efficiency and limited demand reduction techniques and projects. This approach also yields limited returns. This is usually a good place to start, however complex energy environments with dynamic complicated tariff structures require a more sophisticated approach to achieve greater energy cost reductions. These analyses cannot be effectively performed with the historical spread sheet approach and require unique data acquisition, algorithms and visualization to realize, quantify and capture the available costs reduction opportunities.
Many energy cost reduction efforts fail not because the projects are performed badly, but because they neglect to take into account 2 crucial factors:
- Energy use and generation must support the business and scale as business conditions change; and,
- Energy cost reduction is not necessarily directly related to energy usage reduction.
The second point is not always obvious, and often requires explanation. But, depending upon the tariff, reducing load may not save money, and simply shifting load to the wrong time can be expensive. Often, business and operating conditions don’t offer a lot of flexibility, and energy analytics can help chart a path around unique business constraints.
A Water District Example
In a contract awarded by the California Energy Commission (CEC), UC Davis’ Center for Water and Energy Efficiency is running a project with Helio Energy Solutions at the Moulton Niguel Water District to better understand how water utilities can become a key tool in helping California manage its roller coaster electricity supply-and-demand challenges.
Over the next three and a half years, researchers at UC Davis will utilize Helio Energy Solution’s PredictEnergy software platform to develop technologies and processes to integrate California’s water infrastructure with the electrical grid. The Moulton Niguel Water District in Laguna Niguel, has volunteered as the proving ground for a cutting-edge approach to respond to the daily ebb and flow of the State’s energy consumption as weather patterns place changing and challenging demands on available energy.
Moulton Niguel Water District spends approximately $2 million per year to power its water services for 170,000 customers in South Orange County. CWEE researchers will combine water system hydraulic modeling with Helio Energy Solution’s software platform to create a demand management system that supports grid health and simultaneously reduces Moulton Niguel’s energy costs.
The project uses PredictEnergy’s software analytics module, leveraging real-time energy analytics to develop an energy management approach that adapts to changing energy demands throughout the day. Changing energy rate structures for Moulton Niguel’s potable and recycled water systems create challenges and opportunities to support the grid and simultaneously reduce energy costs for rate payers. PredictEnergy analytics enables Moulton Niguel to visualize its operations from an energy cost perspective. It will apply complex and dynamic utility rates and visualization so plant operators can “see” current efficiency and production.
While the system is complex, the plan is simple: When energy is in high demand, plant operators shift processes to minimize power requirements, when energy is in surplus, operators adjust to bolster storage in anticipation of the next demand.
For more information on reducing energy costs at Moulton Niguel Water District please click here.
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