By definition, commercial and industrial stakeholders tend to maintain large facilities that consume a tremendous amount of energy. The average data center, for example, devotes up to 55% of its energy budget – just to cool its servers.

Similar requirements exist for medical facilities, military installations, manufacturing plants, and industrial parks – all of which require 24/7 access to power in order to guarantee 100% uptime.

This energy commitment is already problematic against a backdrop of rising and volatile utility grid prices. However, it also creates issues as more energy-hungry facilities invest in on-site distributed energy resources (DERs) – ranging from solar to wind to microgrids – in an effort to green their operations and meet increasingly stringent regulatory guidelines.

Managing these intermittent renewable power sources requires understanding how one’s organization consumes energy at both the granular and facility level – a process known as “baselining.” As such, commercial and industrial utility customers are incentivized to explore the greenest and most profitable combination of energy generation and storage assets. 

In short, facilities must be able to accurately predict:

  • How to model the best DER configurations
  • How much solar, storage, and capacity to install 
  • How much energy to use (and when)
  • How to manage and finance upfront capital investments
  • How to forecast projected costs, savings, and revenues

Even when using legacy energy resources – like diesel generators and utility power – this type of forecasting can be challenging. In fact, the US Department of Energy provides resources dedicated to facility fleet optimization for this very reason. However, growing reliance on innovative energy generation technologies – coupled with the rise of smart devices, sensors, thermostats, and the general Internet of Things (IoT) – introduces a host of challenges as large energy stakeholders try to control costs, go green, and future-proof their operations.

Why Facility Energy Optimization Matters

Facility energy optimization isn’t simply an academic exercise. It is foundational to long-term business continuity as the country’s energy mix becomes more fragmented and complex. Below are just some of the driving forces behind growing interest in comprehensive facility-wide optimization:

1. Rising Energy Costs

With utility rates trending upwards, businesses of all sizes must take proactive steps to control energy spending while still meeting operational objectives. Once installed, for example, distributed energy assets like solar power, wind turbines, and battery storage can help shield utility customers from rising grid electricity prices. However, the degree of protection ultimately depends on what complement of DERs are installed – and how they are actively managed.

Done correctly, for example, solar power coupled with battery storage allows commercial industrial stakeholders to engage in peak shaving, solar smoothing, demand charge avoidance, and time-of-use (ToU) utility bill savings.


2. New Regulatory Guidelines

Businesses must comply with local, state, and federal government regulations guiding carbon emissions and building energy optimization codes. These regulations not only impact new green projects, but they can also retroactively affect existing investments as well.

In most cases, regulatory guidelines are nonnegotiable – even if they vary substantially from one locale to the next. This variability poses significant challenges for those looking to become and remain compliant.


3. Public Demand for Sustainability

In addition to official governmental green targets, there also exist a body of informal expectations from the general public. Companies have both a moral obligation and fiscal duty to their employees, suppliers, vendors, and customers to make sure their operations align with larger societal sustainability goals.

This includes minimizing the negative environmental impact of delivering goods and services through the intelligent management of green assets designed to reduce each facility’s carbon footprint.


4. Potential Monetization Strategies

Although most commercial and industrial stakeholders go green to control costs, it’s becoming increasingly possible to monetize the renewable power generated using privately owned distributed energy resources.

For example, one can now:

  • Sell unused solar and wind power on wholesale energy markets. When paired with intelligent battery storage management, this approach unlocks unprecedented arbitrage opportunities for those who are able to consistently “buy low and sell high.”
  • Generate solar renewable energy certificates (SRECs) – i.e. green credits that can also be sold on open exchanges.
  • Enroll in feed-in tariff programs that allow utility customers to feed excess solar and wind power into the electricity grid. These incentives are similar to net energy metering programs. But instead of earning utility credits, feed-in tariff participants receive actual cash payments for any unused renewable power they sell to their utility providers.

Proven Strategies for Optimizing Facility Energy Management

Facility energy optimization can be applied at nearly every scale – from building sustainability projects to campus-wide improvements to redesigning entire cities:

  • At the micro level, improvements can range from upgrading lighting systems to implementing occupancy sensors. As more facilities embrace the Internet of Things, they benefit from true integration in which energy consumption, production, and storage data is shared in real-time across all connected devices.
  • At the campus or industrial park level, optimization might include strategic siting of newly constructed buildings and other infrastructure to minimize transportation needs – while also maximizing efficiency.
  • At the municipal level, strategies might involve using public transportation powered by renewable energy – instead of relying more heavily on privately owned, gas-guzzling vehicles.

However, taking advantage of these facility energy optimization benefits involves a more holistic approach that can accurately account for the millions of tiny variables that might exist. Even at the micro level, facilities often find it difficult to design, achieve, and maintain an optimal balance of distributed energy resources. This is especially true as grid conditions and operational needs evolve over time. Projects that initially received the green light often struggle to deliver returns as a result of this ever-changing landscape. 

Fortunately, a new generation of emerging tools is helping to level the playing field – providing investors, facility managers, and other stakeholders with the confidence they need to move forward with new green projects – and reconfigure existing ones that have already been deployed in the field.

The Role of Artificial Intelligence in Facility Energy Optimization

Teams of human engineers and facility operators have historically been tasked with finding the optimal balance of green investments to power their operations. However, the sheer amount of technical, feasibility, and financial data to analyze when researching potential green investments is overwhelming. Even with the best forecasting and facility energy management tools, investing in green technologies involves taking on a host of risks – especially as regulatory guidelines, grid conditions, and energy demands continue to evolve.

By contrast, artificial intelligence (AI) can do all of the above faster and more accurately – given its ability to collect, analyze, and autonomously act on large data sets. Better still, AI can do this in real time across thousands of potential configurations to instantly identify the optimal combination of distributed energy resources before ground is ever broken. This real-time analysis even includes factoring in the ratings, warranty guidelines, and technical limitations of each individual distributed energy resource in the system to both optimize performance and extend the useful lifetimes of these edge devices.

Artificial intelligence can also perform a similar function with existing DERs – actively controlling sensors and collecting data from receivers across all edge devices facility-wide. For example, an AI-powered DERMS platform can automatically discharge on-site batteries or power off lights based on real-time energy demands instead of relying on manually set schedules. The same is true for peak shaving or demand charge avoidance, with AI intelligently finding the optimal time to power a facility’s operations with solar power, stored energy, or grid electricity – i.e. whichever source is cheapest and most available at that exact moment in time.

In addition, AI can analyze both market and grid conditions to correctly forecast the price of energy seconds, days, and even weeks into the future. Knowing the future price of energy confers a competitive advantage on open exchanges since one can now “time the market” based on profit maximization.

Most important, this approach is scalable.

In fact, the larger and more complex the system becomes, the more historic and real-time data the AI algorithm can analyze. This leads to vastly improved forecasting – thanks to iterative machine learning in which earlier predictions are matched against real-world results to generate increasingly accurate forecasts over time.

Discover How Our AI Can Help Optimize Your Facility’s Energy Needs

Mitigating the effects of climate change requires rapid decarbonization across every sector of society. Energy-hungry stakeholders sit at the vanguard of this larger movement. But when using legacy tools to analyze potential green investments and manage the influx of intermittent renewable power generation, businesses of all sizes increasingly struggle to balance the demands of rising energy prices, stricter government regulations, and growing public pressure to green their operations.

But in terms of speed and accuracy, artificial intelligence has already proven far more capable than humans at finding this ideal balance – both for newly constructed projects and for distributed energy resources that are already operational. Better still, these capabilities will only improve as AI-powered algorithms continue to analyze more data and refine its predictions.

To learn how Veritone’s AI-powered DERMS technology can help your own organization green its operations and control rising costs, schedule a free demonstration with our facility energy optimization team today.