Optimizing battery performance during modeling comes down to assessing how a battery will charge and discharge in practice. By correctly modeling battery performance, gathering utility rates, and planning usage plans, developers can predict how a storage system will operate and how much financial benefit it will yield once it’s applied to their customers’ sites.

Why Modeling Matters

Accurate modeling is essential for demonstrating the value of storage systems to investors and developers, with solar and energy storage modeling software playing a critical role in that process.

This form of prediction is complicated, however. It requires that a lot of data is gathered, and that that data spans a sufficient period of time for it to be accurate. 

Of course, perfection is impossible, but the more information you have, the more reliable the prediction becomes. When a company is able to provide records of its energy use across weeks or even months (accounting for variations in seasons), models can really zero in on energy use and more accurately predict costs and benefits tailored to that business.

Modeling Complexity

When discussing battery performance models, it’s important to remember the importance of specificity. Not only is this useful for showcasing the benefits of batteries to investors and developers, it’s also helpful when it comes to implementing the system and tracking its successes and failures in real time.

A few aspects of battery performance need to be assessed in order to create accurate models, including:

  • Battery capacity and power ratings, which determine how much energy can be stored and at what rates it can be delivered
  • Wear and tear over time
  • How aging affects storage and power ratings
  • Energy usage history of the company, which shows peak usage and how often it occurs
  • Utility rate structures that show time-of-use pricing and demand charges

 

Using this information, energy storage software can create an optimized charge and discharge schedule, which can help assess battery wear and tear and other factors.

This complex intersection of data and real-world application is part of why energy storage project feasibility assessments are both necessary and difficult to conduct with accuracy. It’s also why quality tools like Energy Toolbase’s ETB Developer are so sought after. 

These tools are able not only to gather all the above information, but to synthesize it into meaningful data that can guide decisions. This synthesized data can also reveal benefits to potential clients.

Making Use of Modeling

When battery performance has been modeled accurately, it opens a whole new world for solar and storage developers to communicate with buyers. For example, with accurate modeling, powerful software can start creating schedules. Predicting the most valuable charge and discharge schedule of a given battery bank is a common use for storage modeling software. 

The best of this software can also collect a massive amount of data and correlate it into actionable steps. It isn’t enough to know when and how much energy is being spent; businesses need to know exactly how to use that information to maximum benefit.

Quality modeling should last the life of a project. In part, this is because predictions need to be verified, and small adjustments over time can change the costs and benefits systems yield, and businesses need to be aware of those adjustments as they happen. Real-time monitoring, especially when it’s automated, also helps detect issues quickly, minimize system downtime, and respond in ways that will optimize savings.

Optimization at the Touch of a Button

Energy Toolbase can help you optimize battery performance in modeling not only to help pitch the benefits of energy storage to potential clients, but to understand entire energy systems. With our powerful software suite, you can gain insight into the life of potential projects from beginning to end.