This article walks you through some of the most common steps when considering the deployment and operation of a battery storage system, and shows you the power of data monitoring, smart algorithms, and simulations to maximize the economic return of battery energy storage systems throughout their lifetime across multiple revenue streams.
In this article, we set out five steps to successfully operating a BESS. We’ll explain how BESS analytics tools like data monitoring, smart algorithms, and simulations can maximize economic returns. We’ll also show how battery intelligence technology can minimize risk across multiple revenue streams throughout the lifetime of a BESS.
The modern world is rapidly transitioning to renewable energy sources. This shift is causing a significant need for energy storage systems (ESS). Increased demand for ESS has lowered overall associated costs and expanded deployment options.
A popular and efficient storage solution is provided by lithium-ion batteries (LIBs). LIBs are relatively low cost with high power and good energy density. However, companies are now releasing that there are considerable difficulties in profitably operating a battery energy storage system (BESS) over its lifetime.
To ensure BESS ventures are profitable and can operate optimally over their lifetime, companies need to find solutions to a range of problems. They must identify the best BESS deployment option and calculate the upfront and operating costs. The longevity of a BESS is crucial to its profitability, so issues such as battery aging and ongoing maintenance requirements must be addressed. Immediate and potential safety risks must be identified and then mitigated or eliminated.
Overcoming the operational challenges posed by BESS requires sophisticated technological solutions. By employing battery intelligence and smart algorithms, stakeholders can gain valuable insights to enable more informed decision-making.
Taking a BESS from the design stage to operation is a highly complex process that can take years. While it’s an impossible task to anticipate all the issues that may arise on this journey, companies can act to protect their investment by leveraging advanced BESS analytics tools.
The journey toward creating a BESS begins in the planning and procurement phase. To secure investment and funding, a BESS concept must be proven fit for its application. The right battery chemistry must be decided upon and there has to be a realistic estimate of the profitability of the entire system over its lifetime.
A project developer needs to identify opportunities, conduct feasibility studies, develop a comprehensive project plan, and manage the regulatory process. The system integrator must analyze project requirements, assess the impact of the load profile on battery factors, and design an ideal battery configuration. Asset managers work to minimize financial and technical risks and ensure the BESS is properly maintained and operates at peak performance throughout its lifetime.
The right battery cell choice is crucial. Today, companies can choose from a variety of different battery cell types and styles from various manufacturers.
Nickel Manganese Cobalt (NMC) cells and Lithium Iron Phosphate (LFP) cells are commonly used in stationary energy storages. NMC cells are the more established technology and are widely used in the automotive industry and for portable electronic goods. NMC cells are competitively priced with good overall performance. They provide high energy density and are considerably lighter than LFP cells.
However, NMC batteries are not as thermally stable as LFP cells, making them a riskier choice for stationary energy storage systems. NMC batteries also have significant environmental costs, especially if they contain cobalt.
Batteries with LFP cathode chemistry have demonstrated their suitability for battery energy storage systems due to their extended lifespan and reduced susceptibility to failure. LFP cells are also cheaper and have lower operating costs than NMC cells.
More information on LFP cells in the context of energy storage systems can be found here.
Battery simulation models can provide valuable data on the optimum cell choice. Different battery models can be tested with specific load profiles to gain insights into the degradation of these battery cells during operation. This results in an accurate estimate of the safe operational lifespan of the system.
The optimal operation strategy will ultimately depend on a range of factors. These include where the BESS is located and what market it serves. A BESS may be a stand-alone system or may be situated next to a solar or wind farm as part of a larger renewable energy project. It may need to provide power for US markets like ERCOT, CASIO, or MISO or serve European markets such as Nord Pool, EPEX SPOT, or UKPX.
Employing a multi-purpose operating strategy can increase the overall profitability of a BESS. Profitability considerations often focus solely on daily monetary profit. However, battery degradation and capacity loss should be evaluated for all operation modes over time.
Knowing when to run operating strategies such as energy arbitrage, frequency regulation, demand response, and peak shaving is crucial.
In determining the most promising option for a BESS, various load profiles and scenarios can be tested using battery simulation models. The operating strategy can be adjusted to compare its impact on battery degradation and lifetime - all before the actual system is built.
Once a suitable battery cell has been chosen, the system must be deployed. Commissioning in the energy storage context refers to the process of ensuring that a newly installed energy storage system functions as intended and meets the specified performance requirements. This involves testing and verifying all components and systems, as well as fine-tuning the settings to optimize performance and efficiency.
Digital technologies can play a significant role in the commissioning process. With digital commissioning, asset owners can proactively identify potential issues before deployment. The initial status of a BESS can be ascertained at the Beginning of Life (BoL) with minimal effort. Digital commissioning only requires an internet connection. It supports the on-site commissioning process as it pin-points where issues could occur, providing vital input to on-site teams.
Digital commissioning is a fast, dependable, and effective approach for evaluating the performance of energy storage systems and confirming the details provided by the integrator. It ensures consistent outcomes across diverse energy storage systems, allowing for more efficient asset management.
As BESS expand, digital commissioning processes can be scaled accordingly at very little additional cost and without requiring additional time. This contrasts with the cost of conventional commissioning which increases with plant size and takes more time to accomplish the larger the BESS grow.
Identifying and fixing faulty cells during the deployment stage reduces the risk of downtime later during the storage lifetime, helping to avoid penalties and costs associated with downtime. Using digital commissioning, a BES system can be ready for operations in less time than traditional commissioning. Â
The KPIs and information provided by digital commissioning allow asset owners to verify the information provided by the integrator and can serve as benchmarks for future reporting. Gathering information at the BoL stage makes it easier for an asset owner to make warranty or deficiency claims.
Digital commissioning can be used to analyze a massive amount of data. This cannot be done on-site or with additional hardware measurements. Manufacturing failures or other issues can be precisely located. Weak modules can be replaced before operations begin.
There must be a continuous data connection to the BESS during the entire digital commissioning process. The digital commissioning system calculates the initial Discharge- and Charge Energy Capacity, DC-DC Roundtrip Efficiency (RTE), and the DC Resistance (DCR) for the BESS. These complex calculations are based on string-level data and aggregated on the inverter level.
Onsite commissioning is unlikely to identify defects that occur at more granular levels than the inverter level. Since defects are more prevalent at finer levels, digital commissioning can identify a greater number of issues than what would be possible using only on-site measurements.
The next step is to ensure the BESS can sustain optimal performance over an extended lifespan. Although many potential issues can be identified and solved during the deployment stage, a BESS must be closely monitored while in operation. The health of the BESS needs to be constantly assessed and maintained to maximize performance capabilities and accurately predict battery life.
Every BESS is regulated by an energy management system that controls battery current, voltage, and temperatures to maintain safe conditions. This is done by using physical sensors to measure real-world variables and employing models and smart algorithms to estimate the state of charge and health of each battery.
Energy storage health analytics can be used to efficiently monitor the health of an entire BESS portfolio. With the right software, asset owners can access comprehensive overviews of the health of their systems on one dashboard. Crucial insights can be provided on a per-asset basis.
A centralized cloud-based analytics platform can provide battery health data in real-time. Data from multiple locations across the globe can be analyzed with powerful AI tools.
In this way, dedicated energy storage health analytics software can deliver detailed root-cause analysis and provide more detailed insights into predicted aging behavior. This data enables stakeholders to take immediate steps to avoid issues and extend the lifetime of the BESS.
The larger a BESS is, the more difficult it is to keep it in good health. Without efficient tools, monitoring the health of an entire portfolio of systems is incredibly complicated. Manufacturers’ KPI calculations can differ, and each manufacturer may provide different monitoring software.
While an asset owner may have access to large amounts of data, many energy management systems have inadequate processing and analyzing capabilities. Often, these systems only provide limited insights into how to optimize battery health or extend the lifetime of the BESS.
Now that the system is operational, steps must be taken to mitigate risks associated with underperformance, failures, and critical safety issues such as burning battery storage.
Asset owners need to eliminate short- and long-term risks to batteries over the lifetime of a BESS. The longer a BESS can remain operational, the more profit it will generate. The actual usage of the batteries determines the longevity of a BESS as does preventing safety issues such as battery failures or worst-case scenarios like fires.
Risks can be minimized by ensuring that a BESS operates within its warranty constraints and by leveraging battery analytics to identify safety issues and predict future risks.
Performance warranties indicate the number of cycles until the battery reaches a specific capacity loss. In most cases, a multi-use BESS operating strategy won’t conform to the load profile of these specific cycles. Â
Performance warranties also contain operating constraints such as optimum temperature, average State of Charge, C-rate, and others. Although energy management systems (EMS) can limit the current, voltage, and temperature of batteries, they are not fail-safe. An EMS cannot analyze historical data and so cannot show long-term trends or anomalies.
Dedicated warranty trackers can show if storage systems and racks are being operated within warranty agreement thresholds. Teams can be instantly alerted to deviations and strategies can be changed to prevent voiding warranties or incurring penalties.
Maintaining the quality of individual components enhances the performance, lifetime, and safety of a BESS. If the required manufacturing standards are not adhered to this can create safety issues that lead to financial risks for asset owners and integrators
Battery analytics provide a second layer of safety. They give teams more time to react, provide accurate root-cause analysis, and enhance risk prevention. Battery analytics use intelligent algorithms to recalculate equivalent full cycles and provide insights into the actual BESS health status based on thousands of data points. Safety risks can be detected months before they become critical.
Finally, asset owners want to maximize the profit potential of their BESS. Ensuring a satisfactory return on investment (ROI) requires the system to always be operating at maximum availability. Â
Typically, the performance of batteries is judged by key performance indicators (KPIs) like state of charge (SoC) and state of health (SoH). However, most monitoring systems don’t provide granular insights into factors that impact availability.
Implementing a cloud-based monitoring system can maximize the revenue potential of a BESS. A sophisticated monitoring system can identify issues, enhance availability, increase output, and drastically decrease downtime.
A BESS can last for many years, even decades. As the lifespan of the BESS increases, so too does the value of historical data. A cloud-based monitoring system can track and collect data and issue automated reports. This can identify areas of improvement and ensure the BESS consistently operates at the highest possible availability.
Customized monitoring systems can provide detailed information on storage performance and round-trip efficiency. They can provide immediate data on issues that impact performance, such as voltage spreads, temperature spreads and DC resistance, and module imbalance. This enables a deeper understanding of issues that affect availability.
Finding an optimum operating strategy for a BESS isn’t an easy task. Each battery should be assigned an operating strategy that takes into account arbitrage, frequency regulation, demand reduction, peak shaving, and frequency.
Annually, an average of 35,000 decisions about how and when to charge or discharge batteries are made by complex algorithmic trading systems. However, algotraders make decisions on the revenue potential of a strategy without the benefit of historical insights.
Integrating battery analytics ensures that factors like the degradation effect of each operating strategy are considered. Decisions must consider the effects of degradation, as battery aging can impact the overall lifespan of the battery and so affect long-term profitability.
Considerable costs and resources are involved in designing, deploying, maintaining, and operating a BESS. The use of predictive analytics software can ensure that a BESS delivers maximum availability and profitability throughout its lifetime. Following the steps in this article will help stakeholders protect their investments and get the most out of their energy assets.
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