PREFACE
Against the global shift toward a low-carbon economy and sustainable development, many countries and regions have introduced fiscal incentives and subsidies to support renewable energy deployment—providing strong momentum for the growth of commercial and industrial (C&I) energy storage systems. At the same time, businesses in these regions are increasingly challenged by rising energy costs and tightening environmental regulations, which drive the urgent need for economic and sustainable energy solutions. In this context, high-efficiency and high-reliability storage systems have become essential for enterprises to reduce emissions and lower operational costs.
Pylontech has cultivated deep expertise in the global energy storage market for over fifteen years. To promote sustainable industry growth and empower C&I end users, power retailers, and channel partners to make more informed investments, Pylontech introduces the “Profit and Performance Commercial and Industrial Energy Storage System Solution White Paper.” This white paper offers insights and forward-thinking approaches in areas such as economics, performance, and system efficiency, providing valuable reference for stakeholders across the industry.
Application Scenarios: Case Studies
The rapid development of renewable energy has enabled commercial and industrial users to either build their own or participate in energy storage projects to optimize power consumption strategies. By storing electricity during off-peak periods and discharging during peak-price hours, enterprises can significantly reduce their electricity expenses. Moreover, energy storage systems enhance energy self-sufficiency, reduce dependence on conventional grid supply, and mitigate risks associated with power instability. The following two case studies illustrate typical challenges faced by C&I users in power consumption, and how energy storage solutions can address them effectively.
1.1 A Manufacturing Plant in Hungary
With a steady increase in production orders, a manufacturing plant in Hungary began facing a critical constraint: the existing transformer capacity could no longer meet the growing electricity demand. The chart below illustrates the plant’s average daily energy usage during a peak production period, clearly showing that transformer limitations were significantly restricting the factory’s ability to operate at full capacity—leading to extended delivery times and reduced operational efficiency. Operating under overload conditions not only reduces energy efficiency but also poses severe safety risks, including potential equipment failure and fire hazards. As a result, the factory urgently needed to increase its available power capacity to meet production demands and ensure operational continuity.
Statistics of The Enterprise Energy Load in Q4
Enterprises typically have two primary pathways to expand their power capacity: traditional power expansion and energy storage dynamic expansion
While traditional power expansion can fundamentally address capacity shortages, they often come with high capital investment and extended lead times. In contrast, dynamic expansion of energy storage avoids the need for large-scale infrastructure construction. It offers a more cost-effective and time-efficient alternative, and can be rapidly scaled in line with rising production demands. Beyond addressing power capacity constraints, deploying an properly configured energy storage system can generate additional economic benefits through a variety of use cases, including peak-valley arbitrage, demand charge reduction, demand-side response participation, backup power supply, participation in electricity market trading and more.
These applications of C&I ESS collectively support faster, more flexible growth for commercial and industrial users.
1.2
A Large Hotel in San Diego, USA
A large hotel located in San Diego, California—a region with high penetration of renewable energy—operates a six-story facility with a total floor area of approximately 11,000 m².
Hotel Profile:
Installed PV System
250
Maximum power demand
Annual electricity consumption
2.9 kWp Million kWh kW
Distributed Solar
Annual Electricity Bill
$571,000
564
Energy Usage Charge
$449,000
$122,000 Demand Charge
Despite the PV installation, electricity costs remain high due to a mismatch between PV generation and load demand peaks, forcing the hotel to purchase electricity during peak tariff periods and incur high demand charges. To address this issue, the hotel deployed a 250 kW / 522 kWh lithium battery storage system for cost optimization. Under the control of an intelligent algorithm, the system charges during off-peak night hours when electricity is cheapest, and discharges fully during evening peak-price periods to maximize arbitrage benefits. Furthermore, because demand charges increase significantly when peak load exceeds 500 kW, the storage system is also used to cap peak demand below this threshold, reducing the hotel’s demand-related expenses.
As a result, the storage solution delivers significant cost savings, cutting electricity bills by approximately $5,000 per month during the summer.
Load (KW)
It is evident that for C&I buildings like this hotel—with significant day-night load fluctuations—co-located distributed energy storage systems combined with rooftop PV are already beginning to demonstrate economic viability in electricity cost management.
Maximizing Profitability with C&I Energy Storage Systems
In the context of the energy transition and the evolving electricity market, C&I energy storage system is increasingly regarded as a strategic tool to enhance energy efficiency, improve operational flexibility, and support sustainable development goals.
However, deploying energy storage systems involves significant capital investment, making a comprehensive economic feasibility assessment essential. By considering factors such as supported revenue models, business models, and feasibility analysis models, enterprises can identify the most effective pathway to achieving an attractive return on investment.
Deploying C&I energy storage systems is not merely a technological upgrade—it is a financially sound, future-oriented investment aligned with broader low-carbon ambitions.
2.1 Diversified Revenue Models
C&I energy storage systems can be applied across a wide range of scenarios, including peak shaving, load shifting, renewable energy integration, backup power, grid services, energy management, microgrids, and EV charging support. The following revenue models enable C&I users to unlock greater value and support rapid business growth:
Time-of-Use Arbitrage
Charge during off-peak periods and discharge during peak-price hours to capture price differentials and reduce electricity costs.
Demand Charge Management
Discharge during peak demand to reduce maximum load, helping lower demand charges in utility bills.
Backup Power
Provide instant power during outages or grid failures, ensuring critical systems and production lines remain operational and minimizing economic losses.
Virtual Power Plant
Aggregate multiple distributed storage systems to form a virtual plant that participates in grid dispatch and ancillary markets for additional revenue.
Ancillary Services
ESS can provide rapid-response capabilities for frequency regulation, load balancing, and spinning reserves. These systems can store excess energy and release it when needed, improving grid flexibility.
Dynamic Capacity Expansion
Discharge stored energy during transformer overloads to reduce strain and avoid costly infrastructure upgrades—while still enabling arbitrage-based savings.
2.2 Business Models for C&I Energy Storage System
C&I users, project owners, and financial investors are adopting differentiated approaches to capitalize on energy storage investments. At present, there are mainly three business models for the operation of C&I ESS.
Energy management contracts
Energy management contract (EMC) is a third-party investment model. The ESS project owner signs an energy management agreement with the end user, overseeing the system’s construction, operation, and maintenance, while defining a revenue-sharing model for storage-related benefits.
Financial leasing
Financial leasing companies can be introduced as lessors of energy storage equipment. During the lease period, the ownership of the energy storage equipment belongs to the financial leasing party and the owner has the right to use it. After the lease expires, the owner can obtain the ownership of the energy storage equipment.
Owner-owned investment
The owners of industrial and commercial enterprises invest and benefit themselves, and the main profit channel is peak-valley arbitrage. This can directly reduce the electricity cost, but the C&I user needs to bear the initial investment cost and annual equipment maintenance cost.
2.3 Economic Feasibility Analysis
For commercial and industrial users, deploying an energy storage system is a significant investment decision. Economic feasibility assessments help determine whether a project can deliver sufficient returns. Key financial metrics such as Net Present Value (NPV) and Internal Rate of Return (IRR) are calculated based on initial capital expenditures (including batteries, inverters, etc.), installation and maintenance costs, and projected returns from electricity cost savings, time-of-use arbitrage, and ancillary service revenues—discounted over the system’s lifecycle.
The system's scale and configuration have a direct impact on its economic performance. Through proper calculation, enterprises can optimize the storage system’s capacity-to-power ratio, identifying the most cost-effective setup. Economic modeling also enables businesses to assess project-related risks—such as electricity price volatility or policy shifts—and develop appropriate risk mitigation strategies accordingly.
Critical Factors of C&I Energy Storage Systems
As electricity market liberalization continues to expand, more business owners are actively exploring commercial and industrial energy storage projects. However, the complexity of business models and the relatively high upfront investment still present substantial risks. How to further unlock the utilization value of energy storage systems and improve their economic return has become a critical challenge for the industry. This calls for higher performance standards across the system’s lifecycle energy throughput, intelligent scheduling, and O&M services.
3.1 System Efficiency and Cycle Life
To improve return on investment and ensure long-term value, a C&I energy storage system must strike a balance between energy efficiency and cycle life. Maximizing total energy throughput per unit cost requires both high round-trip efficiency and a long service life.
ESS Total Throughput Over the System's Lifetime
Capacity for Any Number of Cycles
Energy Ef ficiency
Refers to the ratio between the energy discharged and the energy charged into the system. This metric directly affects the economic return of each charge-discharge cycle.
• Battery System State Estimation: Accurate estimation and management of battery state is fundamental to ensuring both system safety and operational efficiency. Inaccurate estimation can lead to overly conservative depth-of-discharge limits, lower system utilization, and increased safety risks.
• Thermal Management: Data from multiple energy storage plants show that round-trip efficiency during winter is on average 2% higher than in summer, with thermal management accounting for approximately 30% of total system losses. An efficient thermal management strategy can significantly reduce auxiliary power consumption and enhance overall system performance.
Battery Cycle Life
Cycle life determines the long-term economic value of the storage system. It must be supported by high-quality battery cells, optimized charge-discharge strategies, and effective thermal management to minimize cell degradation and extend system longevity.
System
3.2 Energy Management and Dispatching
The Energy Management System (EMS) is a critical component of any energy storage system. It comprises both hardware and software that are responsible for monitoring, controlling, analyzing, and optimizing energy flow and consumption across the system. EMS ensures that charging and discharging operations are scheduled intelligently to maximize efficiency and cost-effectiveness.
In the event of a grid fault, the EMS must enable millisecond-level frequency and voltage responses to support grid stability. Therefore, intelligent control strategies, ultra-fast device response, and highly validated coordination mechanisms are essential to achieve efficient energy utilization and ensure reliable power supply.
3.3 Operation and Maintenance
C&I energy storage projects are typically deployed across multiple industrial and commercial sites. Routine monitoring and maintenance often require personnel to travel between locations, resulting in high management complexity and elevated operational costs. When multiple sites require on-site support simultaneously, resource bottlenecks may occur, leading to delayed response times and disruptions to system performance.
As a result, the adoption of intelligent operation and maintenance (O&M) solutions has become a vital pillar in achieving safe, efficient, and sustainable operation of commercial and industrial energy storage systems.
Pylontech C&I Energy Storage Solutions
As a pioneer with 15 years of deep engagement in the energy storage industry, Pylontech possesses extensive technological know-how and proven product application experience. Guided by a customer-centric development approach, we have consistently focused on both profitability and performance. As a result, we have continued to developing advanced technologies and competitive product advantages. The following are three critical parts:
High Efficiency and Long Cycle Life
Intelligent Scheduling
Seamless Operation with Smart System Management
VERTICAL PRODUCTION CHAIN AND CORE TECHNOLOGY
Management Battery Module
Management
4.1 High Efficiency and Long Lifespan: Significantly Reducing Levelized Cost of Energy (LCOE)
4.1.1 Pylontech’s High-Precision BMS Design
In lithium iron phosphate (LFP) energy storage systems, algorithm design plays a pivotal role in performance optimization and operational safety. Among them, the algorithms for State of Charge (SOC), State of Health (SOH), and cell balancing form the core pillars of a Battery Management System (BMS), directly impacting system reliability, efficiency, and lifespan.
SOC Algorithm
The estimation of the State of Charge (SOC) is a critical function of the Battery Management System (BMS), as it reflects the remaining capacity of the battery. Accurate SOC estimation helps prevent overcharging and over-discharging, extends battery life, and optimizes energy management strategies. Due to the nonlinear voltage-SOC relationship of lithium iron phosphate (LFP) batteries—particularly within the mid-SOC range—traditional estimation methods often struggle to achieve high accuracy.
Pylontech employs a Double Sigma Point Kalman Filter (DSPKF) algorithm for SOC estimation in its LFP batteries. This advanced algorithm enhances accuracy when dealing with nonlinear systems and also provides excellent real-time performance and robustness. It continuously updates the SOC estimate by integrating
Key features of the algorithm include:
• Online parameter identification of the equivalent circuit model using dual Kalman filters, improving the accuracy of model parameters used in SOC estimation;
• Advanced filtering techniques that outperform conventional methods such as ampere-hour integration and extended Kalman filters in terms of estimation accuracy;
• Industry-leading accuracy, maintaining full-range SOC estimation error within 3%;
• Validation through DST (Dynamic Stress Test) conditions as defined in standard GB/T 38661. The new SOC algorithm was tested under continuous DST cycling and compared against the traditional Kalman filter method. Results are illustrated in the figure below (left).
Dynamic Stress Test Accuary of Dynamic Stress Test
As shown in the above (right) figure, the proposed new SOC algorithm demonstrates significantly improved accuracy, with estimation errors consistently maintained within a 3% margin.
SOH Algorithm
The State of Health (SOH) is directly related to the evaluation of battery condition and service life. It reflects the extent of capacity degradation compared to the battery's initial state. During long-term cycling, factors such as ambient temperature and usage patterns can introduce inconsistencies, thereby affecting the accuracy of SOH estimation.
For energy storage systems, obtaining a timely and accurate understanding of battery health is essential for fault prediction and preventive maintenance. Pylontech adopts the Two-Point Method for SOH estimation. This approach estimates battery health by calculating the actual discharge capacity between two SOC reference points. It is a simple and intuitive method—actual charge/discharge capacity is computed using ampere-hour counting. However, one of the key challenges in practice is acquiring accurate SOC reference points and maintaining estimation reliability. In this method, two SOC points are selected: one at full charge, and the other at rest after deep discharge. This approach effectively minimizes deviations caused by SOC estimation inaccuracies and improves capacity evaluation reliability.
To verify the validity of the SOH algorithm, a long-term aged battery module was selected for testing. The actual capacity degradation observed during cycling was compared with the SOH estimation results to assess algorithm accuracy:
• As shown in the figure, a significantly aged module was chosen to validate SOH estimation effectiveness;
• The comparison between actual and estimated SOH values shows that the error remained within 2%.
Global Balancing Algorithm
Inherent differences among individual battery cells can lead to inconsistencies in voltage and capacity over extended use, ultimately impacting the performance and lifespan of the entire battery pack. As such, balancing algorithms play a crucial role, especially in lithium iron phosphate (LFP) energy storage systems, where global passive balancing strategies are widely adopted. Traditional voltage-based balancing logic is not fully suitable for LFP batteries, as the voltage difference between cells during the flat voltage plateau is minimal—even when there are significant capacity differences. This makes it difficult to trigger balancing based solely on voltage.
Pylontech adopts a balancing strategy based on available residual capacity. The objective is to ensure that all cells within a battery pack maintain consistent usable capacity levels. This approach effectively keeps the operational state of all cells aligned, enhancing overall system stability and performance. In large-scale battery systems, energy loss associated with passive balancing becomes a critical design challenge. Accurate calculation of balancing time requires high-precision SOC and SOH algorithms.
SOH Estimate SOH SOH Error(%) SOH
Pylontech's global balancing algorithm is built upon this foundation, with a framework that enables intelligent and effective balancing control:
Dynamic at low SOC
Resting state at low SOC
Determine the reference cell (internal resistance and capacitance are normal)
Charging terminal status
Dynamic in the platform area
Calculate balancing time remaining
Determine balancing enable flag bit
Execute the Balancing commands on eligible cells
Close the Balancing commands on Ineligible cells
The global balancing strategy offers the following advantages:
• Dual-factor evaluation using both cell SOC and voltage enables more accurate identification of cells requiring balancing. This reduces the risk of incorrect or ineffective balancing and minimizes the negative impact of over-balancing on cell lifespan.
• Compared to conventional voltage-based balancing, global balancing provides more frequent and flexible balancing opportunities for eligible cells, thereby improving both balancing efficiency and overall cell consistency.
• Unlike traditional voltage-based strategies, which typically activate balancing only at the end of discharge, Pylontech's global balancing approach improves balancing efficiency by over 60%.
• Following GB/T 38661 balancing test standards, experimental results confirm that the global balancing strategy delivers significantly improved balancing performance.
Charge and Discharge for a Period of Time (No Equalization Algorithm)
Global Equalization Algorithm
4.1.2 Advanced Thermal Management Technologies and Strategies
Extreme temperatures—either too high or too low—can negatively impact the charging and discharging efficiency of a battery system. Moreover, temperature uniformity across battery cells directly affects cycle life and long-term performance. Modern C&I energy storage systems require low-power thermal management strategies that maintain optimal operating temperatures, minimize energy loss, extend battery life, and improve overall system efficiency. Traditional cooling methods often rely solely on cell temperature as the control variable, neglecting factors such as ambient temperature, thermal system lag, and system load profiles. This can result in insufficient cooling during high-load operation, compromising safety, and frequent on-off cycling, which increases energy consumption.
Optimized refrigerant selection
Enhanced heat exchange efficiency
Improved system layout
Smart control algorithms
Thermal Management Optimation Strategy
These innovations significantly reduce energy consumption on the system side, while improving overall energy efficiency and usable battery capacity. Pylontech further enhances control precision by constructing battery equivalent circuit models, thermal models, and electro-thermal coupling models. Using dynamic programming algorithms, it computes global optimal thermal trajectories for battery operation. Leveraging a big data platform, the system monitors and forecasts future operational states. By dynamically setting optimal cooling temperature targets, the system uses fuzzy PID algorithms to adjust compressor speed and cooling water temperature—achieving predictive thermal shutdown and minimizing cooling system energy use.
With this optimized strategy, the temperature difference within a single battery rack (cluster) is ≤ 3°C, and system-wide cell temperature variation is ≤ 5°C. This balance between precise thermal control and auxiliary power efficiency results in:
Extended Battery Life
Improved System Performance
Tangible Economic Returns for End Users
For example, under 25°C ambient conditions, an M7 liquid-cooled cabinet operating at 0.5P continuous charge/discharge reaches thermal equilibrium with a maximum surface temperature difference of only 3°C, ensuring consistent thermal performance under real-world C&I load conditions.
4.1.3 Cell Performance and Cycle Life Optimization
High-quality battery cells are the cornerstone of long cycle life in energy storage systems. As LFP-graphite cell technology continues to evolve, Pylontech has taken a comprehensive approach to improving cell performance and extending lifespan through multiple innovation paths:
Electrolyte Formulation Optimization
By precisely adjusting the types and concentrations of electrolyte additives, the solid electrolyte interphase (SEI) is formed with optimized thickness and porosity, enabling faster lithium-ion transport, lower interfacial resistance, and higher energy efficiency—ultimately extending cycle life.
Crystalline Structure Optimization
Controlling synthesis conditions to achieve smaller grain sizes or higher crystallinity improves ion migration within active materials. This accelerates lithium diffusion, enhances charge/discharge capability, and indirectly contributes to longer cycle life.
Material Stability Enhancement
Using chemically stable, high-temperature-tolerant materials reduces undesirable side reactions during cycling. For example, LFP cathode materials show lower degradation rates than graphite anodes during extended cycling. In contrast, NCM cathodes degrade faster than graphite, making LFP-based cells generally more durable than ternary lithium alternatives.
Surface Engineering and Sintering Optimization
Through surface coating techniques and sintering process refinements, Pylontech reduces active material surface area and structural defects—effectively suppressing unwanted reactions between electrode materials and electrolytes, thereby improving long-term cell stability.
The test results based on IEC 62620 show that after optimizing the electrolyte, the battery efficiency increased to 96.26%. The pre-lithiation technology can effectively improve the battery's cycle life by 4,000 cycles.
Energy Efficiency@25℃, 0.5P
Retention (1C/1C, 25°c)
Li-ion Battery Cycling Performance
Number of Cycles
4.2 Intelligent Dispatching to Maximize Returns
The Energy Management System (EMS) plays a pivotal role in intelligent dispatching across three key dimensions as following:
Optimized Energy Management
EMS centrally manages and dispatches all connected energy storage units, ensuring optimal energy allocation. It dynamically adjusts charge and discharge schedules based on load demand, generation availability, and electricity price fluctuations—maximizing operational efficiency and minimizing cost.
Demand Response and Grid Interaction
EMS enables smart interaction with the grid, automatically adjusting system behavior in response to grid signals and pricing schemes. During supply shortages or grid stress events, EMS supports load balancing and helps mitigate peak demand pressure through coordinated response.
Improved Energy Utilization and Economic Return
Through intelligent dispatching and optimization, EMS minimizes system energy losses and boosts storage performance. In volatile electricity markets, EMS leverages real-time pricing data to strategically schedule charging and discharging—driving profit maximization for end users.
Unlike traditional EMS solutions that rely on predefined rules and static parameters, Pylontech’s EMS-Agent employs AI-driven adaptive control to dynamically optimize charging and discharging strategies. By analyzing historical load profiles, regional electricity prices, and system behavior, EMS-Agent automatically generates demand management strategies tailored to specific usage scenarios. It supports multi-objective optimization, simultaneously addressing:
Revenue maximization under full-load operations
Incremental gain optimization
System safety and lifecycle protection
This ensures safe system operation while extending equipment life and improving long-term performance.
Forecasting Accuracy Improvement
Leveraging large-model AI techniques, EMS-Agent improves load forecasting accuracy by 18% to 25%. During peak production periods, forecasting error is reduced to less than 5%.
With precise electricity price forecasting, the system charges during the lowest-price periods and discharges during peak-price windows. When price fluctuation ranges between 15% and 20%, the optimized EMS charging strategy can generate up to 12% to 18% in additional economic return. Price Volatility Response
Power Station State
Optimization
4.3 Seamless Operation with Smart System Management
4.3.1 Simplified Installation Process
Pylontech’s outdoor cabinets and containerized products are delivered in a pre-integrated, prefabricated format, offering significant advantages in installation efficiency and commissioning convenience. Before shipment, all core subsystems—including the battery system, thermal management, fire protection, and control systems—are fully assembled, tested, and fine-tuned in the factory. Each unit undergoes rigorous factory acceptance testing to ensure system stability and functional integrity.
Upon delivery, on-site deployment requires only the connection of power and communication harnesses between cabinets and between the system and the grid interface panel. This streamlined process enables rapid commissioning, reduces construction costs, and minimizes operational risk.
4.3.2 Real-Time Online Monitoring & Full-System Visibility
Pylontech’s cloud-based intelligent O&M platform enables real-time data interaction and system-level diagnostics. It features functions such as fault prediction, thermal runaway alerts, and battery life forecasting.
These capabilities significantly reduce O&M costs by:
• Lowering the routine maintenance workload and improving personnel efficiency
• Providing early fault warnings, enabling maintenance teams to identify issues in advance
• Supporting proactive maintenance planning tailored to site-specific conditions, minimizing the risk of unexpected downtime and associated financial losses
This intelligent, data-driven approach delivers greater reliability, safety, and long-term value for energy storage system owners and operators.
4.3.3 Remote Diagnostics & Maintenance Support
During system operation, any faults or alarms are automatically logged within the mobile app. Customers can submit fault events online through the app to Pylontech’s after-sales support platform. Technical engineers can then access the system via remote monitoring, assist in real-time diagnostics, and provide fast, targeted solutions—minimizing system downtime and ensuring efficient issue resolution.
Unlocking Economic Efficiency with Pylontech C&I ESS Solutions
Pylontech’s latest liquid-cooling C&I energy storage solutions offer significant improvements in both performance and efficiency compared to traditional air-cooling systems. The C&I ESS solution features an optimized BMS architecture in both hardware and software level, enhanced by the company’s latest SOX algorithm. This next-generation solution delivers higher energy density, improved performance, and greater efficiency, while maintaining robust safety standards.
Building upon its core technology, Pylontech has simultaneously launched three integrated C&I storage products: OPTIM US L260-OMNI, OPTIM US L417-BAT, and CONTAINER L5000-BAT. These products are designed to address a wide range of application scenarios, with system capacities ranging from 30 kWh to 5000 kWh, covering everything from commercial buildings to industrial parks, and from behind-the-meter to front-of-the-meter applications. The product lineup offers full-spectrum coverage of energy storage needs—scalable from kilowatt-level small applications to megawatt-scale large projects. Whether for small businesses with precise energy demands or large industrial campuses seeking high-efficiency energy management, Pylontech provides tailor-made solutions to ensure diversified and optimized energy storage deployment.
• Applicable scenarios include:
Time-of-Use Arbitrage
Demand Charge Management
Pv-Coupled Storage
Dynamic Capacity Expansion
Demand-Side Response
Emergency Backup Power
OPTIM US L260-OMNI is a 125 kW / 261 kWh all-in-one cabinet solution that integrates all core subsystems—including battery modules, BMS, PCS, EMS, thermal management, fire protection, and power distribution—into a single enclosure. The system supports front-side maintenance, reducing footprint by 25% and increasing energy storage capacity by 13% compared to conventional solutions. Each unit can operate independently or be paralleled with multiple systems for scalable capacity expansion. This flexible architecture makes it ideal for a wide range of commercial and industrial applications.
M7-L417-Centralized type-EU——Solution
M7-L417-Distributed type-EU——Solution
OPTIM US L417-BAT is a 471 kWh battery cabinet that integrates battery modules, BMS, thermal management,
CONTAINER L5000-BAT is a 5 MWh energy storage solution housed in a standard 20-foot container. Except for the PCS, all core subsystems—including battery modules, BMS, EMS, thermal management, fire protection, and power distribution—are fully integrated within the container.
The internal layout features a communication and power convergence cabinet, enabling streamlined integration of data and power wiring. External connections are simplified, requiring only plug-in access to the pre-configured communication and power interfaces.
The system supports both centralized and string-type PCS architectures, offering high flexibility for large-scale C&I and utility-side deployments.
After deploying Pylontech’s OPTIM US L260-OMNI system at the hotel site (as detailed in Case Study 1), the customer is able to benefit from multiple revenue streams. With a battery round-trip efficiency (RTE) > 95% and cycle life exceeding 8,500 cycles, the system delivers outstanding total energy throughput over its lifetime, resulting in a low levelized cost of energy (LCOE). Its intelligent energy dispatch and smart O&M capabilities contribute to a stable return on investment and sustained long-term gains. Pylontech’s M7 Series not only enables time-of-use arbitrage and demand charge reduction for the hotel client, but also delivers additional income through ancillary grid services—including frequency regulation, peak shaving, and capacity support. In addition, a microgrid system was deployed on-site to optimize internal energy flows, with the M7 solution also supporting fast EV charging in the hotel’s parking area, creating another source of revenue.
Using Pylontech’s proprietary economic modeling tool, it was determined that deploying two units of the OPTIM US L260-OMNI provides the optimal financial performance for the hotel. Under optimized operational conditions, the storage system enables annual electricity cost savings of up to $85,000, of which:
• $58,000 is saved through energy charge reduction—mainly due to time-of-use arbitrage enabled by intelligent EMS dispatching;
• $20,000 is saved from demand charge reduction, as the system effectively keeps peak load below 500 kW, avoiding excess demand penalties.
• $7,000 is gained from microgrid system profit.
The economics of deployment of the OPTIM US L260-OMNI system are presented below*:
24.3% Internal Rate of Return (IRR)
$199,077
Present Value (NPV) 3.81 Years
Payback Period 4.48 Years
*The data is calculated based on the large hotel's electricity load and the product's operating conditions at the time of installation.
Conclusion and Outlook
According to BloombergNEF, as of 2024, commercial energy storage accounts for only 4% of global storage deployments, but this share is projected to rise to 7% by 2035. As storage costs continue to decline, growing electricity demand from commercial and industrial enterprises—particularly in countries with weaker grids—will further accelerate C&I storage adoption.
As a World's Leading Energy Storage Supplier, Pylontech remains committed to its mission of “Liberating Your Energy Sustainably”, focusing on advancements in cell technology, system efficiency, and intelligent management strategies. Through continuous innovation, Pylontech delivers C&I storage solutions that meet the evolving needs of diverse application scenarios—empowering millions of businesses worldwide to achieve energy security and energy independence.
Pylontech, To Energize Billions With Smarter Power.
Pylon Technologies Co., Ltd
Website en.pylontech.com.cn
Address
No.300, Miaoqiao Road, Kangqiao Town, Pudong New Area, Shanghai 201315, China
Sales: sales@pylontech.com.cn
Service: service@pylontech.com.cn
TEL
+86-21-51317699