Early-stage capacity planning and financial modeling directly shape the investment returns and operational reliability of energy storage projects. Yet many teams still rely on manual trials, spreadsheet-based parameter tuning, and typical-day simulations. These conventional sizing methods are often inefficient, insufficiently accurate, financially incomplete, and costly to deliver, making it difficult to support scalable, refined energy storage development.
To address these challenges, DoGo Power has launched EcoSizing, an in-house intelligent planning platform. Backed by DoGo Power's grid-forming energy storage solutions, EcoSizing is built around three differentiated capabilities: a renewable-energy-centered calculation engine, a finance-grade compliance model, and full-lifecycle simulation. It delivers high-fidelity, traceable, and executable decision support for renewable energy projects, helping the industry move from experience-based trial-and-error sizing to data-driven global optimization.
Common Limitations of Traditional Energy Storage Sizing
Traditional early-stage planning workflows can no longer keep pace with the industry's shift toward more refined project development. Their main limitations fall into four areas:
1.Efficiency bottlenecks
Most projects still depend on manual Excel-based parameter tuning. A single project plan may take several days to produce, and comparing multiple scenarios or business models requires repeated calculations, heavy labor input, and slow response cycles.
2.Simulation accuracy gaps
Many tools rely only on one-year hourly data or typical-day datasets. They cannot fully capture year-round operating fluctuations across all conditions, and they often omit lifecycle variables such as PV degradation, storage degradation, and equipment replacement, widening the gap between planned results and actual operation.
3.Weak financial support
Traditional calculations usually cover only initial investment and basic revenue. They often lack a full-lifecycle cash flow model and typically support only self-investment scenarios, making it difficult to support PPA pricing or provide a solid financial basis for decisions and quotations.
4.High delivery and learning costs
Project plans require manual data consolidation and report formatting, which is repetitive and error-prone. Energy storage sizing also requires multidisciplinary expertise, so new team members face a long ramp-up period and professional knowledge is difficult to reuse efficiently.
Four Core Differentiated Advantages
Drawing on DoGo Power's deep experience in grid-forming (GFM) energy storage and its fully self-developed algorithm system, EcoSizing overcomes the adaptability limits of generic planning tools. Its core capabilities outperform typical industry tools and can help reduce project CAPEX by more than 20%.
Self-developed adaptive algorithms for GFM energy storage
Unlike general-purpose optimization algorithms, EcoSizing is deeply developed around DoGo Power's energy storage product characteristics. It adapts to high PV-to-storage-ratio scenarios and wide-SOC GFM operating strategies, closely aligning the algorithm with real equipment operating strategies. The resulting storage capacity optimization plan can be implemented directly, solving the disconnect between generic algorithms and real-world equipment operation.
Full-lifecycle simulation at 15-minute resolution
Unlike the industry's common one-year, 8,760-hour calculation approach, EcoSizing uses N x 8,760h x 4-step precise sampling for PV, storage, diesel generators, and load. This preserves peak-load data without distortion and incorporates dynamic variables such as annual PV degradation, storage SOH decline, mid-term equipment replacement, capacity replenishment, grid electricity prices, and PPA discounts. It covers extreme year-round operating conditions and reflects full project lifecycle trends through exportable, transferable, and traceable plans.
Finance-grade compliant financial model
The platform builds a full-lifecycle financial model covering tax depreciation, equipment residual value, O&M costs, financing loans, and other key factors. It automatically outputs core economic indicators such as CAPEX, IRR, NPV, payback period, and LCOE. It also supports one-click switching between all-equity and debt-financed investment perspectives, with cash flow outputs aligned with financial reporting and investment due diligence standards.
Dual business model coverage
Unlike most industry tools, which optimize only NPV under self-investment models, EcoSizing covers both self-investment and PPA models. It can automatically optimize for maximum NPV, minimize NPC under a specified ROI, or reverse-calculate PPA contract electricity prices based on a target payback period. It supports fixed-price, tiered-price, time-of-use, and other commercial contract structures.
Full-Process Functional Coverage
EcoSizing covers the full project workflow from modeling to delivery through five key modules:
- Flexible data input: Supports PV and load data simulation generation, allowing calculations to start even when measured data is unavailable. It also supports hierarchical load modeling and JSON configuration import and export, enabling fast reuse of historical project experience.
- Multi-mode capacity optimization: Supports optimization across PV, storage, diesel, and grid-connected combinations, covering both planning and operation modes. It supports capacity planning for new projects as well as revenue evaluation for existing assets.
- Full-lifecycle operation simulation: Simulates project operation year by year to forecast long-term revenue trends. Both 15-minute-resolution operating plans and annual operating statistics can be exported and traced.
- Standardized solution delivery: Centralizes key indicators and supports multi-scenario comparison. Intelligent PPA pricing supports commercial quotations, while one-click standardized design reports automatically consolidate configuration, simulation, financial data, and charts.
- Built-in intelligent expert: Provides round-the-clock professional support for parameter explanations, configuration assistance, and result interpretation across energy storage, microgrids, and financial modeling, lowering the learning threshold for users.
EcoSizing can be widely applied to off-grid and weak-grid microgrid design, commercial and industrial energy storage project planning, project bidding proposals, revenue reviews for operating projects, and economic comparisons across multiple investment plans. It supports decision-making across different project stages.
As DoGo Power's in-house intelligent renewable energy sizing tool, EcoSizing integrates technical simulation, financial modeling, and solution delivery into a single workflow. It directly addresses the core pain points of traditional sizing methods and helps improve decision-making efficiency and investment reliability for energy storage projects.
