What is Energy Optima?

Energy Optima is a professional simulation and optimization platform for battery energy storage systems (BESS), solar PV, wind, and hybrid energy systems. It provides hourly-resolution dispatch modeling, multi-year degradation projections, and financial analysis for EPCs, consultants, and project developers.

What standards does Energy Optima follow?

Energy Optima uses NREL PVWatts for solar modeling, IEC 62933 for battery degradation, IEC 61850 for dispatch logic, and follows IEEE 1547 for grid interconnection. Battery models use validated degradation tables with 3D interpolation across year, C-rate, and cycling frequency.

Can Energy Optima simulate battery degradation over time?

Yes. Energy Optima simulates battery SOH (State of Health) and RTE (Round-Trip Efficiency) degradation using 3D interpolation from manufacturer-specific degradation tables. It tracks degradation across the full project lifetime (up to 25 years) with year-by-year capacity retention analysis.

What components are available in the database?

Energy Optima includes 147+ battery models, 127+ PV modules, 215+ inverters, 105+ wind turbines, and 157+ diesel generators from manufacturers like CATL, BYD, JinkoSolar, LONGi, Huawei, and Sungrow. All with verified datasheet specifications.

Is there a free plan available?

Yes. The Free plan includes 1 project (up to 1 MWh / 1 MW PV AC), battery + PV + grid topology, 1-year hourly simulation, payback analysis, LCOE calculation, rule-based auto-design, and PDF export. No credit card required.

How does Energy Optima compare to PVsyst or HOMER?

Energy Optima specializes in battery energy storage simulation with a focus on detailed loss modeling (DC RTE, transformer, auxiliary), multi-year degradation projections, and automated LP optimization. Unlike PVsyst (primarily solar) or HOMER (simplified models), Energy Optima provides component-level loss waterfalls and real-product database integration.

What is battery energy storage system (BESS) simulation software?

BESS simulation software models the performance, degradation, and economics of battery energy storage systems over their project lifetime. Energy Optima simulates SOC/SOH tracking, round-trip efficiency losses, thermal behavior, and dispatch optimization using real manufacturer cell data with 3D interpolation across year, C-rate, and cycling frequency.

How do you calculate LCOE for battery energy storage?

Energy Optima calculates LCOE (Levelized Cost of Energy) for battery storage using the capital recovery factor (CRF) method, dividing total lifecycle costs (CAPEX plus discounted OPEX) by total energy discharged over the project lifetime. The calculation accounts for battery degradation, round-trip efficiency losses, augmentation costs, and project-specific discount rates.

What is the best software for solar PV and battery hybrid system design?

Energy Optima is a leading software for solar PV and battery hybrid system design, combining NREL PVWatts-based solar modeling with manufacturer-specific battery degradation data. It supports LP-optimized capacity sizing for minimum LCOE, 3 dispatch strategies (rule-based, economic LP, MILP), and 25-year financial projections across 39 currencies.

How accurate is Energy Optima's battery degradation modeling?

Energy Optima's battery degradation modeling uses real manufacturer degradation tables with 3D interpolation across three dimensions: calendar year, C-rate (charge/discharge rate), and cycling frequency (cycles per day). This captures SOH fade, RTE degradation, and capacity loss with higher accuracy than linear degradation assumptions used in most competing tools.

Can Energy Optima model grid-connected battery storage with solar?

Yes. Energy Optima models grid-connected battery storage integrated with solar PV, wind turbines, and diesel generators. It supports time-of-use tariffs, demand charge optimization, export/import policies, grid outage simulation with automatic islanded detection, and SAIDI/SAIFI reliability modeling — all in a single 8760-hour annual simulation.

What is the difference between LP and MILP optimization for energy systems?

LP (Linear Programming) optimization finds the minimum-cost PV + battery + wind sizing for continuous variables like capacity and hourly dispatch. MILP (Mixed-Integer Linear Programming) adds binary decision variables, enabling diesel generator commitment scheduling with SOS2 fuel curves, minimum runtime constraints, and on/off logic. Energy Optima supports both methods.

Battery Storage & Renewable Energy Optimization Platform

Energy modeling software for BESS degradation, solar PV, and hybrid system design. Model 50-year project economics in minutes. Bankable analysis that investors trust.

Physics-Validated Models

Science-backed Modeling Engine

8 Integrated Energy Components

Battery, PCS, Solar, Wind, Diesel, Grid, Load & Transformers

50-Year Simulation Horizon

Long-term degradation & financial analysis

Start 14-Day Free Trial →

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Energy Optima dashboard showing battery SOC tracking, financial KPIs, and energy balance

Why Energy Optima

Complete system integration

Solar PV, wind, diesel, grid services, and TOU optimization. Model the complete energy ecosystem in a single platform—from generation to storage to grid interaction.

8 energy components

Built-in templates + CSV upload

Battery storage expertise

Manufacturer-specific degradation tables, chemistry-dependent cycle limits, and multi-year SOH tracking.

147 battery models

Built for your workflow

From feasibility studies to 30-year financial projections — solo engineers to multi-user teams.

5 flexible tiers

Transparent & honest

No vaporware. Battery simulation, solar modeling, NPV/IRR/LCOE, AI-assisted analysis, and multi-year projections—all live now.

50 year simulations

Export-ready reports

Word, Excel, PDF, PowerPoint, and CSV exports. Generate audience-specific reports for engineers, investors, or owners — with your branding.

5 export formats

Simple pricing that scales with you

Free plan for exploration. Paid plans from $99/month with 14-day free trial. Founding Engineer program: 30% off forever.

View All Plans →

BATTERY & ENERGY STORAGE

Manufacturer-specific degradation modeling

Model battery state-of-health (SOH) and round-trip efficiency losses over 25+ years using real manufacturer degradation tables. Chemistry-specific cycle tracking, auxiliary power consumption, and economic analysis from day one to end-of-life.

147 real battery models (CATL, BYD, Samsung SDI, EVE Energy, LG, and more)
SOC/SOH tracking with 3D degradation interpolation
Battery augmentation planning with degradation projections
FAT-to-COD pre-commissioning SOH loss modeling
Auxiliary power modeling (C-rate × temperature)

Explore battery storage simulation

24-Hour Energy Flow

Battery dispatch, PV generation, grid interaction — explore the full interactive simulation

View interactive chart →

Solar PV Loss Analysis

10 loss types from soiling to temperature — see how each impacts your net energy yield

View loss analysis →

SOLAR PV INTEGRATION

Physics-based generation modeling

Calculate solar generation with temperature-corrected PV models, real weather data from PVGIS, and comprehensive loss accounting. 127 module models, 215 inverter options, hourly simulation for accurate yield predictions.

PVWatts modeling with NOCT temperature correction
10 loss types (soiling, shading, cables, inverter, etc.)
Multi-array PV Designer with per-array MPPT distribution
PVGIS weather integration (1994-2022 historical data)
Capacity factor, specific yield, performance ratio outputs

Explore solar PV design tools

FINANCIAL ANALYSIS

Bankable economics for project financing

NPV, IRR, LCOE, and payback calculations using NREL methodologies. Multi-year cash flow projections, component-level cost tracking, and sensitivity to key parameters. Financial analysis suitable for investor presentations and lender reviews.

NPV with configurable discount rates
IRR via Newton-Raphson convergence
LCOE with capital recovery factor (CRF)
Multi-currency support (39 currencies)
Up to 50 years cash flow analysis

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Financial dashboard with NPV, IRR, LCOE metrics

Energy balance and grid integration diagram

GRID & HYBRID SYSTEMS

Complete system integration

Model grid interactions with time-of-use tariffs, demand charges, and export policies. Integrate multiple renewable sources (solar PV, wind, diesel) with battery storage for hybrid energy systems. Grid reliability modeling with SAIDI/SAIFI outage simulation and automatic islanded detection.

TOU tariffs with demand charge optimization
Wind turbine modeling with configurable wake loss
Built-in load templates or custom CSV upload
Grid outage simulation and islanded detection
Interactive loss waterfall charts and energy flow diagrams
3 dispatch strategies: Rule-Based, Economic LP, MILP Hybrid

Explore grid connection modeling

AUTOMATIC SYSTEM DESIGN

AI-powered capacity optimization

Define your energy requirements and the optimizer designs the optimal system. Quick Design mode asks minimal questions and produces results in seconds. Full auto-design uses Linear Programming (LP) to minimize LCOE while meeting renewable targets, or MILP for diesel-battery hybrid optimization with binary scheduling constraints.

Quick Design: minimal inputs, results in seconds
LP optimizer: minimum-cost PV + Battery + Wind sizing
MILP diesel: SOS2 fuel curves, binary scheduling
5 backup strategies for constrained projects
Outputs: LCOE, IRR, Payback, Renewable Fraction

Explore auto-design optimization

Auto-Design Output Example

LCOE

$0.063/kWh

IRR

18.6%

Payback

6.3 yrs

RE Fraction

78.7%

PV: 5.08 MW Battery: 6.9 MWh Diesel: 2.0 MW

Model Predictive Control Loop

Forecast

Load demand + solar/wind generation prediction

Optimize

LP dispatch over adaptive 12-96h horizon

Execute

Apply first timestep, measure actual state

Feedback

SOC/SOH state correction → re-optimize

Receding horizon with degradation-aware constraints

MODEL PREDICTIVE CONTROL

Real-time dispatch optimization

Go beyond static simulation with Model Predictive Control. The MPC controller continuously re-optimizes dispatch decisions using actual system state — battery SOC, degradation, and real generation data. Adaptive horizons expand or contract based on forecast confidence.

Adaptive horizon: 12-96 hours based on conditions
State feedback with SOC/SOH correction
Degradation-aware constraint tightening
12 tracking metrics per timestep

Explore MPC dispatch control

AI PROJECT ASSISTANT

Ask questions in plain English

Run simulations, query results, compare scenarios, and get engineering insights through a conversational AI assistant. 25 specialized tools that understand your project context — from component sizing to financial analysis to sensitivity studies.

25 engineering tools (simulate, compare, export, configure)
Voice input for hands-free interaction (Whisper transcription)
Conversation persistence with full history
Quick mode for rapid feasibility assessments

Explore AI project assistant

AI Project Assistant

Run a 25-year simulation for the industrial energy project with the CATL battery.

Starting 25-year simulation for Industrial Energy Project. CATL 280Ah LFP, 5.2 MW PV, 6.8 MWh battery. Estimated time: 4-6 minutes.

Tool: runSimulation | Duration: 4m 32s

Simulation complete. LCOE: $0.063/kWh, IRR: 18.6%, Payback: 6.3 years. Renewable fraction: 78.7%. Full results available in the results dashboard.

Tool: pollSimulationStatus | Status: complete

25 tools Project context aware Voice input

Report Builder

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Word

📊

Excel

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PDF

PowerPoint

CSV Data

Engineer Investor Owner

3 audience profiles with tailored narrative complexity

REPORTS & COLLABORATION

Deliverables that close deals

Generate audience-specific reports for engineers, investors, or owners. Export in 5 formats with your branding. Collaborate with your team through shared project libraries, role-based permissions, and activity tracking.