COSIM Cockpit
When battery storage follows electricity market prices, what does that do to the distribution grid — and can grid tariffs steer it without destroying the business case? This dashboard lets you explore full-year, 15-minute simulations in which market trading, storage control, and grid power flow are solved together.
Why Integrated Simulation Matters
Battery dispatch, electricity markets, and distribution-grid operation are mutually interdependent. No single-domain model captures their interaction.
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Market-optimal dispatch creates grid loading patterns invisible to pure price models
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Grid tariffs (TURPE7) distort market-optimal schedules in ways visible only under joint simulation
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Distribution congestion emerges from the interaction of PV, loads, and EMS decisions — not from any single signal
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Policy assessment requires joint simulation: a tariff reform propagates through market response → battery cycling → transformer loading → voltage, and each step changes the next.
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The coupling runs both ways: transformer loading is fed back to the control strategy as a live congestion signal.
What a Grid Operator Can Study Here
Each scenario is a full year of coupled market, storage, and network operation at 15-minute resolution — so questions that depend on when things coincide can be answered with evidence rather than assumption.
Hosting capacity
How much additional PV or storage can a feeder absorb before voltage or thermal limits bind? Full-year load flow shows which hours actually constrain the feeder, not just a design worst case.
Deferring reinforcement
Can flexible operation postpone a transformer or line upgrade, and for how long? Compare annual peak loading and hours-above-limit with and without storage, across control strategies.
Congestion management & redispatch
What relieves a recurring bottleneck most efficiently — price signals, dynamic connection limits, or explicit curtailment? Congestion-oriented strategies let you compare the alternatives on the same grid and the same year.
Grid tariff design
Does a capacity charge genuinely flatten peaks, or merely shift them to another hour? Tariff variants are simulated end-to-end, with grid tariffs paid and the resulting net position reported separately.
Dynamic operating envelopes
Can time-varying import and export limits replace firm curtailment while keeping the connection economically viable? DOE strategies quantify both the network guarantee and its cost to the operator.
Voltage & reverse power flow
Where does distributed PV lift voltage, and does storage relieve or aggravate it? Per-bus voltage is tracked across the year, with the most-stressed buses ranked.
Assessing connection requests
What happens to this feeder if a large battery connects at a given node under a given tariff? The scenario can be run before the connection agreement is signed.
Valuing flexibility
What is flexible operation worth — to the asset owner and to the network? Market revenue, grid tariffs, and network stress are reported side by side, so the trade-off is explicit rather than implied.
What Is Simulated
Distribution Grid
AC load-flow calculation on German benchmark distribution grids (SimBench), at 15-minute timesteps over a full calendar year.
Load & Generation Profiles
Synthetic load profiles for residential, commercial, and industrial connection points, taken from the German SimBench dataset. PV and wind generation included.
Battery Storage (BESS)
Dispatch is optimised over a rolling 72-hour horizon and re-optimised every 24 hours, against market prices and grid tariffs.
Electricity Markets
Day-ahead and intraday auction price time series, fed directly into the storage control strategy's cost objective.
Grid Tariffs (TURPE7)
French TURPE7 distribution grid tariff: a volumetric energy charge (AP) and a peak capacity charge (LP), with configurable time-of-use windows.
EMS Strategy Library
35 strategy variants across 8 families: self-consumption, price arbitrage, peak shaving, grid-tariff response, frequency reserves (FCR/aFRR), multi-use, degradation-aware, and co-located renewables.
Analytical Workflow
CONFIGURATION
Scenario Config
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Load & Generation Profiles
Market Data (Day-Ahead / Intraday)
Grid Tariffs (TURPE7)
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COUPLED SIMULATION
Storage Control Strategy
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Distribution Grid Model
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OUTPUT
Result Collection
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CSV Result Files
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ANALYSIS
Grid Analysis
Assets
Market–Grid
Comparison
Research & Application Focus
TURPE7 Tariff Impact
How an energy + capacity charge tariff structure alters battery dispatch relative to pure wholesale arbitrage.
Congestion Management via Price Signals
Whether banded energy-charge multipliers (1× → 10×) reduce transformer peak loading without explicit curtailment.
Market vs. Grid Signal Trade-offs
Conditions under which day-ahead/intraday wholesale prices dominate over regulatory grid tariff signals — and vice versa.
Degradation-Aware Dispatch
Whether including battery ageing cost in the optimisation objective extends storage lifetime without sacrificing revenue.
Multi-Market Co-Optimisation
How to split storage capacity between frequency reserve, arbitrage, self-consumption, and peak shaving simultaneously.
Example Research Questions
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Can a static capacity charge alone reduce transformer loading peaks in a rural medium-voltage grid?
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Does a dynamic capacity charge with seasonal time-of-use windows outperform a static one?
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How does a 3× energy-charge weighting affect annual cycling and grid peak loading?
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Do congestion-banded energy-charge multipliers (70 / 80 / 90 % thresholds) defer transformer overloading in summer-peak scenarios?
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Which congestion path achieves better peak management: penalise both directions (Path A) or credit charging (Path B)?
Technical Specifications
Simulation resolution
15 minutes (900 s per step)
Simulation horizon
Full calendar year · 35,040 timesteps
EMS strategy variants
35 available across 8 families
Optimisation solver
Gurobi (default) · CBC/PuLP · HiGHS
Parallel execution
Multi-process batch execution (20 scenarios validated)
Reference grid
German benchmark MV rural feeder (SimBench) · 20 kV · ~110 buses
Reference BESS
10 MW / 20 MWh per scenario
Rolling EMS horizon
72 h · re-optimised every 24 h with perfect foresight
What You Can Adapt
The platform is configuration-driven: the studies below can be varied without rebuilding the simulation.
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New control strategy — add a strategy definition; the simulation core stays untouched.
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New technology model — battery, PV, or wind models can be combined with any control strategy.
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New grid — bring your own distribution network model, or reference a published benchmark grid.
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New tariff scheme — define time windows and tariff classes in configuration; no change to the control strategies.
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New data source — additional market or measurement feeds are connected through configuration.
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New analysis view — further result perspectives can be added to this dashboard.
Platform Architecture
CONFIGURATION
Scenario Config
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Simulation Engine
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COUPLED SIMULATION
Load & Generation
Storage Control
Grid Model
Grid Tariffs
Result Collection
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OUTPUT
CSV Result Files
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ANALYSIS
COSIM Cockpit
Grid Analysis
Storage & Flexibility
Market–Grid
Comparison
Glossary & Abbreviations
Terms used across this dashboard. Where a technical term cannot be simplified without losing precision, it is kept and explained here.
Abbreviations
BESS — Battery Energy Storage System
A grid-connected battery that can absorb electricity (charge) and feed it back (discharge). The flexibility asset studied throughout this dashboard.
EMS — Energy Management System
The controller that decides when the battery charges and discharges, optimising against market prices and grid tariffs. Each scenario runs one EMS strategy.
FCU — Flexibility Control Unit
The simulation component that models a storage unit together with its EMS. You will see this name in raw result files (result_FlexibilityControlUnit-*.csv); in the interface it appears as Storage & Flexibility.
DOE — Dynamic Operating Envelope
Time-varying import and export limits set by the grid operator for a connection point. The storage may optimise freely inside the envelope, giving the operator a network guarantee without fixed curtailment.
DAA / IDA
Day-Ahead Auction and Intraday Auction — the two wholesale market products traded here. Shown as 'Day-Ahead' and 'Intraday' in charts and tables.
State of charge (SoC)
How full the battery is, from 0 (empty) to 1 (full). Comparable to a fuel gauge.
Per unit (p.u.)
Voltage expressed relative to its nominal value: 1.00 p.u. is nominal, 0.95 is 5% below. Lets voltages be compared across voltage levels.
MV / LV
Medium voltage (typically 1–50 kV, the distribution backbone) and low voltage (below 1 kV, the level serving households).
N-1 security
The principle that a grid should keep operating within limits after the loss of any single component, such as one line or transformer.
PV
Photovoltaic generation. Distributed solar feed-in is one of the drivers of voltage rise and reverse power flow in the modelled grids.
TURPE7
The French regulated distribution grid tariff. Version 7 combines an energy charge with a peak capacity charge and time-of-use windows.
SimBench grid
A publicly available set of realistic benchmark distribution grids, used so results can be reproduced and compared by others.
Co-simulation
Running separate models — market, storage control, and grid power flow — as one coupled system, so each one's output becomes the next one's input at every timestep.
Concepts & Metrics
Battery storage system
A grid-connected battery that can absorb electricity (charge) and feed it back (discharge). Referred to as 'storage' throughout this dashboard.
Dispatch
The schedule of charging and discharging over time — how much power the storage takes from or feeds into the grid at each moment.
Control strategy
The optimisation logic that decides when to charge and discharge, based on market prices and grid tariffs. Each scenario uses one strategy.
Day-ahead market
Wholesale electricity auction where power is traded one day before delivery. Sets an hourly price used as an input to the control strategy.
Intraday market
Wholesale market trading closer to delivery time, allowing positions to be corrected after the day-ahead auction closes.
Price arbitrage
Charging when electricity is cheap and discharging when it is expensive, to earn the price difference.
Equivalent full cycle
One complete charge and discharge of the battery's full capacity. Used to express battery utilisation and wear independently of partial cycles.
Energy charge (volumetric)
Grid tariff component billed per unit of energy drawn (per kWh or MWh), regardless of when it is used. Known as 'AP' (Arbeitspreis) in the TURPE tariff.
Capacity charge (peak demand)
Grid tariff component billed on the highest power drawn during a period, rewarding a flatter load profile. Known as 'LP' (Leistungspreis) in the TURPE tariff.
Loading (%)
How much of a line's or transformer's rated capacity is in use. Above 100% the equipment is overloaded and may age faster or trip.
Simultaneity
The share of storage units charging or discharging in the same direction at the same time. High simultaneity concentrates stress on the grid.
Power flow calculation
The physics simulation that computes voltages and line loadings across the network for a given set of loads and generation.
Getting Started
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Sign in with your credentials
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Select a simulation scenario from the Scenario Browser
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Open Grid Analysis to review voltage profiles and transformer loading
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Open Storage & Flexibility to inspect battery dispatch and control decisions
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Open Market–Grid Coupling to see cost breakdown and tariff impact
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Use Comparison to contrast two or more scenarios side by side
Research & Development
The COSIM Cockpit platform is developed within the collaborative research and development activities of the Institute for High Voltage Equipment and Grids, Digitalization and Energy Economics (IAEW) — Active Energy Distribution Grids group — at RWTH Aachen University and the Fraunhofer FIT research team Digitale Energie. The work combines academic expertise in active distribution networks, grid operation and planning, and flexibility integration with applied digital-energy system development and engineering-oriented analytical tooling.
Contact
Primary contact for this platform:
Steffen Kortmann
steffen.kortmann@fit.fraunhofer.de+49 241 80-92946Legal Notice
The COSIM Cockpit is a research and engineering platform developed at IAEW RWTH Aachen University and Fraunhofer FIT. Results are based on simulation models, modelling assumptions, and scenario-specific input data. Real-world system behaviour may differ from simulated outcomes. Analyses do not constitute operational guarantees or binding engineering assessments.
No warranty is provided regarding completeness, correctness, or fitness for a specific operational purpose. Users are responsible for independently validating conclusions before applying them to real-world decisions.
Research use only: This platform is designed exclusively for research and academic analysis. Results must not be used as the sole basis for investment, operational, or regulatory decisions without independent engineering validation.
Market data: Electricity price time series used in simulations (day-ahead/intraday from ENTSO-E Transparency Platform and EPEX Spot) are subject to the respective platform terms of use.
Confidentiality: Simulation scenarios, configuration files, and result data may contain confidential project-specific information. Exported results and reports must not be shared beyond the intended audience without prior authorisation.
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Technology & Open-Source Components
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Built on open-source software: Reflex (Apache 2.0), Plotly (MIT), pandapower (BSD 3-Clause), SimBench (Open Database License), pandas & NumPy (BSD 3-Clause).