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Pandapower GUI PRD

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Pandapower Web GUI — Product Requirements Document

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Guiding Principles

  1. Incremental delivery — each milestone ships a usable feature
  2. Most-used first — power flow before OPF, OPF before short-circuit
  3. PDF reports at every stage — each analysis milestone includes report generation
  4. pandapower as engine — the GUI is a thin wrapper; all computation stays in pandapower
  5. JSON as transport — pp.to_json() / pp.from_json() for all network data
  6. Plotly for visualization — leverage pandapower's built-in Plotly integration

Milestone 0: Project Foundation

M0.1 — Backend Skeleton

  • ☐ FastAPI (or Flask) project with CORS, health endpoint
  • ☐ pandapower installed as dependency
  • ☐ Session management: one pandapowerNet per session (in-memory to start)
  • ☐ POST /api/network — create empty network, return session ID
  • ☐ GET /api/network — return full network as JSON (pp.to_json)
  • ☐ DELETE /api/network — clear session

M0.2 — Frontend Skeleton

  • ☐ React (or Vue/Svelte) SPA with router
  • ☐ Basic layout: sidebar navigation, main content area, status bar
  • ☐ API client module wrapping all backend calls
  • ☐ Toast/notification system for errors and success messages

M0.3 — Network Import/Export

  • ☐ POST /api/network/import — accept JSON file upload → pp.from_json()
  • ☐ GET /api/network/export?format=json — download as JSON
  • ☐ GET /api/network/export?format=xlsx — download as Excel
  • ☐ Frontend: Import dialog with drag-and-drop
  • ☐ Frontend: Export buttons (JSON, Excel)

M0.4 — Built-In Example Networks

  • ☐ GET /api/networks/examples — list available test networks
  • ☐ POST /api/networks/examples/{name} — load a test network (e.g., case_ieee30, mv_oberrhein, simple_four_bus_system)
  • ☐ Frontend: "Load Example" picker in new-network flow

Milestone 1: Network Editor (CRUD)

M1.1 — Bus Management

  • ☐ Table view of all buses (net.bus DataFrame)
  • ☐ Create bus: form with vn_kv, name, type, zone, geodata
  • ☐ Edit bus parameters inline or via modal
  • ☐ Delete bus (with validation — warn if connected elements exist)
  • ☐ Bulk operations: select multiple, delete, change zone

M1.2 — Line Management

  • ☐ Table view of all lines (net.line)
  • ☐ Create line: select from_bus, to_bus, length_km, std_type (dropdown from net.std_types["line"])
  • ☐ Create line from parameters: r_ohm_per_km, x_ohm_per_km, c_nf_per_km, max_i_ka
  • ☐ Edit/delete lines
  • ☐ Show standard type library with search/filter

M1.3 — Transformer Management

  • ☐ Table view of 2-winding transformers (net.trafo)
  • ☐ Create trafo: hv_bus, lv_bus, std_type (dropdown from net.std_types["trafo"])
  • ☐ Create from parameters: sn_mva, vn_hv_kv, vn_lv_kv, vk_percent, vkr_percent, etc.
  • ☐ Tap changer configuration: tap_pos, tap_min, tap_max, tap_step_percent
  • ☐ 3-winding transformers (net.trafo3w) as advanced option

M1.4 — Load & Generation

  • ☐ Create/edit/delete loads: bus, p_mw, q_mvar, type (wye/delta), const_z/i/p_percent
  • ☐ Create/edit/delete generators: bus, p_mw, vm_pu, min_p_mw, max_p_mw
  • ☐ Create/edit/delete static generators (sgen): bus, p_mw, q_mvar, type
  • ☐ Create/edit/delete external grids: bus, vm_pu, va_degree
  • ☐ Table views for each element type

M1.5 — Switches & Shunts

  • ☐ Switch management: create between bus-bus or bus-element, toggle open/closed
  • ☐ Shunt management: bus, p_mw, q_mvar, vn_kv
  • ☐ Storage management: bus, p_mw, max_e_mwh, soc_percent
  • ☐ Impedance management: from_bus, to_bus, rft_pu, xft_pu

M1.6 — Network Diagram (View Only)

  • ☐ GET /api/plot/network — return Plotly figure JSON using pp.plotting.plotly.simple_plotly()
  • ☐ Render Plotly figure in frontend
  • ☐ Auto-generate geodata if missing (pp.plotting.create_generic_coordinates())
  • ☐ Color buses by voltage level
  • ☐ Hover tooltips showing element details
  • ☐ Zoom, pan, select

Milestone 2: Power Flow Analysis (AC/DC)

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M2.1 — Run Power Flow

  • ☐ POST /api/analysis/powerflow with options:
    • algorithm: "nr" (default), "bfsw", "gs", "fdbx", "fdxb"
    • init: "auto", "flat", "dc", "results"
    • max_iteration, tolerance_mva
    • calculate_voltage_angles: true/false/"auto"
    • enforce_q_lims: true/false
    • trafo_model: "t" / "pi"
    • voltage_depend_loads: true/false
    • distributed_slack: true/false
  • ☐ Return convergence status, iteration count, elapsed time
  • ☐ Frontend: "Run Power Flow" button with collapsible options panel

M2.2 — Results Dashboard

  • ☐ Bus results table: vm_pu, va_degree, p_mw, q_mvar — color-code voltage violations
  • ☐ Line results table: loading_percent, i_from_ka, i_to_ka, pl_mw, ql_mvar — highlight overloads
  • ☐ Transformer results table: loading_percent, pl_mw, ql_mvar
  • ☐ Generator results table: p_mw, q_mvar, vm_pu
  • ☐ Summary cards: total generation, total load, total losses, max loading, min/max voltage

M2.3 — Results Visualization

  • ☐ Network diagram colored by bus voltage magnitude (heatmap)
  • ☐ Network diagram colored by line/trafo loading percentage
  • ☐ Use pp.plotting.plotly.pf_res_plotly() or custom Plotly traces
  • ☐ Legend showing color scale
  • ☐ Toggle between voltage view and loading view

M2.4 — DC Power Flow

  • ☐ POST /api/analysis/dcpowerflow — calls pp.rundcpp()
  • ☐ Same results dashboard as AC but with DC-specific fields
  • ☐ Frontend toggle: AC / DC power flow

M2.5 — Power Flow PDF Report

  • ☐ GET /api/report/powerflow — generate PDF
  • ☐ Report contents:
    • Network summary (# buses, lines, trafos, gens, loads)
    • Solver settings used
    • Convergence info
    • Bus voltage table (sorted by violation severity)
    • Line loading table (sorted by loading %)
    • Transformer loading table
    • Total generation vs total load vs losses
    • Network diagram screenshot (server-side Plotly image export)
    • Voltage profile chart (vm_pu vs bus index)
    • Loading bar chart (top 10 most loaded branches)
  • ☐ PDF library: WeasyPrint or ReportLab on backend

Milestone 3: Optimal Power Flow (OPF)

M3.1 — Cost Function Setup

  • ☐ UI to define polynomial costs per generator/load: cp0_eur, cp1_eur_per_mw, cp2_eur_per_mw2
  • ☐ UI to define piecewise-linear costs
  • ☐ Set controllable=True on generators/loads/storage
  • ☐ Set min/max P and Q limits on controllable elements
  • ☐ Set voltage limits on buses: min_vm_pu, max_vm_pu
  • ☐ Set loading limits on lines/trafos: max_loading_percent

M3.2 — Run OPF

  • ☐ POST /api/analysis/opf — calls pp.runopp()
  • ☐ POST /api/analysis/dcopf — calls pp.rundcopp()
  • ☐ Options: init, verbose, delta
  • ☐ Return objective value, convergence, dispatch schedule

M3.3 — OPF Results Dashboard

  • ☐ Optimal dispatch table: generator P/Q setpoints
  • ☐ Cost breakdown per generator
  • ☐ Binding constraints highlighted (voltage limits, loading limits, P/Q limits)
  • ☐ Comparison view: base case vs OPF dispatch

M3.4 — OPF PDF Report

  • ☐ Network & cost setup summary
  • ☐ Optimal dispatch schedule
  • ☐ Total cost
  • ☐ Binding constraints
  • ☐ Voltage/loading compliance tables
  • ☐ Generation dispatch bar chart

Milestone 4: Short-Circuit Analysis

M4.1 — Run Short-Circuit

  • ☐ POST /api/analysis/shortcircuit with options:
    • fault: "3ph", "2ph", "1ph"
    • case: "max", "min"
    • ip: true/false (aperiodic current)
    • ith: true/false (thermal equivalent)
    • tk_s: fault clearing time
    • lv_tol_percent: 6 or 10
    • r_fault_ohm, x_fault_ohm: fault impedance
    • branch_results: true/false
  • ☐ Calls pp.shortcircuit.calc_sc(net, ...)

M4.2 — Short-Circuit Results

  • ☐ Bus SC table: ikss_ka (symmetrical), ip_ka (peak), ith_ka (thermal)
  • ☐ Branch SC table (if branch_results=True): currents through lines/trafos
  • ☐ Highlight buses exceeding equipment ratings
  • ☐ Network diagram colored by SC current magnitude

M4.3 — Short-Circuit PDF Report

  • ☐ Fault type & case settings
  • ☐ Bus short-circuit current table (sorted by magnitude)
  • ☐ Branch currents (if calculated)
  • ☐ Equipment rating comparison (SC current vs breaker rating)
  • ☐ Network diagram with SC current overlay
  • ☐ Bar chart: top 10 highest SC currents

Milestone 5: Network Diagnostics & Topology

M5.1 — Network Diagnostics

  • ☐ POST /api/diagnostic — calls pandapower diagnostic functions
  • ☐ Check for: isolated buses, duplicate lines, disconnected elements, missing impedance, impossible switch configs
  • ☐ Return categorized issues with severity (error, warning, info)
  • ☐ Frontend: diagnostic panel with expandable issue groups
  • ☐ Quick-fix suggestions where possible

M5.2 — Topology Analysis

  • ☐ GET /api/topology — network graph analysis
  • ☐ Connected components (islands)
  • ☐ Unsupplied buses
  • ☐ Stubs, bridges, articulation points
  • ☐ Meshed vs radial classification
  • ☐ Frontend: highlight topology features on network diagram

M5.3 — Diagnostics PDF Report

  • ☐ Issue summary by category
  • ☐ Detailed issue list with element references
  • ☐ Topology summary
  • ☐ Connectivity diagram

Milestone 6: State Estimation

M6.1 — Measurement Management

  • ☐ Create/edit/delete measurements: meas_type (v, p, q, i), element_type, element, value, std_dev
  • ☐ Table view of all measurements
  • ☐ Visual overlay: show measurement locations on network diagram

M6.2 — Run State Estimation

  • ☐ POST /api/analysis/estimation with options:
    • algorithm: "wls", "wls_with_zero_constraint", "irwls", "opt", "lp"
    • init: "flat", "results", "slack"
    • tolerance, maximum_iterations
    • zero_injection: handling of zero-injection buses
  • ☐ Calls pp.estimation.estimate(net, ...)

M6.3 — Estimation Results

  • ☐ Estimated vs measured values comparison table
  • ☐ Residual analysis (measurement residuals)
  • ☐ Bad data detection indicators
  • ☐ Estimated voltage profile overlay on network diagram

M6.4 — State Estimation PDF Report

  • ☐ Measurement summary
  • ☐ Estimated state table
  • ☐ Residual statistics
  • ☐ Bad data flags
  • ☐ Voltage profile comparison (estimated vs measured)

Milestone 7: Time Series Simulation

M7.1 — Time Series Data Setup

  • ☐ Upload CSV/Excel time-varying profiles (load P/Q, generation P/Q per timestep)
  • ☐ Map profiles to network elements (which profile → which load/generator)
  • ☐ Preview profiles as time-series charts
  • ☐ Built-in profile templates (daily load curve, solar generation curve)

M7.2 — Run Time Series

  • ☐ POST /api/analysis/timeseries with options:
    • time_steps: range or list
    • continue_on_divergence: true/false
    • output_variables: which results to record
  • ☐ Progress indicator (WebSocket or SSE for long simulations)
  • ☐ Cancel running simulation

M7.3 — Time Series Results

  • ☐ Time-series charts: voltage at selected buses over time
  • ☐ Time-series charts: loading at selected branches over time
  • ☐ Heatmap: all bus voltages over all timesteps
  • ☐ Statistical summary: min, max, mean, std for each element
  • ☐ Identify timesteps with violations

M7.4 — Time Series PDF Report

  • ☐ Simulation setup summary
  • ☐ Key statistics table
  • ☐ Voltage and loading time-series charts
  • ☐ Violation summary (which timesteps, which elements)
  • ☐ Daily/hourly aggregated tables

Milestone 8: Contingency Analysis

M8.1 — Contingency Definition

  • ☐ Define contingency set: which lines/trafos/generators to trip
  • ☐ N-1 auto-generation: all single-element outages
  • ☐ Custom contingency lists
  • ☐ Import/export contingency definitions

M8.2 — Run Contingency Analysis

  • ☐ POST /api/analysis/contingency — calls pp.contingency.run_contingency()
  • ☐ Parallel execution for large contingency sets
  • ☐ Progress indicator

M8.3 — Contingency Results

  • ☐ Table: each contingency case → worst voltage violation, worst loading
  • ☐ Highlight critical contingencies (non-convergent or with violations)
  • ☐ Drill-down: click a contingency to see full results
  • ☐ Network diagram: overlay worst-case loading

M8.4 — Contingency PDF Report

  • ☐ Contingency set summary
  • ☐ Critical contingencies table
  • ☐ Per-contingency results (top N worst cases)
  • ☐ Comparison charts: base case vs contingency loading
  • ☐ Pass/fail summary

Milestone 9: Advanced Features

M9.1 — Controller Configuration

  • ☐ List active controllers in network
  • ☐ Configure tap changer controllers: target voltage, deadband, side
  • ☐ Configure DER controllers: droop settings, reactive power modes
  • ☐ Run power flow with controllers enabled (run_control=True)
  • ☐ Show controller convergence info

M9.2 — Protection Devices

  • ☐ Fuse configuration and coordination
  • ☐ Overcurrent relay settings
  • ☐ Protection coordination diagrams (time-current curves)
  • ☐ Protection PDF report

M9.3 — Grid Equivalents

  • ☐ Define internal/external zones
  • ☐ Generate REI or Ward equivalents
  • ☐ Compare full network vs equivalent results
  • ☐ Export equivalent network

M9.4 — Three-Phase Analysis

  • ☐ Asymmetric load/generator creation
  • ☐ Run 3-phase unbalanced power flow (runpp_3ph)
  • ☐ Phase-specific results (A, B, C voltages/currents)
  • ☐ Unbalance factor visualization

M9.5 — FACTS Devices

  • ☐ SVC, TCSC, SSC, VSC creation and configuration
  • ☐ Results with FACTS devices in power flow
  • ☐ FACTS device operating point visualization

Milestone 10: Project Management & Collaboration

M10.1 — Project Save/Load

  • ☐ Save network + settings + results to project file
  • ☐ Load project file to restore full state
  • ☐ Auto-save / recovery
  • ☐ Project metadata: name, description, author, date

M10.2 — Scenario Comparison

  • ☐ Save named scenarios (snapshots of network state)
  • ☐ Compare two scenarios side-by-side
  • ☐ Diff view: what changed between scenarios
  • ☐ Comparison PDF report

M10.3 — User Management (if multi-user)

  • ☐ Authentication
  • ☐ Project sharing / permissions
  • ☐ Audit log of changes

Milestone 11: Format Converters

M11.1 — Import Formats

  • ☐ MATPOWER .m files → pp.converter.from_mpc()
  • ☐ PYPOWER case dicts → pp.converter.from_ppc()
  • ☐ CIM/CGMES XML → pp.converter.cim.from_cim()
  • ☐ PowerFactory .dgs → pp.converter.powerfactory.from_pf()
  • ☐ UCTE .uct files → pp.converter.ucte.from_ucte()

M11.2 — Export Formats

  • ☐ MATPOWER format export
  • ☐ PYPOWER format export
  • ☐ CIM export (where supported)

Report Generation Strategy

Every analysis milestone includes PDF report generation. The approach:

Backend PDF Pipeline

Analysis Results (DataFrames)
    │
    ├─→ Jinja2 HTML template (styled tables, charts)
    │       │
    │       ├─→ Plotly server-side image export (kaleido)
    │       │
    │       └─→ WeasyPrint → PDF
    │
    └─→ Alternative: ReportLab for direct PDF generation

Report Template Structure

Every report shares a common structure:

  1. Header: Report title, date, network name, pandapower version
  2. Network Summary: Element counts, voltage levels, total generation/load
  3. Analysis Settings: Parameters used
  4. Results Tables: Sorted by severity/importance, color-coded
  5. Charts/Diagrams: Network plots, bar charts, profiles
  6. Footer: Page numbers, generation timestamp

PDF Generation Priority

Priority Report Milestone
1 Power Flow Report M2.5
2 Short-Circuit Report M4.3
3 OPF Report M3.4
4 Diagnostics Report M5.3
5 Time Series Report M7.4
6 Contingency Report M8.4
7 State Estimation Report M6.4
8 Protection Report M9.2
9 Scenario Comparison Report M10.2

Non-Functional Requirements

Performance

  • Power flow on networks up to 10,000 buses should complete in < 5 seconds
  • PDF report generation should complete in < 30 seconds
  • Time series: show progress for simulations > 100 timesteps
  • Use recycle option for repeated power flows

Usability

  • Responsive layout (desktop primary, tablet secondary)
  • Keyboard shortcuts for common actions (Ctrl+R = run power flow)
  • Undo/redo for element creation/modification
  • Contextual help linking to pandapower documentation

Reliability

  • Graceful handling of non-convergent power flows (show diagnostic info)
  • Input validation before sending to backend
  • Auto-save network state every 5 minutes
  • Session recovery after browser refresh

Security

  • Input sanitization on all API endpoints
  • File upload size limits and type validation
  • No arbitrary code execution from user input
  • Rate limiting on analysis endpoints
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