Virtual Power Plant Battery Arbitrage Agent Pipeline Script

Role: Senior Energy Trading & Virtual Power Plant (VPP) Automation Engineer specializing in algorithmic battery energy storage system (BESS) dispatch.

Context

• Fleet Identifier: {{asset_fleet_id}}
• ISO Market Data Endpoint: {{iso_market_feed}}
• Minimum State-of-Charge Floor: {{min_soc_threshold}}
• Marginal Degradation Cost per MWh: {{degradation_cost_per_mwh}}
• Settlement Integration URL: {{settlement_api_key}}
• Telemetry Polling Interval: {{telemetry_poll_interval_sec}}

Task

Author a production-grade Python orchestration script for an autonomous market agent that polls Locational Marginal Pricing (LMP), assesses distributed battery storage telemetry across {{asset_fleet_id}}, runs profitability calculations against cycle degradation, and issues automated charge/discharge schedules.

Method

1. Ingest five-minute LMP and ancillary service pricing arrays from {{iso_market_feed}}.
2. Poll live telemetry across {{asset_fleet_id}} at intervals governed by {{telemetry_poll_interval_sec}}.
3. Compute net arbitrage spreads by factoring in round-trip efficiency and {{degradation_cost_per_mwh}}.
4. Calculate available inverter capacity while respecting {{min_soc_threshold}} safety boundaries.
5. Generate optimal 15-minute dispatch setpoints using linear optimization logic.
6. Execute validation routines to prevent thermal runaway risk or breach of local interconnection limits.
7. Submit signed dispatch payloads to {{settlement_api_key}} using secure HMAC headers.
8. Output structured performance metrics including estimated revenue and avoided carbon intensity.

Constraints

• MUST abort automated discharge if asset state-of-charge approaches {{min_soc_threshold}}.
• MUST NOT submit market bids when the price delta is lower than {{degradation_cost_per_mwh}}.
• Include exponential backoff retry logic for all {{iso_market_feed}} polling operations.
• The script must run without external runtime database dependencies using in-memory state tracking.

Output format

Provide a clean Python automation script containing:

1. Configuration constants and typed payload schemas.
2. Arbitrage mathematical optimization engine class.
3. Fleet telemetry aggregation and dispatch execution handler.
4. Main evaluation loop demonstrating a full 24-hour pricing cycle.

Self-review

• Verify that battery degradation costs are subtracted prior to generating discharge triggers.
• Confirm {{telemetry_poll_interval_sec}} properly sets asynchronous polling delays.
• Ensure strict assertions prevent violation of {{min_soc_threshold}}.