Research map / Multi-agent systems and games / Games and equilibria
Autonomous Electricity Trading Using Time-of-Use Tariffs in a Competitive Market
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace fixed-rate tariff with gradient-optimized TOU tariff (ablation) | broker agent · Power TAC vs AgentUDE and CWIBroker | peak demand (MW): 86.771 -> 73.519 (UDE); 86.701 -> 73.651 (CWI) | Helped |
| replace fixed-rate tariff with gradient-optimized TOU tariff (ablation) | broker agent · Power TAC vs AgentUDE | broker score (M$): 1.893 -> 1.922 | Helped |
| replace fixed-rate tariff with gradient-optimized TOU tariff (ablation) | broker agent · Power TAC vs CWIBroker | broker score (M$): 0.677 -> 0.622 | Hurt |
| replace fixed-rate tariff with gradient-optimized TOU tariff (ablation) | broker agent · Power TAC vs CWIBroker | market share (%): 44.2 -> 54.7 | Helped |
| use gradient-based TOU optimization instead of naive cost-plus-margin TOU (ablation) | TOU broker · Power TAC vs AgentUDE | broker score (M$): 1.689 -> 1.922 | Helped |
| use gradient-based TOU optimization instead of naive cost-plus-margin TOU (ablation) | TOU broker · Power TAC vs CWIBroker | broker score (M$): 0.524 -> 0.622 | Helped |
| add consumption-shifting prediction module (ablation) | TOU broker · Power TAC vs CWIBroker | broker score (M$): 0.507 -> 0.622 | Helped |
| add consumption-shifting prediction module (ablation) | TOU broker · Power TAC vs CWIBroker | peak demand (MW): 83.728 -> 73.651 | Helped |
| use accurate cost-curve prediction instead of noisy flatter-slope prediction (ablation) | TOU broker · Power TAC vs CWIBroker | broker score (M$): -0.007 -> 0.622 | Helped |
| use accurate cost-curve prediction instead of noisy flatter-slope prediction (ablation) | TOU broker · Power TAC vs CWIBroker | peak demand (MW): 82.779 -> 73.651 | Helped |
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