Publication record · 18.cifr/2010.mohsenianrad.game-dsm

Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

v1.0.0

Amir-Hamed Mohsenian-Rad (University of British Columbia), Vincent W. S. Wong (University of British Columbia), Juri Jatskevich (University of British Columbia), Robert Schober (University of British Columbia), Alberto Leon-Garcia (University of Toronto)

RAI18.cifr/2010.mohsenianrad.game-dsm

IEEE Transactions on Smart Grid· 2010· doi:10.1109/TSG.2010.2089069

This paper proposes an autonomous and distributed demand-side management (DSM) strategy for the future smart grid. We model the interaction among the users as a non-cooperative game. Each user schedules their energy consumption to minimize their daily electricity payment. We prove the existence and uniqueness of a Nash Equilibrium and design a distributed algorithm to reach it. Simulation results show significant reduction in peak-to-average ratio and electricity payment.

demand-side managementgame theoryNash equilibriumsmart gridenergy scheduling

✦ Research context

What this agent contributes to the literature.

Problem solved

Utility companies suffer costly peak demand events; prior DSM needed central coordinators or user data sharing. This work gives each household an autonomous scheduler that shifts flexible loads to off-peak hours while accounting for all other users' simultaneous decisions.

Novelty

Formulates residential DSM as a non-cooperative game and proves existence and uniqueness of a Nash Equilibrium. A distributed best-response algorithm converges to the NE without centralized control or user privacy sacrifice. The NE is also shown to approximate the social optimum under price-anticipating behavior.

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Canvas contract1-in / 1-out · unpacked into dsm_input, algo_params legacy ports

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sha256:3e39b02e15b3c1222e03dd01d7fad4e7dc9ff5b6bc270b7619830dd33ba81390

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input:application/json

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inputapplication/jsonoptional

Unified canvas input — nested keys described in legacy_inputs

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{
  "dsm_input": {
    "pricing_coeff": 0.01,
    "households": [
      {
        "id": 0,
        "appliances": [
          {
            "name": "washer",
            "daily_demand_kwh": 1.94,
            "start_hour": 0,
            "end_hour": 23,
            "length_hours": 1
          },
          {
            "name": "dryer",
            "daily_demand_kwh": 2.5,
            "start_hour": 6,
            "end_hour": 22,
            "length_hours": 1
          }
        ]
      },
      {
        "id": 1,
        "appliances": [
          {
            "name": "dishwasher",
            "daily_demand_kwh": 1.44,
            "start_hour": 0,
            "end_hour": 23,
            "length_hours": 1
          },
          {
            "name": "ev_charger",
            "daily_demand_kwh": 3.3,
            "start_hour": 18,
            "end_hour": 23,
            "length_hours": 2
          }
        ]
      }
    ]
  },
  "algo_params": {
    "max_iterations": 100,
    "tolerance": 0.0001
  }
}

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