Publication record · 18.cifr/2020.ding.pv-optimal-dispatch-dms

Optimal Energy Dispatch of Distributed PVs for the Next Generation of Distribution Management Systems

v1.0.0

Fei Ding (National Renewable Energy Laboratory), Yingchen Zhang (National Renewable Energy Laboratory), Jeffery Simpson (National Renewable Energy Laboratory), Andrey Bernstein (National Renewable Energy Laboratory), Subramanian Vadari (Modern Grid Solutions)

RAI18.cifr/2020.ding.pv-optimal-dispatch-dms

IEEE Open Access Journal of Power and Energy· 2020· doi:10.1109/OAJPE.2020.3009684

This paper proposes an optimal energy dispatch framework for distributed photovoltaic (PV) systems integrated into distribution management systems (DMS). The approach formulates a convex second-order cone programming (SOCP) relaxation of the optimal power flow (OPF) problem to determine real and reactive power setpoints for PV inverters. The objective minimizes active power curtailment while satisfying voltage magnitude, branch thermal, and inverter apparent power capacity constraints on radial distribution feeders. The proposed methodology supports Volt/VAR optimization and smart inverter functionalities in next-generation DMS platforms.

distributed PVoptimal power flowSOCPdistribution management systemsmart inverterVolt/VAR optimization

✦ Research context

What this agent contributes to the literature.

Problem solved

Distribution utilities lack scalable, real-time OPF-based dispatch for high-penetration distributed PV on radial feeders.
Non-convex AC OPF is computationally intractable for DMS deployment; SOCP relaxation makes it tractable.
Smart inverter reactive power capabilities are underutilized without coordinated, constraint-aware setpoint optimization.

Novelty

Applies SOCP relaxation of OPF specifically for real-time PV inverter dispatch within DMS platforms.

Related research

Computing related research...

Canvas contract1-in / 1-out · unpacked into network, pvs legacy ports

Sample data

Loading sample data...

Total calls

This month

Citations

Last called

—

Image digest

sha256:2dbb534c018052f874cbe2f70d4df94afa35e3b1deee9d5a14bf57becaffc331

Invoke command

python main.py

Inputs

input:application/json

Outputs

output:application/json

Citation

Loading DOI…

Invoke

CPU compute only

How to get GPU access: Your university, lab, or company can become a CIFR institutional member. Members get GPU-accelerated runs for all their researchers. Contact us

Pre-filled with the paper's canonical scenario. Click Invoke agent to reproduce the original result, or edit the JSON below to run a counterfactual.

inputapplication/jsonoptional

Unified canvas input. The executor unpacks this JSON blob into legacy per-port files: network, pvs

Leave empty to run the paper's canonical scenario.

{
  "network": {
    "base_kva": 1000,
    "base_kv": 4.16,
    "slack_bus": "B1",
    "v_slack": 1,
    "buses": [
      {
        "id": "B1",
        "p_load_kw": 0,
        "q_load_kvar": 0,
        "v_min_pu": 0.95,
        "v_max_pu": 1.05
      },
      {
        "id": "B2",
        "p_load_kw": 50,
        "q_load_kvar": 20,
        "v_min_pu": 0.95,
        "v_max_pu": 1.05
      },
      {
        "id": "B3",
        "p_load_kw": 80,
        "q_load_kvar": 30,
        "v_min_pu": 0.95,
        "v_max_pu": 1.05
      },
      {
        "id": "B4",
        "p_load_kw": 60,
        "q_load_kvar": 25,
        "v_min_pu": 0.95,
        "v_max_pu": 1.05
      },
      {
        "id": "B5",
        "p_load_kw": 40,
        "q_load_kvar": 15,
        "v_min_pu": 0.95,
        "v_max_pu": 1.05
      },
      {
        "id": "B6",
        "p_load_kw": 30,
        "q_load_kvar": 10,
        "v_min_pu": 0.95,
        "v_max_pu": 1.05
      }
    ],
    "branches": [
      {
        "id": "BR1",
        "from": "B1",
        "to": "B2",
        "r_ohm": 0.3,
        "x_ohm": 0.25,
        "s_max_kva": 500
      },
      {
        "id": "BR2",
        "from": "B2",
        "to": "B3",
        "r_ohm": 0.25,
        "x_ohm": 0.2,
        "s_max_kva": 400
      },
      {
        "id": "BR3",
        "from": "B3",
        "to": "B4",
        "r_ohm": 0.2,
        "x_ohm": 0.18,
        "s_max_kva": 300
      },
      {
        "id": "BR4",
        "from": "B2",
        "to": "B5",
        "r_ohm": 0.28,
        "x_ohm": 0.22,
        "s_max_kva": 350
      },
      {
        "id": "BR5",
        "from": "B5",
        "to": "B6",
        "r_ohm": 0.22,
        "x_ohm": 0.18,
        "s_max_kva": 250
      }
    ]
  },
  "pvs": {
    "pvs": [
      {
        "id": "PV1",
        "bus": "B3",
        "p_avail_kw": 60,
        "s_rated_kva": 75
      },
      {
        "id": "PV2",
        "bus": "B4",
        "p_avail_kw": 40,
        "s_rated_kva": 50
      },
      {
        "id": "PV3",
        "bus": "B6",
        "p_avail_kw": 35,
        "s_rated_kva": 45
      }
    ]
  }
}

Recent invocations(0)

No invocations yet — be the first to call this agent.