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Least-Cost Overvoltage Control in PV-Rich Distribution Networks via Unbalanced Optimal Power Flow

Andrea Espinosa del Pozo, Araceli Hernandez, Luis Badesa

Abstract

The increasing penetration of photovoltaic (PV) generation in low-voltage distribution networks presents operational challenges, with overvoltages being among the most critical. This study introduces a tool based on Unbalanced Optimal Power Flow (UBOPF) to assess cost-effective local inverter control strategies specifically aimed at mitigating overvoltage issues. Two approaches are examined: dynamic active power curtailment and combined active and reactive power control. These strategies are tested on a residential low-voltage network with high PV penetration, where the UBOPF model with voltage-magnitude constraints was implemented in Julia using the JuMP optimization package. The results demonstrate that both methods are effective in maintaining voltage levels within regulatory limits, with the latter leading to lower PV curtailment. The analysis highlights the need to consider these control actions as ancillary services to the grid, which should be properly compensated given their effect on generator revenues.

Least-Cost Overvoltage Control in PV-Rich Distribution Networks via Unbalanced Optimal Power Flow

Abstract

The increasing penetration of photovoltaic (PV) generation in low-voltage distribution networks presents operational challenges, with overvoltages being among the most critical. This study introduces a tool based on Unbalanced Optimal Power Flow (UBOPF) to assess cost-effective local inverter control strategies specifically aimed at mitigating overvoltage issues. Two approaches are examined: dynamic active power curtailment and combined active and reactive power control. These strategies are tested on a residential low-voltage network with high PV penetration, where the UBOPF model with voltage-magnitude constraints was implemented in Julia using the JuMP optimization package. The results demonstrate that both methods are effective in maintaining voltage levels within regulatory limits, with the latter leading to lower PV curtailment. The analysis highlights the need to consider these control actions as ancillary services to the grid, which should be properly compensated given their effect on generator revenues.
Paper Structure (25 sections, 15 equations, 8 figures, 9 tables)

This paper contains 25 sections, 15 equations, 8 figures, 9 tables.

Table of Contents

  1. Introduction
  2. Overvoltage Phenomena in Low-Voltage Networks and Inverter-Based Control Strategies
  3. Overvoltage Phenomena in LV Distribution Networks
  4. Inverter-Based Strategies for Overvoltage Mitigation
  5. Dynamic Active Power Curtailment
  6. Combined Active and Reactive Power Control
  7. Local vs. Centralized Control Implementation
  8. Regulatory and Economic Considerations
  9. UBOPF Formulation
  10. Nomenclature
  11. Branch Admittance Matrix Construction
  12. Global Nodal Admittance Matrix Construction
  13. Nodal Power-Balance Equations
  14. Definition of Line Power Flows
  15. Optimization Problem
  16. ...and 10 more sections

Figures (8)

  • Figure 1: Operating points under different inverter control strategies with a local voltage constraint of $V = 1.1\,\mathrm{pu}$ shown as a straight line in the $P$--$Q$ plane. Point 0: full active power injection without control, leading to overvoltage. Point 1: active power curtailment at unity power factor. Point 2: combined active and reactive power control to maximize active power injection while remaining within voltage limits.
  • Figure 2: Three-phase $\pi$-model of a distribution line between nodes $i$ and $j$.
  • Figure 3: Reference low-voltage distribution network with 18 nodes, 20 residential loads (C1–C20) and 16 PV inverters (G1–G16).
  • Figure 4: Voltage profile in phase B without control. Overvoltages occur at nodes with high PV injection and weak local load.
  • Figure 5: Curtailment percentage under P-only and coordinated P+Q control strategies in the baseline scenario and scenarios S1 ('Excess PV Generation + Low Demand') and S2 ('High Residential Demand').
  • ...and 3 more figures