## Abstract

The classical optimal power flow (OPF) problem optimizes the power flow in a power network considering the associated flow and operating constraints. In this paper, we investigate OPF in the context of utility-maximizing demand response management in distribution networks, in which customers' demands are satisfied subject to the operating constraints of voltage and transmission power capacity. The prior results concern only elastic demands that can be partially satisfied, whereas power demands in practice can be inelastic with binary control decisions, which give rise to a mixed integer programming problem. We shed light on the hardness and approximability by polynomial-time algorithms for problem with inelastic demands. We show that this problem is inapproximable for general power network topology with upper and lower bounds of nodal voltage. Then, we propose an efficient algorithm for a relaxed problem in radial networks with bounded transmission power loss and upper bound of nodal voltage. We derive an approximation ratio between the proposed algorithm and the exact optimal solution. Simulations show that the proposed algorithm can produce close-to-optimal solutions in practice.

Original language | British English |
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Pages (from-to) | 513-524 |

Number of pages | 12 |

Journal | IEEE Transactions on Control of Network Systems |

Volume | 5 |

Issue number | 1 |

DOIs | |

State | Published - Mar 2018 |

## Keywords

- Approximation algorithms
- discrete optimization
- inapproximability
- inelastic demands
- optimal power flow