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access icon free Stochastic optimal dispatch of PV/wind/diesel/battery microgrids using state-space approximate dynamic programming

© The Institution of Engineering and Technology
Received 10/06/2018, Accepted 29/04/2019, Revised 28/01/2019, Published 02/05/2019

In the operation of microgrids (MGs), the stochastic production of solar/wind, the discrete variables of photovoltaic (PV) inverter's auxiliary service state and diesel generators’ (DGs’) off–on state generally need to be considered, and a stochastic mixed-integer non-linear non-convex programming (MINNP) model is established for the optimal dispatch of MGs. In this model, the expected value of the sum of DGs’ operation as well as start-up cost, the network-loss cost and the PV inverter's auxiliary service cost, is considered as the objective function. The stochastic MINNP model is transformed into a stochastic mixed-integer second-order cone programming (MISOCP) model to reduce the computational complexity. The state-space approximate dynamic programming algorithm is adopted to solve the stochastic MISOCP model. In the algorithm, based on the approximate value functions of typical states that are computed according to the Markov decision process, solving the optimisation model of multiple periods is executed by solving each period's optimisation model one by one to improve the computational efficiency. Meanwhile, parallel computing is executed to greatly improve the efficiency of the proposed algorithm. Test results on two modified IEEE-33 bus and IEEE-123 bus islanded MGs with PV/wind/diesel/battery demonstrate the correctness and efficiency of the proposed model and algorithm.

Inspec keywords: integer programming; nonlinear programming; photovoltaic power systems; wind power plants; power generation dispatch; Markov processes; hybrid power systems; battery storage plants; distributed power generation; concave programming; diesel-electric power stations; convex programming

Other keywords: mixed-integer nonlinear nonconvex programming; Markov decision process; photovoltaic inverter; stochastic MINNP model; PV inverter; stochastic optimal dispatch; PV/wind/diesel/battery microgrids; stochastic MISOCP model; state-space approximate dynamic programming algorithm; stochastic mixed-integer second-order cone programming model; diesel generators

Subjects: Other power stations and plants; Wind power plants; Distributed power generation; Solar power stations and photovoltaic power systems; Diesel power stations and plants; Power system management, operation and economics; Markov processes; Optimisation techniques

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