access icon free Stochastic economic dispatch of power system with multiple wind farms and pumped-storage hydro stations using approximate dynamic programming

The stochastic economic dispatch problem of power system with multiple wind farms and pumped-storage hydro stations is formulated as a specific stochastic dynamic programming (DP) model, i.e. stochastic storage model, it is impossible to obtain an accurate solution due to the curse of dimensionality. Based on the approximate DP (ADP) method, the stochastic storage model can be transformed into a series of mixed-integer linear programming (MILP) models by describing the approximate value functions (AVFs) as convex piecewise linear functions in post-decision states. The AVFs are first initialised using the results of the deterministic model under a forecast scenario of wind farm output and then trained by scanning stochastic sampling scenarios consecutively with the successive projective approximation routine algorithm. To obtain a near-optimal day-ahead dispatch scheme, the forecast scenario is substituted into the MILP models expressed by the trained AVFs and is solved forward through each time interval. The network constraints are incorporated by the while-loop detection of critical lines. Test results on an actual provincial power system and the modified IEEE 39-bus system, including the comparison among the ADP, DP, scenario-based and chance-constrained programming methods, demonstrate the feasibility and efficiency of the proposed model and algorithm.

Inspec keywords: approximation theory; stochastic programming; integer programming; linear programming; power generation economics; wind power plants; power generation dispatch; optimisation; pumped-storage power stations; power system security; stochastic processes; dynamic programming

Other keywords: actual provincial power system; deterministic model; approximate dynamic programming; modified IEEE 39-bus system; forecast scenario; convex piecewise linear functions; MILP models; stochastic storage model; approximate DP method; approximate value functions; stochastic sampling scenarios; multiple wind farms; mixed-integer linear programming models; pumped-storage hydro stations; near-optimal day-ahead dispatch scheme; stochastic economic dispatch problem; successive projective approximation routine algorithm; specific stochastic dynamic programming model; wind farm output; AVFs

Subjects: Optimisation techniques; Wind power plants; Pumped storage stations and plants; Monte Carlo methods; Optimisation techniques; Power system management, operation and economics

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