Coordinated Planning With Predetermined Renewable Energy Generation Targets Using Extended Two-Stage Robust Optimization

Abstract

Coordinated planning is an effective method to balance investment costs and benefits in achieving high renewable target under the renewable-driven power system expansion wave. This paper proposes a coordinated planning model to support the efficient achievement of renewable target considering economy of the system by accounting for the interaction among source, grid, and energy storage system. An adaptive two-stage min-max-min robust optimization model is formulated to take into account renewable target as well as the uncertainty associated with renewable production and load demand. To reduce the conservatism of robust optimization, uncertain budget, multiple uncertain sets, and data-driven method are used to design uncertain sets. The resulting model is transformed into a tractable bi-level programming through strong duality theory and big-M method. A customized column-and-constraint generation algorithm is used to solve the bi-level programming. Simulation results presented for the modified IEEE 30-bus test system corroborates the effectiveness of the methodology, which finds siting and sizing of renewable energy sources and energy storage systems as well as transmission expansion schemes. It is capable to provide a flexible planning tool driven by renewable target under a reasonable computational burden.

Frequency-constrained Co-planning of Generation and Energy Storage with High-penetration Renewable Energy

“…Specifically, group A contains three 300 MW wind farms located at buses 1, 2, and 3; group B contains three 400 MW wind farms located at buses 6, 7, and 8; group C contains three 500 MW wind farms located at buses 20, 21 and 22. All wind farms are installed with a cost of 0.5 M$/(MW•year) [39]. The parameters of candidate BESS are listed in Table II.…”

Bi-Level Multi-Objective Optimal Design of Integrated Energy System Under Low-Carbon Background

“…Generally, the bi-level planning model can be transform into mathematical programs with equilibrium constraints (MPEC) model [23], [24] for one-time solution based on duality theory or Karush-Kuhn-Tucker conditions. When facing the bi-level max-min problems, the column-andconstraint generation algorithm [25], [26] and Benders decomposition algorithm [27], [28] can transform the max-min problem into single level max problem to solve. However, this process still requires the inner layer model to be convex.…”

“…x is the upper-level investment variable optimized from the main problem (26), which is taken as a known quantity into the sub-problem 1 to solve the lower-level objective function.…”

Application of Dynamically Search Space Squeezed Modified Firefly Algorithm to a Novel Short Term Economic Dispatch of Multi-Generation Systems

“…The optimization problem dealing with the optimal power scheduling of two major conventional sources, the hydroelectric source and the thermal energy source is known as the Short Term Hydro-Thermal Scheduling (STHTS) problem in literature. Several deterministic and heuristic techniques are suggested by the authors over the years to find the global optimum of the aforementioned problem [7], [8]. However, the addition of the distributed energy sources to the conventional grid requires more advanced optimization methods to efficiently solve the economic dispatch of the hybrid systems.…”