A two-stage strategy for security-constrained AC dynamic transmission expansion planning

Optimized time reduction models applied to power and energy systems planning – Comparison with existing methods

“…The simplest approach consists in solving a new problem over the shorter time set T'. The time series profiles x ̃t',n in (7) aggregate the representative daily patterns arranged according to their order of occurrence in the original set of days D. The variables and constraints are then defined along this new temporal set and the objective function shall take into account the length ratio between the original problem and the reduced one (( 11))problem re-formulation denoted OPT0.…”

“…'Power systems' denote electrical networks for which the power balance shall be ensured at every node or bus in addition to the fulfilment of grid constraints (e.g. voltage and current limits) [7].…”

Simultaneous generation and network expansion planning in large‐scale power systems under exact AC power flow equations

“…From the viewpoint of optimization methods to provide optimal schemes in a computationally tractable manner, the previous studies can be classified as metaheuristic-and mathematical-based ones. The first class of references applies approaches like real genetic algorithm (GA) [8,9], decimal codification GA [47,48], non-dominated sorting genetic algorithm II (NSGA II) [17,18], particle swarm optimization (PSO) [10][11][12]29], improved discrete PSO [49,50], a combination of PSO and GA (PSO+GA) [27], differential evolution (DE) [13][14][15][16], DE-continuous population-based incremental learning (DE-PBILC) [24,25], artificial bee colony (ABC) [46], modified ABC [19][20][21], discrete ABC [52], improved discrete ABC [51], ant colony optimization algorithm for continuous domains (ACOR) [23], a combination of firefly algorithm and harmonic search algorithm (FFA+HAS) [39], adaptive tabu search (TS) [53], and hybridization of GA, TS, and artificial neural network (GA + TS + ANN) [28]. The latter one uses interior point method (IPM) [7], primal-dual interior-point method (PDIPM) [26], benders decomposition [34,38,40,44] or describes MINLP [22,36], mixed-integer linear programming (MILP) [30-33, 39, 41, 45, 52], and mixed-integer second-order cone programming (MISOCP) …”

Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties

“…Due to the problem complexity, Due to the problem complexity, AC power flow model in power system planning is rarely considered. However, the accurate AC power flow model has attracted researcher to reformulate the nonlinear equation to obtain the solution [21]- [26]. Reference [22] has developed a less relaxed network model using the AC model to obtain a more realistic planning solution as compared to traditional DC model.…”

“…To tackle the nonlinear AC model while considering N-1 contingency, reference [25] applies a modified artificial bee colony algorithm to solve the expansion model. Similarly, reference [26] utilizes a novel evolutionary algorithm based on the best features of particle swarm optimization (PSO) and genetic algorithm (GA) to solve the multi-year AC dynamic transmission expansion planning.…”