Solution to short term hydrothermal scheduling problem by modified subgradient algorithm based on feasible values

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

“…The best solution among all Pareto solutions was then selected utilizing a fuzzy satisfying method. In reference [69], the modified sub-gradient algorithm based on feasible values (F-MSG) was implemented to solve CSTHTS problem by considering additional constraints like off-nominal tap ratio constraints, SVAR system susceptances constraints on 16-bus test-system. Reference [70] solved the CSTHTS problem by implementing the two-stage linear programming with special ordered sets algorithm (TLPSOS) which works by modelling the nonlinear thermal cost functions and hydro-power output functions using the special ordered sets.…”

“…Reference [81] applied the recurrent neural network technique to solve CSTHTS problem. Given below are the details of the works on short term hydrothermal scheduling problem using meta- Decomposition approach with linear programming [63] First order gradient technique with non-linear programming [64] Sequential quadratic programming [65] Lexicographic order andconstraint method [67], [68] Normal boundary intersection method [68] Modified sub-gradient algorithm based on feasible values (F-MSG) [69], [71] Two-stage linear programing with special ordered sets algorithm (TLPSOS) [70] heuristic optimization algorithms. The following sections are presented in terms of the types of STHTS problem and for each type, the implementations of metaheuristic algorithms, as present in literature, is presented.…”