scispace - formally typeset
Proceedings ArticleDOI

Unit commitment using DP — An exhaustive working of both classical and stochastic approach

TLDR
DP is used to solve the stochastic model for unit commitment problem and the commitment is in such a way that the total cost is minimal.
Abstract
In the present electricity market, where renewable energy power plants have been included in the power systems there is a lot of unpredictability in the demand and generation. There are many conventional and evolutionary programming techniques used for solving unit commitment problem. The use of augmented Lagrangian technique by convergence of decomposition method was proposed in 1994, and in 2007 chance constrained optimization was used for providing a solution to the stochastic unit commitment problem. Dynamic Programming is a conventional algorithm used to solve deterministic problem. In this paper DP is used to solve the stochastic model. The stochastic modeling for generation side has been formulated using an approximate state decision approach. The programs were developed in MATLAB environment and were extensively tested for 4 unit 8 hour system. The results obtained from these techniques were validated with the available literature and outcome was satisfactory. The commitment is in such a way that the total cost is minimal.

read more

Citations
More filters
Journal ArticleDOI

Fast Near-Optimal Heuristic for the Short-Term Hydro-Generation Planning Problem

TL;DR: A three-phase approach based on price decomposition that yields quickly near-optimal solutions to large-scale real-world instances to be tested on Hydro-Québec's production system.

A Solution to Unit Commitment Problem via Dynamic Programming and Particle Swarm Optimization

TL;DR: In this article, a particle swarm optimization technique is used which is population based global searching optimization technique to solve the unit commitment problem, for committing the units optimally, which is arrived from the exploration on the bird and fish flocking movement behavior.
Journal ArticleDOI

Solver-Based Mixed Integer Linear Programming (MILP) Based Novel Approach for Hydroelectric Power Generation Optimization

TL;DR: The preliminary optimization results show an increase of $22,000 and $29,130 in the profit for storage and ROR hydropower plants, respectively, which is 19% more than average income, ensuring the credibility of the proposed algorithm for maximizing the revenue ($), is aimed to facilitate and assist better planning for electric power producers.

Hydroelectric power generation and distribution planning under supply uncertainty

TL;DR: This thesis combines both ROR projects and storage dam projects and formulate the problem as a stochastic program to minimize the cost of energy generation and distribution under ROR Projects supply uncertainty.
References
More filters
Book

Power Generation, Operation, and Control

TL;DR: In this paper, the authors present a graduate-level text in electric power engineering as regards to planning, operating, and controlling large scale power generation and transmission systems, including characteristics of power generation units, transmission losses, generation with limited energy supply, control of generation, and power system security.
Journal ArticleDOI

A Branch-and-Bound Algorithm for Unit Commitment

TL;DR: In this paper, a branch-and-bound approach is presented for solving the unit commitment problem based on branch and bound techniques. But it does not require a priority ordering of the units.
Journal ArticleDOI

Unit commitment by enhanced adaptive Lagrangian relaxation

TL;DR: The proposed enhanced adaptive Lagrangian relaxation (ELR) for a unit commitment (UC) problem consists of adaptive LR (ALR) and heuristic search and the total system production costs are less expensive than the others especially for the large number of generating units.
Journal ArticleDOI

Integer Programming Approach to the Problem of Optimal Unit Commitment with Probabilistic Reserve Determination

TL;DR: A method for determining the unit commitment schedule for hydro-thermal systems using extensions and modifications of the Branch and Bound method for Inteler Programming has been developed and significant features include its computational practicability for realistic systems and proper representation of reserves associated with different risk levels.
Journal ArticleDOI

An intelligent dynamic programming for unit commitment application

TL;DR: A heuristic improvement of the truncated window dynamic programming has been studied for the unit commitment application and results indicate a substantial saving in the computation time without sacrificing the quality of the solution.
Related Papers (5)