The profit based unit commitment problem involves determining the time intervals at which a particular generating unit should be online and available for generation, and the associated generation or dispatch, the aim being to maximize its total profits based on a given price profile. This problem can be attacked by various techniques like single unit dynamic programming, lagrangian relaxation, ...

The increasing penetration of uncertain generation such as wind and solar in power systems imposes new challenges to the Unit Commitment (UC) problem, one of the most critical tasks in power systems operations. The two most common approaches to address these challenges — stochastic and robust optimization — have drawbacks that prevent or restrict their application to real-world systems. This pa...

This paper presents a binary PSO based solution technique for power system unit commitment. The intelligent generation of initial population and the repairing mechanism ensure feasible solution that satisfies the spinning reserve and unit minimum up/down constraints. The algorithm adoptively adjusts the inertia weight and the acceleration coefficients in order to enhance the search process and ...

Unit commitment is a complex decision-making process because of multiple constraints which must not be violated while nding the optimal or a near-optimal commitment schedule. This paper discusses the application of genetic algorithms for determining short term commitment order of thermal units in power generation. The objective of the optimal commitment is to determine the on/oo states of the u...

The unit commitment (UC) problem aims to find an optimal schedule of generating units subject to demand and operating constraints for an electricity grid. The majority of existing algorithms for the UC problem rely on solving a series of convex relaxations by means of branch-and-bound and cuttingplanning methods. The objective of this paper is to obtain a convex model of polynomial size for pra...

In existing delegation models, delegation security entirely depends on delegators and security administrators, for delegation constraint in these models is only a prerequisite condition. This paper proposes an Attribute-Based Delegation Model (ABDM) with an extended delegation constraint consisting of both delegation attribute expression (DAE) and delegation prerequisite condition (CR). In ABDM...

Ant colony optimization (ACO) was inspired by the observation of natural behavior of real ants’ pheromone trail formation and foraging. Ant colony optimization ismore suitable for combinatorial optimization problems. ACO is successfully applied to the traveling salesman problem. Multistage decision making of ACO gives an edge over other conventional methods. This paper proposes evolving ant col...

Ant Colony Optimization is more suitable for combinatorial optimization problems. ACO is successfully applied to the traveling salesman problem, and multistage decision making of ACO has an edge over other conventional methods. In this paper, the authors propose the Evolving Ant Colony Optimization (EACO) method for solving unit commitment (UC) problem. The EACO employs Genetic Algorithm (GA) f...

Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC’s birth, there have been two major waves of revolution on UC research and real life practice. The first wave has made mixed integer programming stand out from the early solution and...

Fuzzy Dynamic Programming approach to the solution of unit commitment problem is presented and described in detail. The Fuzzy Dynamic programming provides the ‘fuzzy’ preference in obtaining an optimal solution in the presence of conflicting objectives and constraints. The Fuzzy dynamic programming handles one objective (i.e. minimization of operational cost) and two constraints (i.e. generatio...