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Inspired by potential application in power systems and a fully distributed primal-dual method, we investigate how a novel distributed optimization algorithm can be used to solve the dispath response problem in power systems with a distributed manner, whose main target is to minimize the generation cost of the whole network. The problem we study here can be formulated as a kind of optimization problem,...
Error control coding scheme improves adequate redundancy in communication system. Turbo Code (TC) and its elevated form like 3-Dimensional Turbo Code (3D-TC) are considered as important channel coding scheme, which tend to Shannon limit. In the meantime, substantial development in the field of intelligent computational technique has motivated the researchers to apply this algorithm in various engineering...
The extension of Transmission Locational Marginal Cost Prices (LMP) to Distribution node LMPs, or DLMPs, is a prerequisite for efficient demand response that may support significant integration of Renewables. AC load flow and non-linear distribution cost modeling needed to this end, render centralized market clearing Algorithms intractable, with Distributed Proximal Message Passing (PMP) Algorithms...
After Fifty years of it's existence the K-means clustering is still popular among researchers due to lower computational complexity. Real time embedded applications require hardwiring of unsupervised learning algorithms like K-means within System-on-Chip for prompt processing in applications like image segmentation, pattern classification, speech recognition etc. This requirement is a must while analyzing...
A Microgrid is assumed to be a cluster of distributed generations operating as a single controllable system to provide reliable power to its local area. Integration and control of large number of sources in a Microgrid is not possible with normal P-Q controls. Microgrid requires algorithm capable of handling various control modes such as PQ, PV and Droop control. A new formulation is required to provide...
To overcome the slow convergence and local optimum of ant colony algorithm, the cloud model theory is adopted to regulate reasonably the randomness of the ant colony algorithm. In this paper, several adaptive strategies are proposed for the parameters of the ant colony algorithm and the cloud model, and for the optimum path determination. Meanwhile, the evaluation algorithm of pheromone distribution...
This paper addresses the distributed resource allocation problem for a network of multiple agents with directed and time-varying communication topologies. Suppose that the total amount of resources is a constant, represented by an equality constraint, and that the amount of resources allocated to each agent is subject to an inequality constraint, called the state constraint. We then aim to solve it...
In this paper, a simple control approach is proposed for the multi-chain systems. This method is based on a switching algorithm of two sets of smooth steering laws. Global exponential convergence of all states is guaranteed. More importantly, the convergence rate is given explicitly. Two concrete methods are proposed for the design of steering laws. One is based on the backstepping design, another...
Power flow calculation of shipboard power system aims at determining operation conditions of the whole system, such as voltages of every bus, power distribution and power loss in shipboard grid, according to given operation conditions and network structure. Ladder-shaped shipboard power system is a newly developed network with greater reliability and flexibility. In this paper, a parallel power flow...
This paper considers the economic dispatch problem for a group of power generating units communicating over an arbitrary strongly connected, weight-balanced digraph. The goal of the group is to collectively meet a specified load while respecting individual generation bounds and minimizing the total generation cost, which corresponds to the sum of individual arbitrary convex functions. We introduce...
This paper focuses on a nonlinear on-line learning control system with some priori knowledge that can be represented with the functions of the gain scheduling. For this, we develop the Gain-Scheduling direct Heuristic Dynamic Programming (GSHDP) controller that is based on the fundamental principle of reinforcement learning. In order to improve the convergence speed of the on-line learning, DL-RM...
The energy management problem in smart grid is a complex optimization problem of a Cyber-Physical System. Distributed cooperative energy management algorithms have great potential to solve this class of problems. In addition to the synchronous distributed algorithms, asynchronous distributed algorithms are more flexible, robust to packet loss and do not require global clock synchronization. In this...
Bat algorithm is a recent addition to the bioinspired algorithms, considered as a new metaheuristic algorithm based on Bat behaviour. This work presents, the optimal solution of economic load dispatch (ELD) is obtained using the proposed bat algorithm. Here the operating cost of a thermal power plant is optimized using Bat algorithm. Numerical results show that the proposed method has good convergence...
Although the problem of k-area coverage has been intensively investigated for dense wireless sensor networks (WSNs), how to arrive at a k-coverage sensor deployment that optimizes certain objectives in relatively sparse WSNs still faces both theoretical and practical difficulties. In this paper, we present a practical algorithm LAACAD (Load balancing k-Area Coverage through Autonomous Deployment)...
In recent years, there has been a growing interest in real world application of heuristic methods. Memetic Algorithm (MA) is one of such effective heuristics. In this paper, we represent an efficient MA for determining optimal proportional-integral-derivative (PID) controller parameters of an AVR system. This MA is developed by combining a competitive variant of Deferential Evolution (DE) and a Local...
In a next generation power system, effective distributed control algorithms could be embedded in distributed controllers to properly allocate electrical power among connected buses autonomously. In this paper, we present a novel approach to solve the economic dispatch problem. By selecting the incremental cost of each generation unit as the consensus variable, the algorithm is able to solve the conventional...
This paper presents an improved particle swarm optimization algorithm (IPSO) to optimal reactive power dispatch and voltage control of power system. The improved particle swarm optimization algorithm introduces the adaptive inertia factor into the classical swarm algorithm to improve the global search capability and accelerate the searching speed. Study the DPSO algorithm to construct the collection...
The traditional serial simulated annealing algorithm has low efficiency, and is high depending on the setup parameters. The author presents a new hybrid parallel simulated annealing algorithm based on multi-thread parallel computing. Algorithm generates a set of random initial points, and then calculates a number of Markov chains in parallel. Each Markov chain has its own setup parameter. At every...
Adaptive focusing particle swarm optimization (AFPSO) based on the balance characteristic between global search and local search of particle swarm optimization was an adaptive swarm intelligence optimization algorithm with preferable ability of global search and search rate. AFPSO was proposed to optimize the reactive power optimization. Based on optimal control principle, AFPSO applied for optimal...
With the influence of electrical field value, electrical field frequency and electrical field direction in electrical equipment radial disturbance, the system always appears several local extremum points. In order to solve this problem, a novel adaptive chaos grads optimization method is presented. Firstly, by using grads descend searching method, the optimal points can be figured out, and these points...
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