Solution to Economic Power Dispatch Planning Problem considering Generator Constraints using Artificial Bee Colony Algorithm

Navpreet Singh Tung,Sandeep Chakravorty 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.5

Optimum active and reactive power dispatch is an inherent part of power system generation planning and it is the need of an hour for the electrical utilities and power engineers to dig this area in short and long term planning scenarios. Load demand requirements subjected to economic feasible solutions matching voltage profile, power demand, minimization of losses, voltage stability and improve the capacity of the system is the need of the hour. Optimization techniques based on evolutionary computing, artificial intelligence, search method finds their applications in the area of economic load dispatch planning to reach global optimal solution for this multi-decision, multi-objective combinatorial problem subjected to different constraints. In this paper, ant bee colony based algorithm has been proposed to solve economic dispatch problem. Unlike other heuristic algorithms, ABC utilizes search space as multi-step decision process. It possesses a flexible and well-balanced operator to enhance and adapt the global and fine tune local search to follow the minimum cost path in the search boundary. The suggested technique is tested on IEEE 25 bus system. Test results are compared with other techniques presented in literature.

Gravity Local Search Inspired Particle Swarm Algorithm for Economic Power Dispatch Planning Problem in Small Scale System

Navpreet Singh Tung,Sandeep Chakravorty,Harkamal Singh Bhullar 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.5

This research presents novel Particle swarm optimization inspired by gravitational based search method to solve active power dispatch problem in electrical power system planning. The proposed PSO utilizes the operator of social thinking coupled with search capacity of gravity inspired algorithm to formulate and develop technique for active power dispatch problem to satisfy power demand requirements. Optimal scheduling of generators and system constraints to match load demand and losses is successfully done with proposed method. Total operating cost is minimized satisfying various bounds of system with proposed method. Exploration and convergence efficiency are evaluated to checklist the computational efficiency and robustness of the proposed technique. The suggested technique is tested and evaluated on different test systems comprises three, five, six test systems. Test results are compared with other techniques presented in literature .Investigations shows promising results which further benchmark the effectiveness of proposed method to solve complex optimization non linear problems.

Ant Lion Optimizer based Approach for Optimal Scheduling of Thermal Units for Small Scale Electrical Economic Power Dispatch Problem

Navpreet Singh Tung,Sandeep Chakravorty 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.7

A novel nature inspired algorithm ant lion optimizer (ALO) is recently developed which is motivated from the hunting mechanism of ant lions .Inherit steps of hunting prey such as the random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building are simulated to find the optimal solution of real life problems . Intelligent and Optimization techniques based on evolutionary computing, metaheuristic,biological base,nature inspired, search method establish their applications in the area of electrical economic power dispatch planning(EEPDP) to reach global optimal solution for this multi scale, multi-decision, multi-objective combinatorial problem subjected to different constraints.An application of ALO to solve non linear elec-tric economic power dispatch problem(EEPDP) is proposed in this paper. Efficient and optimal planning of economic electrical power dispatch problem is an integral part of economic electrical energy generation planning and it is the need of time for the electrical engineers to browse this area in multi-scale planning scenarios.. The performance of s ant lion optimizer (ALO) to solve electrical economic power dispatch problem is tested on three and six unit system.Test results are compared with other techniques grey wolf optimization(GWO),cuckoo search(CS),artificial bee colony(ABC),firefly algorithm(FA),particle swarm optimization(PSO),shuffled frog leap (SFL) ,bacteria foraging algorithm(BFO),harmony search(HS) applied in literature. Simulation results proved that the ALO technique is better as compared to other nature inspired,heuristic,metaheuristic techniques to find global minima and maintain the solution quality in terms of low fuel cost.

Neuro Inspired Genetic Hybrid Algorithm for Active Power Dispatch Planning Problem in Small Scale System

Navpreet Singh Tung,Prof. (Dr). Sandeep Chakravorty 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.9

Allocation of optimum active power is a backbone of power system generation planning and its high impact contribution is the need of current electrical utilities and power engineers need to browse this area in short and long term planning scenarios. Power demand requirements mapped to economic feasible solutions matching voltage profile, power demand, minimization of losses, voltage stability and improve the capacity of the system is the need of the hour. Modern techniques based on evolutionary computing, artificial intelligence, search method find their objectives in the area of economic load dispatch planning to reach global optimal solution for this multi-decision, multi-objective combinatorial problem subjected to different constraints. Many algorithms suffer from global convergence problem. To vanish this drawback, neuro inspired genetic hybrid algorithm (NIGHA) has been proposed in this paper to solve economic dispatch problem. Unlike other algorithms, NIGHA utilizes the weights of Neural Network to explore information and knowledge to train GA parameters to search for feasible region where optimal global solution converges. The suggested technique is tested on IEEE 25 bus system. Test results are compared with other techniques presented in literature. Proposed technique has outperformed other methods in terms of cost, computation time.

Water Cycle Algorithm for Small Scale Electrical Economic Power Dispatch Problem

Navpreet Singh Tung,Sandeep Chakravorty 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.8

Efficient and optimal planning of economic electrical power dispatch problem is an integral part of economic electrical energy generation planning and it is the need of time for the electrical engineers to browse this area in multi-scale planning scenarios. Intelligent and Optimization techniques based on evolutionary computing, metaheuristic,biological base,nature inspired, search method establish their applications in the area of electrical economic power dispatch planning(EEPDP) to reach global optimal solution for this multi scale, multi-decision, multi-objective combinatorial problem subjected to different constraints. In this paper, water cycle algorithm (WCA) has been proposed to solve electrical economic power dispatch problem for three and six unit system.This is based on how the streams and rivers flow downhill towards the sea and recycle in nature The suggested technique is tested on small scale system of three and six unit system of EEPDP considering various equality and inequality constraints . Test results are compared with other techniques grey wolf optimization(GWO),cuckoo search(CS),artificial bee colony(ABC),firefly algorithm(FA),particle swarm optimization(PSO),shuffled frog leap (SFL) ,bacteria foraging algorithm(BFO),harmony search(HS) applied in literature.Convergence of solution with iteration is presented for both cases.Simulation results proved that the WCA technique is better as compared to other nature inspired,heuristic,metaheuristic techniques to find global minima and maintain the solution quality in terms of low fuel cost.

Grey Wolf Optimization for Active Power Dispatch Planning Problem Considering Generator Constraints and Valve Point Effect

Navpreet Singh Tung,Sandeep Chakravorty 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12

This research proposed an application of swarm inspired new meta heuristic algorithm Grey Wolf Optimization to solve active power dispatch problem imposing valve point effect and generator constraints. Grey Wolf optimization is based on mathematical approach whose solution convergence inspired by the leadership hierarchy and hunting mechanism of grey wolves. It explores search space as a multi-level decision mechanism and does not require gradient for search path. This approach converged to global optimal solution in spite of the non linearity added by valve point effect while solving the fitness function. Optimal scheduling of generators to minimize the total operating cost coupled with generator constraints and valve point effect to match load demand is implemented with proposed method and. Exploration, Computation and Convergence power are evaluated to track the computational efficiency of the proposed technique. The presented technique is tested on different test cases comprises three, six and thirteen test systems incorporating valve point effect. Test results are compared with other nature and bio inspired algorithms presented in literature .Analysis shows cut throat results as total operating cost turns out to be minimum as compared to other techniques which infers the effectiveness of proposed method and encourage to further explore the potential of proposed method to solve complex optimization problems in active power dispatch planning area.