ABC ALGORITHM BASED SCHEDULING AND CONTROL OF RENEWABLE HYBRID POWER SYSTEM

Artificial bee colony algorithm has applied here for solving the problem of unit sizing and control of renewable hybrid power system. Among alternate energy resource Wind and Solar have attained the main focus over the time but these two would not be enough for showing irregular power generation behavior. Hybrid power system which comprises of different non-conventional power system like micro hydro plant, solar panel, wind turbine and battery is introduced. Initially the combination of Hydro-Solar-Wind-Battery Bank hybrid system has analyzed for maximum load profile. Later on, its performance has compared with other hybrid systems combining Hydro-Wind-Battery Bank. After considering the maximum load for obtaining the sizing and scheduling, these two systems have again analyzed for different load conditions with ABC Algorithm. It is further demonstrated that results obtained from ABS are better than PSO. Analysis of power generation has done on the basis of Energy Cost and Net Present Cost and ended with overall scheduling and cost comparison on hourly basis.

[1]  R. Srinivasa Rao,et al.  Optimization of Distribution Network Configuration for Loss Reduction Using Artificial Bee Colony Algorithm , 2008 .

[2]  Nguyen Tung Linh,et al.  Application Artificial Bee Colony Algorithm (ABC) for Reconfiguring Distribution Network , 2010, 2010 Second International Conference on Computer Modeling and Simulation.

[3]  Roy Billinton,et al.  Unit Commitment Risk Analysis of Wind Integrated Power Systems , 2009 .

[4]  N. Chakraborty,et al.  Differential evolution technique-based short-term economic generation scheduling of hydrothermal systems , 2008 .

[5]  Ettore Francesco Bompard,et al.  A self-adaptive chaotic particle swarm algorithm for short term hydroelectric system scheduling in deregulated environment , 2005 .

[6]  Srikrishna Subramanian,et al.  Modified ABC Algorithm for Generator Maintenance Scheduling , 2011 .

[7]  Dantong Ouyang,et al.  An artificial bee colony approach for clustering , 2010, Expert Syst. Appl..

[8]  Yanbin Yuan,et al.  An enhanced differential evolution algorithm for daily optimal hydro generation scheduling , 2008, Comput. Math. Appl..

[9]  L. Lakshminarasimman,et al.  A modified hybrid differential evolution for short-term scheduling of hydrothermal power systems with cascaded reservoirs , 2008 .

[10]  Jian Ma,et al.  Incorporating Uncertainty of Wind Power Generation Forecast Into Power System Operation, Dispatch, and Unit Commitment Procedures , 2011, IEEE Transactions on Sustainable Energy.

[11]  Bijaya K. Panigrahi,et al.  Application of Artificial Bee Colony to economic load dispatch problem with ramp rate limits and prohibited operating zones , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).