The objective of this paper is to provide a robust Virtual Power Plant(VPP)network collaborated with Internet of Things(IoT)which uses a conceptual model to integrate each device in the grid.Based on the functionality...The objective of this paper is to provide a robust Virtual Power Plant(VPP)network collaborated with Internet of Things(IoT)which uses a conceptual model to integrate each device in the grid.Based on the functionality all the devices which are purely distributed within the grid are networked initially from residential units to substations and up to service data and demand centres.To ensure the trapping of the available power and the efficient transfer of Distributed Generation(DG)power to the grid Distribution Active Control(DAC)strategy is used.Synchronized optimization of DG parameter which includes DG size,location and type are adopted using Dispatch strategy.The case studies are optimized by rescheduling the generation and with load curtailment.Maximized Customer Benefit(MCB)is taken as an objective function and a straight forward solution is given by heuristic search techniques.This method was vindicated in a practical Indian Utility system.This control proposes better performances,ensures reliability and efficiency even under parameter variations along with disturbances which is justified using IEEE 118 bus system and real time Indian utility 63 bus system.Results reveal that the proposed technique proves advantages of low computational intricacy.展开更多
The intent of this paper is to schedule short-term hydrothermal system probabilistically considering stochastic operating cost curves for thermal power generation units and uncertainties in load demand and reservoir w...The intent of this paper is to schedule short-term hydrothermal system probabilistically considering stochastic operating cost curves for thermal power generation units and uncertainties in load demand and reservoir water inflows. Therefore, the stochastic multi-objective hydrothermal generation scheduling problem is formulated with explicit recognition of uncertainties in the system production cost coefficients and system load, which are treated as random variable. Fuzzy methodology has been exploited for solving a decision making problem involving multiplicity of objectives and selection criterion for best compromised solution. A real-coded genetic algorithm with arithmetic-average-bound-blend crossover and wavelet mutation operator is applied to solve short-term variable-head hydrothermal scheduling problem. Initial feasible solution has been obtained by implementing the random heuristic search. The search is performed within the operating generation limits. Equality constraints that satisfy the demand during each time interval are considered by introducing a slack thermal generating unit for each time interval. Whereas the equality constraint which satisfies the consumption of available water to its full extent for the whole scheduling period is considered by introducing slack hydro generating unit for a particular time interval. Operating limit violation by slack hydro and slack thermal generating unit is taken care using exterior penalty method. The effectiveness of the proposed method is demonstrated on two sample systems.展开更多
文摘The objective of this paper is to provide a robust Virtual Power Plant(VPP)network collaborated with Internet of Things(IoT)which uses a conceptual model to integrate each device in the grid.Based on the functionality all the devices which are purely distributed within the grid are networked initially from residential units to substations and up to service data and demand centres.To ensure the trapping of the available power and the efficient transfer of Distributed Generation(DG)power to the grid Distribution Active Control(DAC)strategy is used.Synchronized optimization of DG parameter which includes DG size,location and type are adopted using Dispatch strategy.The case studies are optimized by rescheduling the generation and with load curtailment.Maximized Customer Benefit(MCB)is taken as an objective function and a straight forward solution is given by heuristic search techniques.This method was vindicated in a practical Indian Utility system.This control proposes better performances,ensures reliability and efficiency even under parameter variations along with disturbances which is justified using IEEE 118 bus system and real time Indian utility 63 bus system.Results reveal that the proposed technique proves advantages of low computational intricacy.
文摘The intent of this paper is to schedule short-term hydrothermal system probabilistically considering stochastic operating cost curves for thermal power generation units and uncertainties in load demand and reservoir water inflows. Therefore, the stochastic multi-objective hydrothermal generation scheduling problem is formulated with explicit recognition of uncertainties in the system production cost coefficients and system load, which are treated as random variable. Fuzzy methodology has been exploited for solving a decision making problem involving multiplicity of objectives and selection criterion for best compromised solution. A real-coded genetic algorithm with arithmetic-average-bound-blend crossover and wavelet mutation operator is applied to solve short-term variable-head hydrothermal scheduling problem. Initial feasible solution has been obtained by implementing the random heuristic search. The search is performed within the operating generation limits. Equality constraints that satisfy the demand during each time interval are considered by introducing a slack thermal generating unit for each time interval. Whereas the equality constraint which satisfies the consumption of available water to its full extent for the whole scheduling period is considered by introducing slack hydro generating unit for a particular time interval. Operating limit violation by slack hydro and slack thermal generating unit is taken care using exterior penalty method. The effectiveness of the proposed method is demonstrated on two sample systems.
