A processor implemented method for optimum coal selection for a power plant and power plant optimization, the method comprising: obtaining, via one or more hardware processors, information about types of coal present at one or more locations; obtaining, via the one or more hardware processors, a set of properties of the types of coal from at least one of a coal database or an operator: obtaining, via the one or more hardware processors, a first set of operating parameters of the power plant; obtaining, via the one or more hardware processors, a zone of operation, wherein the zone of operation is decided by at least one of the operator or taken from system settings of the power plant, wherein the zone of operation decides an objective function; optimizing, via the one or more hardware processors, the objective function to identify an optimum set of coals and their coal blending ratio, for the obtained zone of operation based on the obtained set of properties and the first set of operating parameters using a first predictive model, wherein the first predictive model is at least one or more of a physics based fundamental model, a knowledge based model and a data-driven model; implementing, the via one or more hardware processors, the identified coals along with their optimum coal blending ratio in the system settings of the power plant; receiving, the via one or more hardware processors, a second set of operating parameters; identifying, via the one or more hardware processors, an optimum operation setting for the power plant based on the second set of parameters using a second predictive model and the identified optimum set of coals, wherein the second predictive model is at least one or more of a physics based fundamental model, a knowledge based model and a data-driven model; and implementing, via the one or more hardware processors, the identified optimum operation settings in the system settings of the power plant to optimize the operation of the power plant. obtaining, via one or more hardware processors, information about types of coal present at one or more locations; obtaining, via the one or more hardware processors, a set of properties of the types of coal from at least one of a coal database or an operator: obtaining, via the one or more hardware processors, a first set of operating parameters of the power plant; obtaining, via the one or more hardware processors, a zone of operation, wherein the zone of operation is decided by at least one of the operator or taken from system settings of the power plant, wherein the zone of operation decides an objective function; optimizing, via the one or more hardware processors, the objective function to identify an optimum set of coals and their coal blending ratio, for the obtained zone of operation based on the obtained set of properties and the first set of operating parameters using a first predictive model, wherein the first predictive model is at least one or more of a physics based fundamental model, a knowledge based model and a data-driven model; implementing, the via one or more hardware processors, the identified coals along with their optimum coal blending ratio in the system settings of the power plant; receiving, the via one or more hardware processors, a second set of operating parameters; identifying, via the one or more hardware processors, an optimum operation setting for the power plant based on the second set of parameters using a second predictive model and the identified optimum set of coals, wherein the second predictive model is at least one or more of a physics based fundamental model, a knowledge based model and a data-driven model; and implementing, via the one or more hardware processors, the identified optimum operation settings in the system settings of the power plant to optimize the operation of the power plant.