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This thesis describes and computationally tests a method of using PMU data to generate an optimisation metric that accurately reflects the desirability of a given power system's operating conditions. The optimisation function takes into consideration the voltage profile across the network, reactive power flow, transmission losses and line loading. The optimisation function was investigated as a wide-area control variable for on load tap changing transformers and switched shunt capacitors. Networks whose control assets were optimised with this wide-area optimisation metric were found to be able to handle a greater load and distributed generation before acceptable operating conditions were infringed. The wide-area controlled networks, that were modelled in PSSE, were also found to have a consistently higher efficiency, a better voltage profile and to be more resilient against voltage instability. The initial testing of the optimisation method assumed complete observation of the network in question. The investigation continues to demonstrate how a regression method could be used to extrapolate the global optimisation metric from a limited number of PMU placements on the system. A parsimonious multivariate linear regression method is developed that suggests the best PMU placements and quantifies the degree of error that might result from the reduced visibility. The optimisation function is intended as a method of reducing a profusion of PMU data down to a single simple metric. The optimisation metric can be quickly interpreted by a network operator, its variation used to inform the operation of assets or the desirability of specific asset operation. The metric could easily be transported over legacy SCADA systems, given its small size and the lack of reliance on a reporting rate. The intention of this work is facilitate a power system that can operate more efficiently, handle more distributed generation and provide a better service.