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At present, one of the main issues in electric power networks is the reduction in conventional generation and its replacement by low inertia renewable energy generation. The balance between generation and demand has a direct impact on the system frequency and system inertia limits the frequency rate of change until compensation action can be undertaken. Traditionally generation managed frequency. In future, loads may be required to do more than just be able to be switched off during severe under frequency events. This thesis focuses on the development and practical implementation of the control structure of a smart adaptive load for network power-frequency support applications. The control structure developed makes use of advanced demand side management of fan loads (powered by AC drives) used in heating, ventilation, and air conditioning systems; where a change in power at rated load has little effect on their speed due to the cubic relationship between speed and power. The AC drive implemented in this thesis is based on an induction motor and a two level voltage source converter. To achieve the smart adaptive load functionality, first a power-frequency multi-slope droop control structure (feedforward control) is developed; relating the frequency limits imposed by the network supplier and the fan power-speed profile (Chapter 2, Fig 2.19). Secondly, this control structure is combined with the control developed, in Chapter 3, for the AC drive powering the fan load. The full development of the control structure of the AC drive, its tuning process and its practical implementation is given; an equation is developed to find suitable tuning parameters for the speed control of the nonlinear load (fan load), i.e. Eq. (3.59).The analysis and simulation results provided in Chapter 4 conclude that a fast control of the active power drawn by the AC drive is possible by controlling the electromagnetic torque (hence current) of the induction motor without disturbing the fan load overly. To achieve this, changes between closed loop speed control and open loop torque control (power control) are performed when needed. Two main issues were addressed before the hardware implementation of the smart adaptive load: the estimation of the network frequency under distorted voltage conditions, and the recovery period of the network frequency. In this thesis two slew rate limiters were implemented to deal with such situations. Other possible solutions are also outlined. Finally, experimental results in Chapter 5 support results given in Chapter 4. A full power-frequency response is achieved by the smart adaptive load within 3s.