Optimizing the Operation of Windfarms, Energy Storage and Flexible Loads in Modern Power Systems and Deregulated Electricity Market

The amount of wind energy in power systems is increasing at a significant rate. With this increased penetration, there are certain problems associated with the operation of windfarms which need careful attention. In the operations side, the wake effects of upstream wind turbines on downstream wind turbines can cause a reduction in the total generated power of a windfarm. On the market side, the fluctuation of real-time prices can make the operation of windfarms less profitable. Similarly, the intermittent nature of wind power prevents the windfarms from participating in the day-ahead and forward markets. On the system side, the volatile nature of wind speeds is also an obstacle for windfarms to provide frequency regulation to the system. In this thesis, we address these issues and optimize the operation of windfarms in power systems and deregulated electricity markets.;First, the total power generation in a windfarm is maximized by using yaw angle of wind turbines as a control variable. We extend the existing wake models to include the effects of yaw misalignment and wake deflection of wind turbines. A numerical study is performed to find the optimal values of induction factor and yaw misalignment angle of wind turbines in a single row of a windfarm for achieving the maximum total power with wake effects. The numerical study shows that the maximum power is achieved by keeping the induction factor close to 1/3 and only changing the yaw angle to deflect the wake. We then propose a Dynamic Programming Framework (DPF) to maximize the total power production of a windfarm using yaw angle as the control variable. We compare the windfarm efficiency achieved with our DPF with the efficiency values obtained through greedy control strategy and induction factor optimization. We also extend our expressions to a windfarm with multiple rows and columns of turbines and perform simulations on the 3x3 and 4x4 grid topologies. Our results show that the optimal induction factor for most turbines is quite close to 1/3 and yaw angle acts as the dominant optimization variable.;In the next part of this dissertation, a system comprising of a windfarm and energy storage operating in real-time electricity markets is studied. An Energy-balancing Threshold Price (ETP) policy is proposed to maximize the revenue of a windfarm with on-site storage. We propose and analyze a scheme for a windfarm to store or sell energy based on a threshold price. The threshold price is calculated based on long-term distributions of the electricity price and wind power generation processes, and is chosen so as to balance the energy flows in and out of the storage-equipped windfarm. It is also shown mathematically that the proposed policy is optimal in terms of the long-term revenue generated. Comparing it with the optimal policy that has knowledge of the future, we observe that the revenue obtained by the proposed ETP policy is approximately 90% of the maximum attainable revenue at a storage capacity of 10-15 times the power rating of the windfarm.;The intermittent nature of wind power is a hindrance to the efficient participation of windfarms in the day-ahead and forward electricity markets. In this regard, a flexible forward contract is proposed in this dissertation which allows the windfarms to enter into a forward contract with flexible load with an option to deviate from the contracted amount of power. Using such a flexible contract would allow the windfarms to supply more or less than the contracted amount of power in case of unexpected wind conditions or real-time prices. We also propose models for forecasting wind power and real-time electricity prices. The comparison between the proposed contracting framework and a simple fixed contract (currently existing in the market) for different levels of flexibility and load shows that there is a net gain in windfarm revenues, if the transaction price of the two contracts are set equal.;Lastly, we present and analyze distributed control schemes for frequency regulation in a smart grid using energy storage, wind generators, demand response and conventional generators while having no communication or data sharing between them. We also propose a novel control scheme for frequency support by energy storage in which the power output of energy storage changes proportionally with the reduction in its available energy. The application of the proposed control schemes indicates an improvement in system frequency characteristics, when there is a sudden net loss of generation.