In North American utilities, control area performance of interconnected power systems is assessed by the reliability standards imposed by the North American Electric Reliability Corporation (NERC). NERC standards on control area performance define two indices known as Control Performance Standards 1 and 2 (CPS1 and CPS2) to evaluate control area performance in normal interconnected power system operation. Out of the two indices, CPS1 evaluates the performance of a control area with respect to control of interconnection frequency and tie-line power flows. This thesis proposes a novel method to approximately estimate CPS1 for a two area power system using the probability distribution of load change. The proposed method of estimating CPS1 is validated against the time domain simulation method using a simple two-area test system. In the validation process, it is shown that the proposed method could approximately forecast CPS1 within 5% accuracy. The forecasted CPS1 value could then be used by a control area to design its future control strategies to be in compliance with NERC criteria at the minimum cost. These control actions include, but not limited to tuning governors, reducing non-confirming loads, ensuring adequate operating and spinning reserves etc.

In North American utilities, control area performance of interconnected power systems is assessed by the reliability standards imposed by the North American Electric Reliability Corporation (NERC). NERC standards on control area performance define two indices known as Control Performance Standards 1 and 2 (CPS1 and CPS2) to evaluate control area performance in normal interconnected power system operation. Out of the two indices, CPS1 evaluates the performance of a control area with respect to control of interconnection frequency and tie-line power flows. This thesis proposes a novel method to approximately estimate CPS1 for a two area power system using the probability distribution of load change. The proposed method of estimating CPS1 is validated against the time domain simulation method using a simple two-area test system. In the validation process, it is shown that the proposed method could approximately forecast CPS1 within 5% accuracy. The forecasted CPS1 value could then be used by a control area to design its future control strategies to be in compliance with NERC criteria at the minimum cost. These control actions include, but not limited to tuning governors, reducing non-confirming loads, ensuring adequate operating and spinning reserves etc.

A novel probabilistic method has been developed for modelling the operation of energy storage in electricity systems with significant amounts of wind and solar powered generation. This method is based on a spectral analysis of the variations of wind speed and solar irradiance together with profiles of electrical demand. The method has been embodied in two Matlab computer programs: Wind power only: This program models wind power on any time scale from seconds to years, with limited modelling of demand profiles. This program is only capable of modelling stand-alone systems, or systems in which the electrical demand is replaced by a weak grid connection with limited export capacity. 24-hours: This program models wind power, solar PV power and electrical demand, including seasonal and diurnal effects of each. However, this program only models store cycle times (variations within a time scale) of 24 hours. This program is capable of modelling local electrical demand at the same time as a grid connection with import or export capacity and a backup generator. Each of these programs has been validated by comparing its results with those from a time step program, making four Matlab programs in total. All four programs calculate the power flows to and from the store, satisfied demand, unsatisfied demand and curtailed power. The programs also predict the fractions of time that the store spends full, empty, filling or emptying. The results obtained are promising. Probabilistic program results agree well with time step results over a wide range of input data and time scales. The probabilistic method needs further refinement, but can be used to perform initial modelling and feasibility studies for renewable energy systems. The probabilistic method has the advantage that the required input data is less, and the computer run time is reduced, compared to the time step method.

The Turkish TSO (TEIAS) has been leading a project that aims the synchronous interconnected operation of the Turkish Power System and the ENTSO-E CESA (former UCTE) System. For this purpose, this study concentrates on the specific problems related to the electromechanical systems of large size hydroelectric power plants regarding low frequency inter area oscillations, which are prone to occur once the interconnected operation is established. The expected frequency of inter area oscillations after interconnected operation is close to 0.15 Hz, which is in the frequency range of the speed governing structures of turbines, as explained in the first two sections of the thesis. In the third section, the nonlinear turbine governor model used throughout the study is explained. In the following part, the governor parameter tuning study with regard to the defined performance objectives is explained. Afterwards, the effect of the retuned governor settings of the sample hydroelectric power plants on a simple multi machine power system is shown. Following that, the system wide effect of removing the sources of negative damping, which are strongly dependent on the governor settings of the major hydroelectric power plants of the Turkish Power System, is shown. In the final part, conclusions are made on the operation of the hydroelectric power plants regarding the frequency stability of the system after synchronous interconnected operation of the Turkish Power System and the ENTSO-E CESA System.