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Location of the static VAR compensator (SVC) and other types of shunt compensation devices is important for the enhancement of the voltage stability for practical power systems. With the theory of the normal forms of diffeomorphism, this paper proposes a new method to solve this problem. The proposed method makes use of the nonlinear participation factors, in which the nonlinearity of power systems can be taken into consideration. As a result, the most suitable location where the SVC should be used in power system can be determined, even for the cases in which the system is characterized with strong nonlinearity. In order to show the effectiveness of the proposed method, the New England 39-bus power system with SVC is used as an example. Calculation results show that with the SVC located at the place where the proposed method determined, the voltage stability is considerably enhanced. The steady-state voltage stability index and the time domain simulation results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The electricity industry is significantly affected by weather conditions both in terms of the operation of the network infrastructure and electricity consumption. Following privatization and deregulation, the electricity industry in the U.K. has become fragmented and central planning has largely disappeared. In order to maximize profits, the margin of supply has decreased and the network is being run closer to capacity in certain areas. Careful planning is required to manage future electricity demand within the framework of this leaner electricity network. There is evidence that the climate in the U.K. is changing with a possible 3°C average annual temperature increase by 2080. This paper investigates the impact of weather variables on monthly electricity demand in England and Wales. A multiple regression model is developed to forecast monthly electricity demand based on weather variables, gross domestic product, and population growth. The average mean absolute percentage error (MAPE) for the worst model is approximately 2.60% in fitting the monthly electricity demand from 1989 to 1995 and approximately 2.69% in the forecasting over the period 1996 to 2003. This error may reflect the nonlinear dependence of demand on temperature at the hot and cold temperature extremes; however, the inclusion of degree days, enthalpy latent days, and relative humidity in the model improves the demand forecast during the summer months. [ABSTRACT FROM AUTHOR]

This paper discusses an alternative to the ex post pricing model currently under development within ISO New England's (ISO NE) ancillary service market. Since ISO NE's real-time ancillary service market co-optimizes both energy and reserve products, ex post pricing is needed for both energy and reserve. A co-optimization approach for ex post pricing requires defining complex pricing rules and implementing heuristics to ensure consistent binding constraints with the ex ante dispatch. In order to avoid complexity and uncertainty of required heuristics, a new ex post pricing schema is proposed to calculate the ex post energy and reserve prices in a decoupled way while recognizing the coupling effect of energy and reserve. In the proposed approach, ex post energy prices are first computed by incorporating the ex ante marginal opportunity cost of reserve in the energy offer; the ex post reserve prices are then calculated by considering the ex post marginal opportunity cost of energy. This approach simplifies the implementation of ex post pricing rules in the ISO NE market. Numerical examples are presented to further demonstrate the validity of this approach. [ABSTRACT FROM AUTHOR]