Abstract State estimation is an important tool for system operators. The state of the power system is defined by the voltage magnitudes and phase angles at all buses. The state estimator (SE) determines this state based on a set of redundant measurements. The classic steady-state estimator is widely used. Attempts to formulate a dynamic-state estimator have also been made. To speed up the computation, some authors have tried to formulate a distributed SE which can be computed using parallel processing. Recently it became possible to do very accurate synchronized phasor measurements. Now state-of-the-art SE are implemented using data from these measurements. This paper gives an overview of the power system state estimation theory and practise. It is intended to serve as starting point for developing new state estimation techniques.@en

Diesel generators in small electricity grids are mostly not used in a very efficient way. The reason for this is twofold. First of all, the efficiency of a diesel generator is dependent on the ratio determined by the average power divided by the peak power of the generator. The smaller this ratio is, the lower the efficiency. Furthermore, some loads can regenerate energy. In small grids, this energy is mostly not needed elsewhere and should be dissipated. A solution solving both problems previously mentioned is using an energy storage device in the system. This storage can be used for peak shaving and storing regenerated energy. This paper focuses on a generator-set with energy storage. Six different power management strategies are discussed. Calculation of the costs shows that adding an energy storage device lowers the cost for all methods. Verification with simulation and experiments has been carried out.@en

Diesel generators in small electricity grids are mostly not used in a very efficient way. The reason for this is twofold. First of all the efficiency of a diesel generator is dependent on the ratio between the average power and the peak power of the generator. The smaller this ratio, the lower the efficiency. Furthermore some loads can regenerate energy. In small grids this energy is mostly not needed elsewhere and should be dissipated. A solution solving both above mentioned problems is using an energy storage device in the system. This storage can be used for peak shaving and storing regenerated energy. In this paper for six defined power management strategies, simulation models are developed. These strategies are: Only Generator, Peak Power Shaving, Dynamic Solution, Max On or Off, Average Power and Only Storage. In this paper a system based on a Li-ion HP battery is under consideration. Two models for the a Li-ion HP battery are compared: the simple model and the Thévenin model. It is shown that the Thévenin battery model gives the best results. Simulation results for all power management strategies are given. From this it can be concluded that the model for the Only Generator method is too simple if the voltage is under concern. For the other methods the simulation models seems to be appropriate. One problem can be observed when scaled models are used: the internal resistance of a battery doesn¿t scale with the same factor as the energy content. So the observations made are only an indication if a scaled model is used. From the simulations it is concluded that the power management strategies are correct.@en

Diesel generators in small electricity grids are not always used in an efficient way. The reason for this is twofold. First of all the efficiency of a diesel generator is dependent on the ratio between the average power and the peak power of the generator. The smaller this ratio, the lower the efficiency. Furthermore some loads can regenerate energy. In small grids this energy is mostly not needed elsewhere and should be dissipated. A solution solving both above mentioned problems is using an energy storage device in the system. This storage can be used for peak shaving and storing regenerated energy. This paper focuses on the costs of a generator-set with energy storage. This calculation is done for the general case and for six different power management strategies: Only Generator, Peak Power Shaving, Dynamic Solution, Max On or Off, Average Power and Only Storage. Calculation of the costs shows that adding an energy storage device lowers the cost for all methods. Calculations show that the Max On or Off method is the best choice.@en

Many decentralized generation technologies are mature today. For the Dutch power system it is expected that in 2020 Decentralized Generators (DGs) form a major (about 35 %) part of the total production capacity. This expectation is true all over the world. A large share of DG will influence the voltage stability of the system. The objective of this paper is to give a clear overview of the consequences of DGs for typical voltage stability problems encountered at transmission level. No particular DG will be studied, but an overview will be given what happens if a DG is based on a certain generator type. Based on theoretical expectations the simulations done in this study show for a typical transmission system that adding DG is generally beneficial for the voltage stability. Mainly three factors are important for the consequence DG has on voltage stability: active power support, reactive power consumption, and voltage support. Taking these benefits into account requires intelligent control of the DGs.@en

Diesel generators in small electricity grids are mostly not used in a very efficient way. The reason for this is twofold. First of all the efficiency of a diesel generator is dependent on the ratio between the average power and the peak power of the generator. The smaller this ratio, the lower the efficiency. Furthermore some loads can regenerate energy. In small grids this energy is mostly not needed elsewhere and should be dissipated. A solution solving both problems mentioned above, is using an energy storage device in the system. This storage can be used for peak shaving and storing regenerated energy. This paper suggests six different power management strategies: Only Generator, Peak Power Shaving, Dynamic Solution, Max On or Off, Average Power and Only Storage. The implications of these algorithms are given for a typical case study on a crane used in the harbor. Calculations show that the Max On or Off, Average Power and Only Storage methods save the most energy. Calculation of the costs shows that adding an energy storage device lowers the cost for all methods.@en