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Energization overvoltages are among the severest overvoltages stressing insulations of EHV power system components. Since these overvoltages have a statistical nature, the insulation level should be determined with the use of a statistical approach by which the distribution of overvoltages is calculated. Literature has properly studied the distribution of energization overvoltages in purely overhead line (OHL) or cable systems, but such a study is not available for hybrid systems consisting of both OHLs and cables. It is expected that the overvoltage distributions change substantially when both OHLs and cables are used in a transmission line. This paper tackles this issue by analyzing the overvoltage distributions due to the energization of a 380 kV hybrid OHL-cable circuit, in which the cable length is variable. The study includes various sensitivity analyses to find out the impact of system parameters and topology on overvoltages. By the statistical analysis, it has been discovered that energization overvoltages of a hybrid OHL–cable circuit are higher than those of a fully-cable circuit and very likely lower than those of a fully-OHL circuit with the same transmission lengths.

Current and future developments in the power system industry demand fast power flow solvers for larger power flow problems. The established methods are no longer viable for such problems, as they are not scalable in the problem size. In this paper, the use of Newton-Krylov power flow methods is proposed, and a multitude of preconditioning techniques for such methods are discussed and compared. It is shown that incomplete factorizations can perform very well as preconditioner, resulting in a solver that scales in the problem size. It is further shown that using a preconditioned inner-outer Krylov method has no significant advantage over applying the preconditioner directly to the outer iterations. Finally, algebraic multigrid is demonstrated as a preconditioner for Newton-Krylov power flow and argued to be the method of choice in some scenarios.

Service interruptions have a significant impact on society and therefore the main objective of power system planning and operation is to ensure that they do not happen. Because voltage instability is one of the dynamic phenomena that may result in a system-wide blackout, this type of stability problem has been an important research topic for many years. Grid developments, like the increase of Renewable and Distributed Generation (RDG) and the impact of deregulation, in combination with the steadily increasing electricity demand, will have its impact on the vulnerability of the power system to voltage stability problems. On the other hand, developments in power system monitoring and control such as the use of accurate Phasor Measurement Units and the development of Smart Grid control concepts, introduce new possibilities for voltage instability prevention. In this work the impact of having a large share of RDG capacity on voltage stability is investigated and a new Hierarchical Agent-Based Voltage Instability Prevention (HABVIP) system for online voltage instability emergency control is proposed. The control philosophy uses the maximum loadability index to determine the amount of active and reactive power load relief necessary to restore stability. The intelligence for this control is provided by agents located in the substations: the substation agents. The load relief is obtained by: increase of local generation, virtual load shedding via adjusting the load tap changers set point, intelligent load control and increasing the reactive power output of Static Var Compensators. The control of the actuators is provided by agents located in the actuators: the actor agents. Verification of the system is done by off-line simulations and by building a real-time hardware in the loop demonstration model.

In this paper we investigate how the detailed modelling of uncertainty impacts the assessment of the power system security. We propose a formulation for the inclusion of uncertainty in power system operational security assessment. The model proposed consists of a Monte-Carlo (MC) framework which allows to capture the complex stochasticity of the system inputs using the copula theory for the sampling of the system infeeds, in combination with AC power flow computations for a detailed assessment of the system operation. Taking into account the infeed forecast uncertainty (loads and renewable generation), and the set of possible contingencies, the MC formulation allows the detailed evaluation of the network operation by computing the system risk in terms of Lost Load. Moreover, the model computes the probability of cascading events, pointing out which remedial actions are to be expected and the associated amount of Lost Load. The proposed model is applied to the IEEE 118 bus test system. To highlight how uncertainty modelling impacts the results, we investigate how correlated infeeds affect the severity of estimated system stress. Results show that applying simplifications such as assumptions of independence or approaches that rely on DC approximations could lead to an underestimation of the system risk.

The deployment of EVs leads to a shift of the demand from transport to the power sector. This paper shows that in order to perform a realistic evaluation of the EVs integration impacts on a power system, the future developments in the increase of interconnection capacities should be taken into account. For this, three different charging scenarios are developed and tested using a North-Western Europe system model, together with a unit commitment and economic dispatch tool. EVs load time series are generated for each scenario by a stochastic model which is based on real commuting patterns of the Dutch population. The results indicate that EVs load is mainly supplied by conventional generation: gas, coal and nuclear. It is also noted that EVs lead to a very low increase in wind power utilization and even to a substitution of hydro generation.

This paper proposes a multi-TSO collaborative network expansion methodology of for the congestion alleviation by placing new transmission lines to different control areas in the system separately, meanwhile maintaining the security standard of the grid as a whole. Optimal power flow, using Lagrangian multipliers and locational marginal price as optimisation variables is applied. The method provides the optimal location, type, and the number of extra necessary transmission lines for the optimal network structure under the generation and load scenario that the network may encounter in the future. A test case with the New England 39 bus model is presented in this paper for the validity and effectiveness of the proposed method.

In the power system of the future, reliability will play an important role. This reliability is influenced by different developments like the increase in electricity consumption and the use of renewable and distributed generation. It is important to have a good insight into the reliability performance of the system. With probabilistic methods, the reliability of the power system can be analyzed and decisions can be made to maintain the high reliability level that we demand. This paper gives an overview of the different developments in power systems and describes how these developments influence the reliability of the future power system. The possibilities to implement these developments into the probabilistic reliability analysis in network planning and operational planning are discussed. By use of an example, the possibilities and challenges of probabilistic methods in operational planning are illustrated.

Distributed generation (DG) plays an increasing role in the power system. Due to their local character they could in principle be used in emergency situations to prevent a blackout. Classically, however, DGs are uncontrollable. In this paper methods are proposed to use DG as actuator in the Hierarchical Agent-Based Voltage Instability Prevention (HABVIP) system. The control strategy in this system is to obtain a certain amount of load relief in the problem area. Three types of DG are considered: micro-CHPs, greenhouse CHPs and Wind Turbines (WT). For the micro-CHP and greenhouse CHP the output power can be controlled within limits. These limits are determined by the maximum temperature settings. For the micro-CHP a Virtual Power Plant (VPP) scheme is proposed to obtain continuous power output of a group of micro-CHPs that work under thermostatic control. For the WT the output power cannot be controlled. For that reason a method is proposed to use the predicted power generation of this turbine to anticipate for an increase or decrease. The proposed methods are verified by simulations which show that the methods work properly.

In this paper a strategy is introduced for emergency control of Load Tap Changers (LTCs) to prevent the system from voltage collapse. The method is based on the fact that the power consumed by constant current and constant impedance loads can be lowered by decreasing the secondary voltage of the LTC. This idea is used to develop a method of indirect load shedding. This method calculates, based on a model of the connected load, the voltage set-point of the secondary side of the LTC for a given amount of load that needs to be shed. With simulations it is demonstrated that a LTC can be applied for load relief using the proposed method. A sensitivity analysis is done to study the effect of an error in the load model parameters. Furthermore it is proven that the method can be used to prevent the power system from a typical voltage instability. Finally a proposal for the implementation in a smart grid multi-agent system is presented.

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.

In the Dutch power system the power consumption is increasing while the transmission and distribution system capacity is not increasing at the same rate. Furthermore due to the increasing amount of decentralized generation, by for example micro-CHP units and wind turbines, the power flows in the power system are changing. In weak sub-transmission and distribution grids an increase in the number of voltage stability problems is expected. However: with the large share of decentralized generation we have the solution for voltage problems already there. In this paper we propose a new Hierarchical Agent Based Instability Protection System. In this paper the idea is described and a theoretical justification is given, in a later stage of the project we will verify the system with the Real-time Digital Simulator and external controls.

The fast growing application of sustainable energy sources imposes major structural changes on the current electric power systems. One of these structural changes is to make use of large variable speed wind turbines within the conventional electrical power networks. The installation of these wind turbines has, indeed, indispensable impacts on the dynamic behavior of the existing electric power systems. Thus, it is important to gain a rather generalized overview on how these wind turbines, which mostly use Doubly Fed Induction Generators (DFIGs), affect the system stability. This paper performs an analytical analysis for the indication of small disturbance rotor angle stability in the power systems equipped with variable speed wind turbines using DFIGs. Also, in order to consider the stochastic characteristic of the sustainable energy sources, the paper applies an iterative-stochastic method to analyze the small disturbance angle stability. The suggested iterative-stochastic methodology is numerically verified, within this paper, by getting applied to an electric power test system.

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 incorporation of wind power generation to the power system leads to an increase in the variability of the system power flows. The assessment of this variability is necessary for the planning of the necessary system reinforcements. For the assessment of this variability, the uncertainty in the system inputs should be modeled, comprising of the time-dependent stochasticity of the system loads and the correlated wind resources. In this contribution, a unified Monte-Carlo simulation methodology is presented that addresses both issues. The application of the method for the analysis of the wind power integration in the New England test system is presented.