Exhaustive Modal Analysis of Interconnected European Power System

Stress on the generation and transmission capability of the power system increased as the energy demand increases. Distributed generation (DG), which is usually placed near the load centre has the capability to meet these energy increment in demands. Hence, for making the power system highly durable and reliable, Distributed generations are interconnected with the existing power system. Based on the nature of the primary source of generation and the energy conversion technology these types of generation have important impacts on power system voltage stability. One of the most significant threats considered for a secure operation of the power system is voltage instability problem. Voltage collapse might occur in an interconnected power system due to voltage instability and thus lead to power blackouts. Hence in an interconnected power system it is essential to know the strength of the buses to monitor and improve the stability of the system. This paper focuses on voltage stability analysis of an interconnected distributed photovoltaic system with IEEE 30 bus system. The voltage stability of the system assessed by evaluating voltage stability indicators at each bus of interconnected power systems. Fast Voltage Stability Index value of each bus is evaluated under normal and critical load conditions. The index value helps to identify the weakest or the bus which is likely to get voltage collapse due to voltage instability problem in the interconnected system.

The FACTS device like TCPAR can be used to regulate the power flow in the tie-lines of interconnected power system. When TCPAR is equipped with power regulator and frequency-based stabiliser it can also significantly influence the power flow in the transient states occurring after power disturbances. In the case of simple interconnected power system, consisting of two power systems the control of TCPAR can force a good damping of both power swings and oscillations of local frequency. In the case of larger interconnected power system consisting of more than two power systems the influence of the control of TCPAR on damping can be more complicated. Strong damping of local frequency oscillations and power swings in one tie-line may cause larger oscillations in remote tie-lines and other systems. Hence, using devices like TCPAR as a tool for damping of power swings and frequency oscillations in a large interconnected power system must be justified by detailed analysis of power system dynamics.

As the EU's Emissions Trading Scheme has, up to date, had little impact on the reduction of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions in Europe, direct carbon taxes have been proposed. In this work, high spatial and temporal resolution optimal power flow simulations are conducted to assess the impact of carbon taxes on the inter-connected power system in central Europe. As both individual transmission lines and individual power plants are modeled, this work provides new insights into effects within the European power market. A carbon price of 40 €/tCO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> or more is shown to be necessary in 2030 to achieve the EU emissions targets. This tax burden is borne mainly by Poland and the Czech Republic, who lose more than 2bn € annually in power exports. Consumers in Switzerland face the highest increases in electricity prices, despite consuming very carbon-friendly electricity.

This paper addresses innovative nonlinear approaches for dynamic equivalencing of machines for interconnected power systems. In contrast to the existing approaches that consider only fixed equivalencing steps without taking into consideration the machine parameters, these approaches reformulate the classical conditions incorporating real electromechanical model parameters and behaviours of the machines in the dynamic equivalencing. These aspects enable the integration of modern and intelligent techniques, such as the pattern recognition algorithms, fuzzy concept as machine splitting factor and the system identification by dynamical artificial neural networks. The electromechanical-based approaches generate accurate robust, non-linear dynamic equivalents and thereby enhance significantly their consistency and practical application on network reliability, management and planning. Test of these approaches have been performed and evaluated in large-scale model of the European interconnected electric power system (UCTE/CENTREL) and 16 multi machine system

Conventional control techniques such as proportional integral (PI) control and proportional integral derivative (PID) control are widely used as the load frequency controller in power system control applications; however, the increase in complexity of the power system is degrading the performance of classical control. Therefore, in this paper a new control approach using fractional calculus has been proposed for the load frequency control problem of two-area hydro-thermal power system. The paper presents an interconnected hydro-thermal power system working under different operating conditions introduced in the form of various nonlinearities. Four case studies have been presented in this paper considering transient analysis with (i) different loading conditions, (ii) parameter variations, (iii) different nonlinearities (governor dead band nonlinearity, time delay and generation rate constraints), and (iv) superconducting magnetic energy storage (SMES) device. A tilt integral derivative (TID) control has been presented as a secondary controller to stabilize the frequency deviations occurring in the two-area power system with the above-mentioned different operating conditions. The parameters of TID controller have been optimized using a differential evolution algorithm which solves an optimization problem formulated using the integral of time-weighted absolute error (ITAE) performance index. In addition, a comparison of dynamic system response obtained using TID control and PID control has been presented, which focusses on the better performance of TID control over PID control in an interconnected power system.

In industry or any area increasing load is a vast problem for power generation plants due to increase in demand for power. So making balance between generation and demand is the operating principle of load frequency control (LFC). The reliable operation of a large interconnected power system necessarily requires an Automatic Generation Control (AGC). The objective of AGC is to regulate the power output of Generators within a specified area in response to change in the system frequency, tie line power or relation of the two to each other, so as to maintain the scheduled system frequency and power interchange in the other are within the prescribed limits. This paper presents the use of conventional PI controller and artificial intelligence to study the load frequency control of interconnected power system. In the proposed scheme, a control methodology is developed using conventional PI controller and Fuzzy Logic controller (FLC) for interconnected hydro-thermal power system. The control strategies guarantees that the steady state error of frequencies and inadvertent interchange of tie-lines power are maintained in a given tolerance limitations. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of Fuzzy controller and PI controller based approaches shows the superiority of proposed Fuzzy logic controller for step change in loading conditions. The simulation results also tabulated as a comparative performance in view of settling time and peak over shoot.

The analysis of low‐frequency inter‐area oscillations is of special concern in large weakly interconnected power systems. The ability of static VAr compensators (SVC) to contribute to damping depends strongly on the relative location of generation, load and the SVC. A comprehensive investigation of the use of static VAr compensators to aid damping of low‐frequency inter‐area oscillations in a real weakly interconnected large power system is presented. Based on modal analysis, efficient algorithms to compute voltage‐ and power‐oscillation flow for each mode of concern are developed. Controllability and observability measures are also used to assess the impact of dynamic voltage support on system damping as well as to identify optimal locations for SVC. The knowledge gained by these techniques allows to investigate the influence of existent SVC on overall system damping as well as to evaluate suitable alternatives to site new devices. Detailed time‐domain simulations are finally performed to check the validity of the knowledge gained and to assess the impact of dynamic voltage support on system transient behaviour.

Developing a global interconnected power system model

In the category of small signal stability problem, one of the major causes of unpredictability of power transfer in the inter-connected power system is due to low frequency oscillations (LFO). These oscillations in the inter-connected power system, affects the power transfer capability and thereby, needed to be suppressed. To damp the oscillation and protect the power system, power system stabilizers are used. In this study, a Kho-Kho optimization (KKO) based proportional integral derivative (PID) power system stabilizer is put forward which can suppress the LFO in the inter-connected power system. Optimization methods are widely being used to solve number of optimization problem. Therefore, in this work the specification of the stabilizer are calibrated using KKO technique by optimizing a objective function constructed using the Integral time square error (ITSE) of the speed deviation. To test the effectiveness of the designed optimal controller, a one machine infinite bus (OMIB) with IEEE type DC-1 exciter unit is also taken into consideration. The superiority of the proposed technique is examined by comparing the obtained results with some other existing techniques.

The power system economy and safety demand is likely to force more and more power systems to interconnect. But the power transfer capability in the tie-lines is largely limited by small signal instability. A technique for low frequency oscillation analysis of bulk interconnected power system by combining sparse eigenvalue analysis with Prony method is presented in this paper, which uses Prony analysis to provide approximation of the oscillation modes for initial shift points of the sparse eigenvalue analysis. Based on the result of the sparse eigenvalue analysis, the PSSs that are installed on selected generators to damping the inter-area low frequency oscillation modes; time-domain simulations and sensitivity analysis of the power flow in the tie-line verify their performances. The simulation results of a practical power system demonstrate its effectiveness

Frequency control in interconnected electrical power systems is nowadays realized using the networks' conventional thermal power plants. With the ongoing changes in power systems worldwide the share of these conventional power plants is decreasing while renewable resources such as wind power and photovoltaics are increasing their share continuously. Up to now a contribution of renewable sources to primary frequency control is not realized in interconnected power systems. This paper describes possibilities to support the frequency of power systems using wind turbines with enhanced active power functionalities such as primary frequency control and synthetic inertia. The effects of these functionalities are analyzed in the IEEE 39 bus system. Different simulations with an implementation of these functionalities in a doubly fed induction generator wind turbine model show promising results. The frequency behavior of a 50 % penetrated system with standard wind power plants shows unfavorable frequency behavior compared to the original system, whereas a system with additional frequency supporting functionalities by wind power plants improves the frequency behavior significantly.

This paper investigates sector coupling between the central power system and local energy communities, including heat supply for buildings and charging of electric vehicles. We propose a stochastic linear programming framework to study long-term investments under uncertain short-term operations of nationally aggregated assets. We apply the model to a case study assuming European power sector decarbonization towards 2060 according to a 1.5 degree scenario, and we investigate the impact of coupling building heat systems and electric vehicle charging in Norway with the European power market. The case study focuses on the role of Norway in a European perspective because: (1) Norwegian electricity production is mainly based on flexible and renewable hydropower, (2) Norwegian building heating systems are currently mainly electric, and (3) Norway is already introducing electric vehicles at large. We focus on the European power market to test our hypothesis that it is more cost-efficient to decarbonize when the central power system is coordinated with building heat systems and electric vehicle charging. For Europe as a whole, results show that the average European electricity cost reduces by 3% and transmission expansion decreases by 0.4% when Norwegian heat systems are developed in coordination with the European power system. The average Norwegian electricity cost decreases by 19%. The strategy includes supplying up to 20% of Norwegian buildings with district heating fueled by waste and biomass, and the remaining electric heating supply is dominated by heat pumps.

Renewable electricity is a key enabling step in the decarbonization of energy. Europe is at the forefront of renewable deployment and this has dramatically increased the weather sensitivity of the continent's power systems. Despite the importance of weather to energy systems, and widespread interest from both academia and industry, the meteorological drivers of European power systems remain difficult to identify and are poorly understood. The present study presents a new and generally applicable approach, targeted circulation types (TCTs). In contrast to standard meteorological weather‐regime or circulation‐typing schemes, TCTs convolve the weather sensitivity of an impacted system of interest (in this case, the electricity system) with the intrinsic structures of the atmospheric circulation to identify its meteorological drivers. A new 38 year reconstruction of daily electricity demand and renewable supply across Europe is used to identify the winter large‐scale circulation patterns of most interest to the European electricity grid. TCTs provide greater explanatory power for power system variability and extremes compared with standard meteorological typing. Two new pairs of atmospheric patterns are highlighted, both of which have marked and extensive impacts on the European power system. The first pair resembles the meridional surface pressure dipole of the North Atlantic Oscillation (NAO), but shifted eastward into Europe and noticeably strengthened, while the second pair is weaker and corresponds to surface pressure anomalies over Central Southern and Eastern Europe. While these gross qualitative patterns are robust features of the present European power systems, the detailed circulation structures are strongly affected by the amount and location of renewables installed.

A new cyber-security approach for load frequency control of hybrid interconnected renewable power systems

In order to accomplish the reliable planning and operation of large interconnected power systems with high penetration of renewables, knowledge of the impacts on individual transmission lines and power plants within the system is required. This may be accomplished using high-resolution optimal power flow simulations with which different scenarios can be assessed. This paper presents detailed numerical weather prediction models that can be used for accurate predictions of solar and wind generated electricity. Furthermore a high-resolution power demand model that accounts for the spatial and temporal variations of different sectors is presented. The models are demonstrated in the case of one-year hourly resolution simulation of the central European power system.