Operating reserve adequacy evaluation using uncertainties of wind power forecast

Spacial coordination between data centers and power system considering uncertainties of both source and load sides

Like conventional power plants, wind power plants must provide the power quality required to ensure the stability & reliability of the power system. Increasing amount of wind turbine are connected to electrical power system in order to mitigate the negative environmental consequence of conventional electricity generation. While connecting wind turbine to grid it is important to understand source of disturbance that affect the power quality. In general voltage & frequency must be kept as stable as possible. This stability can be obtained by using FACTS devices. Recently voltage-source or current-source inverter based various FACTS devices have been used for flexible power flow control, secure loading and damping of power system oscillation. Some of those are used also to improve transient & dynamic stability of wind power generation system (WPGS). In this paper, we propose the static reactive compensator (STATCOM) based on voltage source converter (VSC) PWM technique to stabilize grid connected squirrel cage wind generator system. A simple control strategy of STATCOM is adopted where only measurement of rms voltage at the wind generator terminal is needed, there is no need of reactive power measurement. Fuzzy logic controller is used as the control a methodology of STATCOM, rather than conventional PI controller. The voltage sag and swell improvement of WPGS is compared with both fuzzy and PI controller. Moreover, the steady state capacitor value used with induction generator reduced by certain percentage when STATCOM is used with WPGS.

In this study, a grid-connected hybrid system composed of a solar and wind power generation system is modelled and analyzed in Matlab/Simulink. In addition, the quality of power generated by the hybrid power generation system is improved by using Fuzzy Logic (FL) and Proportional-Integral (PI) controllers. Measurements of the frequency, voltage, power and harmonics of the system and the grid are evaluated. In addition, the voltage and frequency fluctuation times prior to synchronization between the hybrid generation system and the grid are analyzed. The voltage rises that occur on the grid while the system is idling have been checked. After synchronization, the voltage, power, frequency and phase angle values measured at the load and at the grid in the hybrid system were observed individually. According to the measured values obtained as a result of the simulation study, the performance of the hybrid power generation system is analyzed.

This work presents the analysis and performance of connecting two wind power generation systems with the energy storage at the dc side. Energy storage is desirable to be installed to keep constant output from the wind power generation system. The DC connection of two wind power generation system helps to exchange power between the two systems and can suppress the disturbance of the output power to the utility systems longer than the stand alone system. The performance of connecting two wind generation systems with the energy storage at the dc side has been investigated by using the simulation. The wind power generation system is modeled and simulated by MATLAB/Simulink and the effectiveness of the dc connection of two systems is presented. This effect is easily achieved and implemented without any additional control. The controller measures only the common dc side capacitor voltage of the local system. MATLAB/Simulink simulation verifies the better performance in a certain situation.

— In a restructured power system, Ancillary services (AS) are required to balance load generation mismatches and to meet unforeseen contingencies. Operating Reserve is a major part of AS which is highly uncertain to forecast, mainly due to unpredictability of customer needs, over or under production of Energy and unpredictability in the integration of renewable energy sources. In this work wind integration is considered as a factor to forecast operating reserve. Increase of wind integration into power system, needs larger quantities of operating reserve. This demands an increase in the cost of generation and emissions. Forecasting the Operating Reserve Ancillary Service helps the system operators (SO) to plan scheduling of generators in advance and also in better bidding environment. Forecasting tools like feed-forward networks, Time series models were used to forecast load and Electricity price in the past. In this paper a hybrid method consisting of Support Vector Machines (SVM) and Fuzzy Interface System (FIS) is used to forecast Operating Reserve in Day-ahead market. Case studies using CAISO and ERCOT ISOs are presented. The SVM-FIS method is found to be better forecasting tool to predict the operating reserve Ancillary Service.

Nowadays voltage instability is a major concern for the secure operation of the electrical power systems. Understanding the effects of wind generators on power system dynamics and stability is crucial given the increasing levels of wind power generation in power systems around the world. This paper shows the dynamic voltage stability analysis with and without renewable energy resource under various operating conditions. The Kundur-10 bus system is being used for the purpose of analysis in the paper. The results show that with different load levels the voltage drops initially and then restores to reference value after the on-load tap changer actives. It has been shown with inclusion of DFIG wind generator improves the voltage profile. The voltage instability effects have been observed by considering different load levels and line outages.

Increasing levels of wind-turbine generation in modern power systems is initiating a need for accurate wind-generation transient stability models. Because many wind generators are often grouped together in wind parks, equivalence modeling of several wind generators is especially critical. In this paper, a reduced-order dynamic fixed-speed wind-generator model appropriate for transient stability simulation is presented. The model is derived using a model reduction technique of a high-order finite-element model. Then, an equivalencing approach is presented that demonstrates how several wind generators in a wind park can be combined into a single reduced-order model. Simulation cases are presented to demonstrate several unique properties of a power system containing wind generators. The results in this paper focus on horizontal-axis turbines using an induction machine directly connected to the grid as the generator.

Operating reserves serve as efficient tools to respond to the sudden outage of power system components caused by either natural events or intentional attacks. Contrary to the natural threats, the intentional attacks exhibit no stochastic behavior and are launched to inflict as much damage as possible to system. Moreover, these attacks are strongly influenced by the measures taken by the system operator. As a consequence, the probabilistic methods of operating reserve procurement and allocation do not prove to be efficient to confront the intelligent attacks. In this paper, the interaction between the system operator as the defender and the intelligent attacker is investigated within a linear two-person zero-sum game model. In this model, the system is scheduled and the operating reserves are allocated and deployed in a limited number of time intervals in such a way that the system incurs the least cost for the worst-case attack. The efficacy of the proposed method is examined by conducting case studies of single- and multiple-target attacks on two test systems. The results indicate that the solutions obtained by the proposed method can result in a considerable reduction in the system costs in comparison to those obtained when the system is scheduled by probabilistic methods and an intelligent attack is launched.

The growing share of electricity generation from renewable energy creates difficulties in maintaining the balance of generation and demand. This is mainly due to uncertainties caused by prediction errors in renewable generation. In order to maintain power system security, the participation of demand side response to the balancing services such as operating reserve is critical. In this paper, the capability of smart appliances to act as operating reserves for the system operator is investigated. The smart appliances considered are washing machines, dish washers and tumble dryers equipped with communication modules. A novel framework is introduced which enables system operators to access demand response from smart appliances in a timeframe suitable for operating reserves. A mathematical model is developed to simulate appliances with multiple discrete power phases. The delay and interruption of appliances cycles are considered in the model. A multiple time-step simulation is introduced that assesses the load reduction from a number of households as a response to a reserve instruction which is modelled as a price increase with a short notification period. The results are used to estimate the available demand response from Great Britain (GB) households at any moment of the day. With a 20% penetration of smart appliances, the demand response can provide up to 54% of the operating reserve requirements of the GB power system depending on the time of day.

In this paper, permanent magnet wind generator with full power converter is investigated in weak grid systems, where the dc-link voltage needs to be controlled from the generator side instead of grid side. When wind power takes a large portion of grid power, it needs to help grid to regulate the voltage and frequency. To achieve this, a variable step search algorithm based on the derivation of the electro-mechanical dynamic model describing the wind turbine is proposed, which enables the wind generator output power to match the load power, thus keeping the dc-link voltage regulated. Based on the non-linearity and different slopes of wind power curve, the controller is designed specifically for different sectors. A back-EMF observer based sensor-less generator control is adopted here to regulate the generator speed. Simulation is built up with a 10 kW wind power generator system and a reduced-scale 1.5 kW system experiment is also carried out in the condition of load power step change and wind speed change. Both simulation and experimental results validate the effectiveness of the proposed control scheme, where the dc-link voltage can be kept stable by adjusting the wind generator speed.

Ahstract- With the increase in fossil fuel burning and shortage of these power sources, power systems are shifting to renewable energy sources such as photovoltaic and wind power generation systems, and energy storage systems. Energy storage systems have more advantages than other power sources due to their fast response to power excess and shortage situations, controllability, adaptability, environment friendliness, and a better solution for global warming. This paper provides a case study for the optimal sizes of energy storage systems, power generators, and loads considering their cost under power and energy balance constraints. The objective of the case study is to check the solution for both power and energy balance constraints. Under these two constraints, the cost of energy storage, power generators, and loads is optimized. Finally, it is analyzed that under different analytical solutions the cost coefficients are effective to find the suitable size of generators, storage, and consumers while keeping the power balance.

To alleviate the impacts of stochastic wind generation on stability performance, this paper proposes a novel control design method for coordination and synthesis of damping controllers for conventional synchronous generators (SG) and double fed induction generators (DFIG)-based wind generation in multi-machine power systems. A probabilistic model of wind generation under Weibull distribution of wind speed is first introduced. Based on this model, an extended probabilistic small signal stability analysis (SSSA) incorporating wind power generation is proposed for handling probability density function (PDF) of its power output. The optimization problem for tuning of damping controllers is then formulated, considering the cumulative distribution function (CDF) of the real part and damping ratio of eigenvalues obtained by the proposed probabilistic SSSA as stability constraints. Particle swarm optimization (PSO) is used to solve the optimization problem and to determine parameters of damping controllers. The effectiveness of the proposed method is demonstrated on the modified New England power system with multi-wind farms through probabilistic SSSA and transient stability analysis, and it is compared with conventional deterministic methods. Accuracy of the proposed probabilistic SSSA is also validated by Monte Carlo simulations (MCS).

The growing integration of renewable energy in power systems demands for adequate planning of generation systems not only to meet long-term capacity requirements hut also to cope with sudden capacity shortages that can occur during system operation. As a matter of fact, system operators must schedule an adequate amount of operational reserve to avoid capacity deficits which can be caused by, for instance, overestimating the wind power that will be available. The framework proposed for the long-term assessment of operational reserve relies on the Nave forecasting method to produce wind power forecasts for the next hour. This forecasting model is simple and widely used to obtain short-term forecasts. However, it has been shown that regression models, such as the Autoregressive Integrated Moving Average (ARIMA) model, can outperform the Naive model even for forecasting horizons of up to 1 hour. This paper investigates the differences in the risk indices obtained for the long-term operational reserve when using the Naive and the ARIMA forecasting models. The objective is to assess the impact of the forecasting error in the long-term operational reserve risk indices. Experiments using the Sequential Monte Carlo Simulation (SMCS) method were carried out on a modified version of the IEEE RTS 79 test system that includes wind and hydro power variability. A sensitivity analysis was also performed taking into account several wind power integration scenarios and two different merit orders for scheduling generating units.

In this paper, a battery-supported hybrid wind-solar energy generation system with switching power flow control is presented to supply stable electrical power to two laboratories at the Electric & Electronic Engineering Department. For this purpose, 600W 3-phase permanent magnet synchronous generator (PMSG) based on the wind power generation system (WPGS) and the solar power generation system (SPGS) consisting of 190W 3 pieces mono crystal solar panel were combined to build a 1170W hybrid wind-solar power generation system (HWSPGS). T he solar and wind power generation systems were used as the main energy sources while 100 Ah 12V 6 pieces gel jeep cycle accumulator groups were used as the energy storage device to ensure continuity of energy. Also d ynamic modeling and switching power flow control of the battery supported the HWSPGS were performed using Matlab/Simulink in this study. D etermining the switching positions of the charge control unit according to loading and battery charge situations of the HWSPGS, power flow control between the generation unit and consumer was made in planned manner. When the curves of electrical magnitudes obtained from simulation results were examined, it was determined that no big difference existed in electrical and mechanical magnitudes in parallel to dynamic behavior of the installed hybrid power generation system .

The implementation of information and communication technologies (ICT) in power systems increases the risks of cybersecurity threats, requiring protection measures that should reflect the multi-actor environment of the contemporary power systems. This paper provides a critical assessment of the cybersecurity practices of the transmission system operators (TSOs) from South East Europe (SEE) and the implementation of obligations for TSOs emerging from the complex set of cybersecurity and electricity legislation. The analyses of TSO cybersecurity practices are based on a survey conducted with the TSOs from SEE and show there is a lack of consistent cybersecurity policy at the TSO level. These analyses demonstrate that the differences between TSOs from the SEE region are not very significant with regards to implementation of technical protection and defense measures for critical infrastructures (CIs) and assets. The comprehensive analyses of electricity and cybersecurity legislation uncover the obligations of TSOs emerging from legislation and relate them to current TSO cybersecurity practices, confirming the necessity to boost existing practices. Considering the analyzed legislation and implemented practices, this paper presents a proposal for a cybersecurity framework for TSOs that should improve their organizational and operational response to the evolving cybersecurity challenges.