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SUMMARY With the advent of large-scale wind farms and their integration into electrical grids, more uncertainties, constraints and objectives must be considered in power system development. It is therefore necessary to introduce risk-control strategies into the planning of transmission systems connected with wind power generators. This paper presents a probability-based multi-objective model equipped with three risk-control strategies. The model is developed to evaluate and enhance the ability of the transmission system to protect against overload risks when wind power is integrated into the power system. The model involves: (i) defining the uncertainties associated with wind power generators with probability measures and calculating the probabilistic power flow with the combined use of cumulants and Gram-Charlier series; (ii) developing three risk-control strategies by specifying the smallest acceptable non-overload probability for each branch and the whole system, and specifying the non-overload margin for all branches in the whole system; (iii) formulating an overload risk index based on the non-overload probability and the non-overload margin defined; and (iv) developing a multi-objective transmission system expansion planning (TSEP) model with the objective functions composed of transmission investment and the overload risk index. The presented work represents a superior risk-control model for TSEP in terms of security, reliability and economy. The transmission expansion planning model with the three risk-control strategies demonstrates its feasibility in the case study using two typical power systems. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

China has made great achievements in wind power generation. By the end of 2009, the installed capacity of wind power totaled 25.8053 GW, 13.8032 GW of which was added in 2009. Although the industry has developed at an impressive rate, its scale is still comparatively small, not fully matching the country's economic size and great demand for green power. It is widely believed that the wind power market in China can develop at an even faster rate over the next decade. A stable market for wind power investment relies on both the cost of wind power and an effective pricing policy to motivate growth in the wind industry. This paper presents corresponding analysis of the costs of wind power generation and the current pricing policies implemented in China. The composition of wind power costs is elaborated through comparing it with that of conventional power resources. The localization of wind turbine manufacturing, which aims to decrease the wind generation costs and promote the development of the local wind power industry, is introduced. Two current pricing systems applied in China are examined: the price committed by the wind power concession bidding projects and the price authorized by the provincial governments. An inflation-adapted model is proposed to analyze the risk of concession prices. Finally, the paper concludes with discussions on the potential benefits and the future strategies for the development of wind power in China. [ABSTRACT FROM AUTHOR]

The ever-increasing penetration of wind power generation and plug-in electric vehicles introduces stochastic continuous disturbances to the power system. This paper proposes an analytical approach to analyze the influence of stochastic continuous disturbances on power system small signal stability. The noise-to-state stability (NSS) and NSS Lyapunov function (NSS-LF) are adopted for stability analysis with respect to the magnitude of uncertainties in a power system. The power system is modeled as a set of stochastic differential equations (SDEs). The supremum of the norm of the covariance is employed to characterize the influence of magnitudes of uncertainties on the power system. Then the relationship between the magnitudes of stochastic variations and probabilistic stability is explicitly identified by NSS. The proposed method can assess the stochastic stability of the power system by checking some algebraic expressions. Hence, it has high computation efficiency compared with the well-established Monte Carlo based method. Besides, since the magnitudes of the stochastic variations are integrated into the definition of the stochastic stability, the proposed method provides theoretical explanations for the impacts of uncertainties. [ABSTRACT FROM AUTHOR]

To address the challenges of integrating ever-increasing renewable energy generation such as wind power and photovoltaic (PV) to the power system concerned, the wind-PV-thermal-bundled (WPTB) transmission mode could be employed to mitigate the intermittent power output from wind and PV units. In this work, based on the mathematical models of thermal generation units, wind turbines and PV units, the WPTB transmission system model is developed. Each load demand is modeled as a random variable under various operating conditions of the concerned power system. The Lyapunov linearization method is used to obtain the system matrix of each operation mode, and then all eigenvalues of the system can be attained. According to the generator participation factor, the oscillation modes of the power system are classified. The eigenvalue and damping ratio of each oscillation mode are employed to formulate the objective function of the optimal strategy for enhancing probabilistic small-signal stability, and the particle swarm optimization algorithm is used for global optimization. The secure operation of the power system can be ensured in a wider range by the designed optimization strategy in this work. The effectiveness of the method is demonstrated by simulation results of a sample power system which can operate stably under some uncertain operation conditions. [ABSTRACT FROM AUTHOR]

Power system stability has been suffering increasing threats with the ever-growing penetration of intermittent renewable generation such as wind power and solar power. Battery energy storage systems (BESSs) could mitigate frequency fluctuation of the power system because of their accurate regulation capability and rapid response. By dividing the Area Control Error (ACE) signal and the State of Charge (SOC) of battery energy storage systems into different intervals, the frequency control task of BESSs could be determined by considering the frequency control demand of the power grid in each interval and SOC self-recovery. The well-developed model predictive control can be employed to attain the optimal control variable sequence of BESSs in the following time, which can determine the output depths of BESSs and action timing at different intervals. The simulation platform MATLAB/Simulink is used to build two secondary frequency control scenarios of BESSs for providing frequency regulation service. The feasibility of the presented strategy is demonstrated by simulation results of a sample system. [ABSTRACT FROM AUTHOR]

One of the major ways of delivering renewable energy generation from large-scale energy bases in northeast, northwest, and northern China, is to bundle the power from wind-photovoltaic-thermal units and then transmit it by alternating current/direct current (AC/DC) systems. The interactions among wind power units, photovoltaic (PV) power units, and high voltage direct current (HVDC) systems make the stability of the interconnected power system more complicated. In this paper, a framework model of wind-PV-thermal-bundled power transmitted by AC/DC systems is constructed based on the mathematical models of thermal power units, wind power units, PV power units, and HVDC transmission systems. Considering the fluctuations of wind power outputs and PV power outputs, a small-signal stability model of an interconnected power system with wind-PV-thermal-bundled power transmitted by AC/DC systems is established based on an existing stability theorem. The interactions among various forms of energy and their impacts on wind-PV-thermal-bundled power transmitted by AC/DC systems are studied through theoretical analysis and dynamic simulation. A sample interconnected power system is used to demonstrate the proposed method. It is shown by simulation results that the wind-PV-thermal-bundled power transmission distance; the electrical distance among wind power units, PV power units, and thermal power units; the grid-connected capacities of wind, PV, and thermal power units; and the power loading ratios of AC lines over DC lines all have various degrees of impacts on the stability of the interconnected power system. [ABSTRACT FROM AUTHOR]

The well-developed unified power flow controller (UPFC) has demonstrated its capability in providing voltage support and improving power system stability. The objective of this paper is to demonstrate the capability of the UPFC in mitigating oscillations in a wind farm integrated power system by employing eigenvalue analysis and dynamic time-domain simulation approaches. For this purpose, a power oscillation damping controller (PODC) of the UPFC is designed for damping oscillations caused by disturbances in a given interconnected power system, including the change in tie-line power, the changes of wind power outputs, and others. Simulations are carried out for two sample power systems, i.e., a four-machine system and an eight-machine system, for demonstration. Numerous eigenvalue analysis and dynamic time-domain simulation results confirm that the UPFC equipped with the designed PODC can effectively suppress oscillations of power systems under various disturbance scenarios. [ABSTRACT FROM AUTHOR]