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Abstract: Wind power is a very useful renewable energy source that is attracting consideration around the world due to its non-exhaustive nature and its environmental and social benefits. The correlation between multiple wind sites has a significant impact on the reliability of power systems containing wind energy conversion systems (WECS). Conventional methods cannot be directly applied to evaluate the reliability of WECS in the absence of comprehensive modeling techniques that recognize the correlation of the wind speeds at different wind farm locations. This paper proposes a model for power system reliability assessment that can consider the wind speed correlation and preserve the statistical characteristics of wind speeds, such as the mean and deviation of the wind speed time series (WSTS). A time-shifting technique is used to produce a new WSTS for a given correlation between two wind sites. The optimal shifted time at the two sites is determined using a linear interpolation technique. The probability distributions of the generated power and the system reliability indices with different degrees of correlation between the two sites are compared using two reliability test systems, i.e. the RBTS and the IEEE-RTS. The results show that the proposed method is useful in evaluating the reliability of WECS with correlation between two wind sites. [Copyright &y& Elsevier]

• The proposed multi-state model prevents the underestimation of reliability level caused by two-state failure model. • The proposed model can accurately evaluate the reliability index, which better reflects the multiple operation states. • Different TES strategies will lead to different operation decisions and reliability results of CSP plants. • The SF size and the TES capacity are positively correlated with the system reliability level. But the system reliability index tends to be stable when the SF size and the TES capacity are large. This paper proposes a multi-state reliability evaluation model for the concentrated solar power (CSP) plant considering partial function failure. Firstly, the component functions and components' consequences of random failure of CSP plants are analyzed. Core components affecting the output of CSP plants are selected. The CSP plant is divided into three subsystems: the heat collection, the heat exchange, and the power generation subsystems, according to the component function. Each subsystem is equivalent to a two-state component. Thus, an 8-state Markov model of CSP plant is established. The CSP plant can be operated in a partial function failure state as thermal energy storage (TES) or generation, depending on the functions of solar-heat and heat-electricity conversion. On this basis, the 8-state model can be simplified to a 4-state model by combining the partial function failure states of the same effect. Finally, the 4-state model is applied to the sequential Monte Carlo simulation for the reliability evaluation of power systems containing CSP plants. Two TES strategies are considered in the simulation: One is based on solar field (SF) average output, another is designed to satisfy the load preferentially. The proposed model is tested on the modified RBTS/IEEE RTS systems to verify the effectiveness. [ABSTRACT FROM AUTHOR]

• High nonlinearities are modeled in the integrated energy systems risk evaluation. • The chronological characteristics of gas storages and pipelines are incorporated. • A novel adaptive energy flow algorithm based on a relaxation idea is proposed. • Several new risk indices related to wind power curtailments are presented. The interconnection and coordinated operation of electricity-gas integrated energy system (EGIES) is becoming a trend. The flexible energy conversion achieved by gas-fired power generation (GPG) and power to gas (P2G) has brought a new opportunity for improving the reliability of both electricity and gas systems in EGIES and enhancing the ability in absorbing fluctuant renewable energy. In this paper, a reliability evaluation framework for EGIES with the high nonlinearities of gas system components and the assessment of wind power absorption is proposed. To capture the practical operation behaviors of gas system, the highly nonlinear characteristics of gas system components are accurately modeled and incorporated into the proposed sequential simulation process. To address the convergence difficulties caused by the high nonlinearity of energy flow equations, an improved energy flow calculation algorithm based on a relaxation idea is presented, achieving an effective convergence acceleration in the reliability evaluation of EGIES. The validity and performance of the proposed method are verified by using the RBTS integrated with a gas network. [ABSTRACT FROM AUTHOR]