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Highlights • Smart grid technologies are explored as resilience enhancement measures for enabling the self-adaptive ability of power systems. • The concept of weather condition-based demand response program pricing mechanism is proposed. • Network topology optimization is first applied to realize the potential of transmission network in surviving the natural hazard by enhancing the system resilience. • A sequential Monte Carlo Simulation based evaluation methodology is developed by incorporating smart grid technologies which are used as resiliency resources. Abstract Natural hazards are great threats to the safe and reliable operation of electric power systems. Some high-impact low-probability (HILP) events usually cause severe load losses to the power grid. Therefore, the enhancement of power system resilience appears to be particularly important. Nowadays, novel smart grid technologies provide more flexible ways for the power system operation. However, these technologies are not comprehensively incorporated in the resilience assessment framework to quantify their contribution for resilience enhancement. In this paper, fragility models for transmission lines and towers and sequential wind data are applied to simulate the operational states of power system under windstorm events. Then, a demand side management (DSM) program termed weather condition based real time pricing (WCRTP) framework is proposed to regulate the customer's electricity consumption behavior according to the extreme weather conditions. A network topology optimization (NTO) operation strategy is applied to mitigate the transmission congestion and realize the potential of transmission capacity by optimizing the network topology. The sequential Monte Carlo Simulation (MCS) method based resilience enhancement evaluation framework is developed to incorporate WCRTP and NTO. Numerical case studies are performed on modified RTS-79 systems. Both methods are proved to be effective self-adaptive measures for power systems in both customer behavior regulation aspect and transmission strategy aspect to boost the system resilience, which could eventually help power system operators to deal with the natural hazards in a more flexible, resourceful, and reliable manner. [ABSTRACT FROM AUTHOR]

Exhausting fossil fuels and increasing environmental pollutions call for the wider deployment of plug-in hybrid electric vehicles (PHEVs), which enable the interactions of transportation and electric sectors. The extra loads for charging massive PHEVs could compromise the power system reliability and impose considerable stress on the power system. Transmission line congestions and generation capacity inadequacy could be caused under this circumstance. However, there is little literature which comprehensively studies the impact of large-scale PHEVs on the bulk power system reliability when smart grid technologies are incorporated including smart charging and flexible transmission topology control technologies. This work studies the impacts of different charging strategies and transmission network operation strategies on the bulk power system reliability with high PHEVs integration. An evolution strategy particle swarm optimization (ESPSO) algorithm is applied to optimize the charging load of PHEVs and shave the peak load. A network topology optimization (NTO) operation strategy is employed to lessen the transmission congestions and reduce the load curtailment. Based on the sequential Monte Carlo simulation method, these technologies are integrated into the reliability evaluation process. Numerical studies and sensitivity analysis are conducted on modified IEEE RTS-79 systems. The results verify the effectiveness of the technologies to realize the potential of existing power system infrastructures so as to relieve the stress caused by the PHEVs load, increase the available penetration of PHEVs and promote the bulk power system reliability which is meaningful for power system planning and risk management. [ABSTRACT FROM AUTHOR]

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]

Abstract: This paper proposes an analytical model and algorithm for tracing power flow (TPF). The concept, construction approach and properties of extended incidence matrix (EIM) are developed. By using results of an AC or DC power flow solution from any off-line program or state estimation, the extended incidence matrix, generation and load power vectors, and distribution factor matrix are derived so that the analytical model of power transfers between generators and loads can be built. The major advantage of the proposed method is that the matrix theory is used to directly build the TPF model and no proportional sharing assumption on the flow distribution is needed. The method was tested using a 4-bus system, and the IEEE 30-bus and IEEE 14-bus power systems. The case studies indicate that the developed technique can be applied to any power system with or without loop flows. [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]

• This paper creatively studies the three-dimensional coordinated layout planning of the ocean current power, taking into account the characteristics of the three-dimensional distribution of ocean currents. • The velocity-output relation of ocean current power is obtained considering the velocity-depth characteristic and the three-dimensional wake effect of the three-dimensional distributed ocean current turbine array. • A coordinated layout optimization model of ocean current turbines and the collector system is presented, considering the three-dimensional wake effect, the three-dimensional topology constraints and the load shedding cost of the system. • The impact of main important factors on the ocean current power plant planning is studied, including the spatial velocity variation, the vertical distance, planning area, load supplied, installation & maintenance cost and power coefficient. Ocean current generation has become a popular form of supplying electric energy by using fluid kinetic energy. For ocean current, the key difference from other planning can be embodied in the turbine layout planning region, which needs to be considered as a three-dimensional area. Considering that, this paper investigates the three-dimensional ocean current turbines and collector system coordinated layout planning model. First, a velocity-depth curve of interest current area is determined by fitting historical velocity data. Then, a three-dimensional ocean current wake model is derived through the integral form of momentum conservation to analyze the influence of the wake effect on the velocity of the three-dimensional distributed turbine array. Finally, a two-level three-dimensional location and capacity planning model is established which involve three-dimensional topology constraints, with the upper-level goal of minimizing the whole system cost, and the lower-level goal of minimizing the cost of power collection topology. The accuracy and effectiveness of the proposed model are investigated through the case study on the current data of the Gulf of Mexico. [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]