Power system simulations that extend over a time period of minutes,hours,or even longer are called extendedterm simulations.As power systems evolve into complex systems with increasing interdependencies and richer dyn...Power system simulations that extend over a time period of minutes,hours,or even longer are called extendedterm simulations.As power systems evolve into complex systems with increasing interdependencies and richer dynamic behaviors across a wide range of timescales,extendedterm simulation is needed for many power system analysis tasks(e.g.,resilience analysis,renewable energy integration,cascading failures),and there is an urgent need for efficient and robust extendedterm simulation approaches.The conventional approaches are insufficient for dealing with the extendedterm simulation of multitimescale processes.This paper proposes an extendedterm simulation approach based on the semianalytical simulation(SAS)methodology.Its accuracy and computational efficiency are backed by SAS's high accuracy in eventdriven simulation,larger and adaptive time steps,and flexible switching between fulldynamic and quasisteadystate(QSS)models.We used this proposed extendedterm simulation approach to evaluate bulk power system restoration plans,and it demonstrates satisfactory accuracy and efficiency in this complex simulation task.展开更多
The power output of solar photovoltaic （PV） systems is affected by solar radiation and ambient temperature. The commonly used evaluation techniques usually overlook the four weather states which are clear, cloudy, f...The power output of solar photovoltaic （PV） systems is affected by solar radiation and ambient temperature. The commonly used evaluation techniques usually overlook the four weather states which are clear, cloudy, foggy, and rainy. In this paper, an ovel analytical model of the four weather conditions based on the Markov chain is proposed. The Markov method is well suited to estimate the reliability and availability of systems based on a continuous stochastic process. The proposed method is generic enough to be applied to reliability evaluation of PV systems and even other applications. Further aspects investigated include the new degradation model for reliability predication of PV modules. The results indicate that the PV module degradation over years, failures, and solar radiation must be considered in choosing an efficient PV system with an optimal design to achieve the maximum benefit of the PV system. For each aspect, a method is proposed, and the complete focusing methodology is expounded and validated using simulated point targets. The results also demonstrate the feasibility and applic- ability of the proposed method for effective modeling of the chronological aspects and stochastic characteristics of solar cells as well as the optimal configuration and sizing of large PV plants in terms of cost and reliability.展开更多
基金supported by the lab-directed research&develop-ment(LDRD)program of Argonne National Laboratory and U.S.DOE Advanced Grid Modeling Program grant DE-OE0000875.
文摘Power system simulations that extend over a time period of minutes,hours,or even longer are called extendedterm simulations.As power systems evolve into complex systems with increasing interdependencies and richer dynamic behaviors across a wide range of timescales,extendedterm simulation is needed for many power system analysis tasks(e.g.,resilience analysis,renewable energy integration,cascading failures),and there is an urgent need for efficient and robust extendedterm simulation approaches.The conventional approaches are insufficient for dealing with the extendedterm simulation of multitimescale processes.This paper proposes an extendedterm simulation approach based on the semianalytical simulation(SAS)methodology.Its accuracy and computational efficiency are backed by SAS's high accuracy in eventdriven simulation,larger and adaptive time steps,and flexible switching between fulldynamic and quasisteadystate(QSS)models.We used this proposed extendedterm simulation approach to evaluate bulk power system restoration plans,and it demonstrates satisfactory accuracy and efficiency in this complex simulation task.
文摘The power output of solar photovoltaic （PV） systems is affected by solar radiation and ambient temperature. The commonly used evaluation techniques usually overlook the four weather states which are clear, cloudy, foggy, and rainy. In this paper, an ovel analytical model of the four weather conditions based on the Markov chain is proposed. The Markov method is well suited to estimate the reliability and availability of systems based on a continuous stochastic process. The proposed method is generic enough to be applied to reliability evaluation of PV systems and even other applications. Further aspects investigated include the new degradation model for reliability predication of PV modules. The results indicate that the PV module degradation over years, failures, and solar radiation must be considered in choosing an efficient PV system with an optimal design to achieve the maximum benefit of the PV system. For each aspect, a method is proposed, and the complete focusing methodology is expounded and validated using simulated point targets. The results also demonstrate the feasibility and applic- ability of the proposed method for effective modeling of the chronological aspects and stochastic characteristics of solar cells as well as the optimal configuration and sizing of large PV plants in terms of cost and reliability.
