Application of Monte Carlo simulation to generating system well‐being analysis considering renewable sources

Abstract

SUMMARYThis paper presents an application of Monte Carlo chronological simulation to evaluate the reserve requirements of generating systems, considering renewable energy sources. The idea is to investigate the behavior of reliability indices, including those from the well-being analysis, when the major portion of the energy sources is renewable. Renewable in this work comprises hydroelectric, mini-hydroelectric, and wind power sources. Case studies on a configuration of the Portuguese Generating System are presented and discussed.

A probabilistic method of operational reserve evaluation using Monte Carlo simulation

“…The reliability indices calculated from such analysis can be utilized to evaluate the reserve capacity in a certain system as well [5], [14]. But by far, research on Monte Carlo reserve evaluation is limited.…”

Risk management of smart grids based on managed charging of PHEVs and vehicle-to-grid strategy using Monte Carlo simulation

“…In our adequacy analysis, the smart grid is divided into three states: healthy, marginal and at-risk, according to the power balance of the supply and demand sides [18,39,40].…”

“…The discussed approach is known to provide well-being assessment including more information than that provided by the basic adequacy evaluation approaches. As described and according to the concept of the well-being criteria introduced in [18,22,39], the well-being state of a smart grid was investigated as demonstrated in Eq. (21).…”

The Future Energy Mix Paradigm: How to Embed Large Amounts of Wind Generation While Preserving the Robustness and Quality of the Power Systems?

“…Due to this fact it was recently introduced in some countries the concept of wind energy storage -and other highly variable time-dependent renewable primary sources -through the establishment of bilateral contracts between the wind park owners and the operators of reversible hydro power stations. The identification of the optimised daily operation strategy for the mix of renewables can be determined by solving a linear hourly-discretized optimisation problem where the economic benefits of such strategy are driving an objective function (Leite da Silva et al, 2007). This form of wind energy storage enables to optimise the daily operation strategy of the power system and allows to:…”

“…The objective is to investigate the behaviour of the common reliability indices, like LOLP = loss of load probability; LOLE = loss of load expectation; EPNS = expected power not supplied; EENS = expected energy not supplied; LOLF = loss of load frequency; LOLD = loss of load duration; LOLC = loss of load cost, as well as well-being indices. Chronological Monte Carlo simulation may be used to evaluate the reserve requirements of the future expansion plans of the generation system, to be defined by a TSO considering a large penetration of wind generation (Leite da Silva et al, 2007). This analysis requires a proper modelling of system components regarding their reliability, which involves the treatment of the primary energy resource availability (hydro, wind, cogeneration, etc.…”