Composite System Reliability Evaluation With Essential Reliability Services Assessment of Wind Power Integrated Power Systems

Abstract

With the increasing penetration of renewable resources and the retirements of conventional coal-fired generation units, power systems are undergoing significant transformation with the instantaneous renewable generation penetration sometimes approaching over 50 percent of the demand. This transformation makes the need for comprehensive reliability assessment critical to properly account for the composite system adequacy and the sufficiency of essential reliability services (ERSs). This paper introduces a probabilistic approach to evaluate the reliability of wind power integrated power systems considering ERSs including frequency and voltage support, in conjunction with resource adequacy. To consider stochasticity in system operating conditions, the proposed approach utilizes sequential Monte-Carlo Simulation (SMCS) as the probabilistic analysis methodology and formulates probabilistic reliability metrics representing the composite system adequacy and the ERSs. The proposed approach and metrics are demonstrated on a synthetic test system. Simulation results illustrate the efficacy of the proposed approach and its importance in analyzing the impact of increasing wind power penetration as well as wind turbine generators (WTGs) providing ERSs on system reliability. Index Terms-Essential reliability services, frequency control, Monte-Carlo Simulation, reliability metrics, voltage control, wind power penetration. NOMENCLATURE Abbreviations AC Alternating current. COV Coefficient of variation. EGAF Expected generator tripping caused by abnormal frequency. EGAV Expected generator tripping caused by abnormal voltage. ELCC Effective load carry capability. EOAF Expected occurrence of abnormal frequency at generator terminals. EOAV Expected occurrence of abnormal voltage at generator terminals. EPNS Expected power not supplied. LOLP Loss of load probability.

A comprehensive review of reliability assessment methodologies for grid‐connected photovoltaic systems

“…In [37], the reliability evaluation of power system integrated with wind technology is done using a probabilistic technique, taking into account essential reliability services (ERSs), including frequency and voltage support. Sequential Monte Carlo simulation (SMCS) is utilized to represent probabilistic reliability metrics that represent the composite system adequacy and the ERSs.…”

“…Loss of load probability and expected power not served for wind turbine generator with and without essential reliability services [37]. …”

“…In [37], the reliability evaluation of power system integrated with wind technology is done using a probabilistic technique, FIGURE 6 Reliability assessment of power grid system [36]. ASAI, average service availability index; CAIDI, customer average interruption duration index; SAIDI, system average interruption duration index; SAIFI, system average interruption frequency index; DER, distributed energy resource; SD, storage device.…”

Co-evaluation of power system frequency performance and operational reliability considering the frequency regulation capability of wind power

“…These studies primarily analyze the impact of frequency regulation on the output power of generators, overlooking the influence of system frequency performance on the reliability parameters of the generation units. Moreover, they fail to adequately consider the frequency regulation capabilities of wind turbine clusters and neglect factors such as the wake effect of wind turbine clusters, leading to overly optimistic reliability assessment results (Wang et al, 2020).…”

Consideração Das Correlações Espaciais Entre Os Regimes De Ventos Na Geração De Cenários De Produção De Energia Eólica – Aplicação Ao Fluxo De Potência Probabilístico

“…Uma capacidade inadequada de prever a produção de energia eólica nos diversos horizontes de tomada de decisão afeta adversamente a estabilidade, a confiabilidade, o planejamento e a programação da operação do sistema de energia, e também o seu benefício econômico. Assim, torna-se fundamental o desenvolvimento e o aprimoramento de metodologias para representar as incertezas das fontes renováveis intermitenteseólica e solar, incluindo-se os modelos de planejamento da expansão e da operação, em seus diversos horizontes de tomada de decisão (ESTANQUEIRO et al 2008, HELSETH & MELO 2020, 2022MACEIRA et al 2020MACEIRA et al , 2022PESSANHA et al, 2020); incluem-se neste contexto, entre outros, análise de confiabilidade (BILLINTON 1984, WANG et al 2020, MELO et al 1993, DAI et al 2015 e fluxo de potência probabilístico -FPP (BORKOWSKA 1974), ALLAN et al 1981, LEITE DA SILVA et al 1990, USAOLA 2009.…”