Abstract
Reliability is a crucial consideration in the expansion of generation or transmission in a bulk power system, especially in a power grid with a high penetration of renewables. Reliability indices, such as loss of load probability (LOLP), are generally evaluated to determine the adequacy of a bulk power system in the future. When a Monte-Carlo simulation is conducted to evaluate the LOLP, the computational time is long because chronological time-series data are involved. This work proposes a novel scenario-based method for studying the LOLP in a bulk power system with a high penetration of renewables. Scenarios are generated by aggregating Markov states of hourly loads, photovoltaic power generations and wind power generations. The power flow result in each scenario is examined to ensure power balance among demand, supply and losses, so the LOLP can be obtained. This novel scenario-based method is more efficient than the traditional chronological time-series approach because the number of considered scenarios is much smaller than the number of considered time-series cases. A set of realistic data regarding Taiwan power system, consisting of 2078 buses associated with a peak load of 39.178 GW, wind power of 6.938GW and photovoltaic power of 20 GW in 2025 is used to validate the proposed method.
Highlights
The operation and planning of electric power grids is becoming increasingly complex on account of the high penetration of renewables and the transactions of power market [1]
To overcome the above limitations, this paper proposes a novel scenario-based method for exploring the loss of load probability (LOLP) in a bulk power system with a high penetration of renewables
A novel scenario-based method is proposed for the analysis of power system reliability in this paper
Summary
The operation and planning of electric power grids is becoming increasingly complex on account of the high penetration of renewables and the transactions of power market [1]. Typical power system reliability studies are categorized into two groups – those that address adequacy and those that address security [6]. Solving this reliability problem is prohibitively timeconsuming owing to the extremely large number of chronological parameters and constraints that are involved. The hourly loads, photovoltaic power and wind power are essential [23]–[26] This paper converts this chronological problem into a scenario-based problem, in which the probabilities and durations of load, wind power and PV power states can be obtained by applying Markov theory. Rather than using a traditional chronological time series with increasing hours from h = 1 to h = 8760 in sequence, the conditions of the power system are varied among Markovian scenarios (Markov chain) according to system transition rates (probabilities).
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