Determining Optimal Operating Reserves Toward Wind Power Penetration in Indonesia Based on Hybrid Artificial Intelligence

Abstract

The stability and economic level of the power system operation during the penetration of Wind Power Plants (WPPs) are much determined by the variability and uncertainty of the wind power output. The characteristics of seasonal wind power output can be used to define the optimal operating reserves of a stable and cost-effective power system operation. This paper proposes a comprehensive algorithm of hybrid Artificial Intelligence (AI) approach that combines the Seasonal Autoregressive Integrated Moving Average (SARIMA) and selected Neural Network Variants (NNVs) in Seasonal Daily Variability and Uncertainty (SDVU) scheme. Among all NNVs, Long Short-Term Memory (LSTM) shows the most consistent and accurate results. With the hybrid AI approach, this algorithm calculates the Dynamic Confidence Level (DCL) to determine hourly operating reserves on a daily basis. The proposed algorithm has been successfully tested using historical data of real-world WPPs that operated in Indonesia. Furthermore, the comparison toward non-seasonal with a Static Confidence Level (SCL) in several percentile scenarios is made to prove the cost-effectiveness advantages of this new algorithm that may save up to 4.2% of total daily energy consumption. An interface application is added so that the results of this research can be directly utilized by users both on the observed power system and generally in Indonesia.INDEX TERMS dynamic confidence level, neural network, operating reserve, wind power, SARIMA.

A Probabilistic Methodology for Estimating Reserve Requirement and Optimizing Its Components in Systems With High Wind Penetration

“…The inherent variability and uncertainty of wind power generation need improved power system flexibility [1] [2], which can be enhanced in a variety of ways, including an estimate of the additional reserve capacity required as the variable renewable generation (VRG) expands [3] [4]. In [5] [6], as wind power penetration rises, reserve requirements rise as well, and in [7] [8], additional reserve requirements increase linearly with this rise. In [9], the study of various countries revealed that an increasing amount must be allocated for an operating reserve as the penetration of wind power in the system has increased and the percentage of reserve requirements associated with the installed capacity of wind power varies greatly across different systems.…”