Estimating the uncertainty of net load of 2030 Renewable Generation

전우영,; 조상민,; 조일현,

doi:10.7849/ksnre.2019.12.15.4.028

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…However, in order to accurately analyze the change of net load curve pattern, it is necessary to predict the hourly pure load curve and the hourly net load curve which includes the pure load level, demand response, renewable generation and other factors. Some studies have introduced the hourly net load pattern with renewable energy resources, but these were based on only the current load level and mainly focused on the impact of variability of renewables [12,17]. Now, we need for the hourly load pattern prediction considering the future change of energy circumstances until 2030.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Challenges Due to Changes in Net Load Curve in South Korea by Integrating DERs

Kim

et al. 2020

Electronics

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The development of Distributed Energy Resources (DERs) is essential in accordance with the mandatory greenhouse gas (GHG) emission reduction policies, resulting in many DERs being integrated into the power system. Currently, South Korea is also focusing on increasing the penetration of renewable energy sources (RES) and EV by 2030 to reduce GHGs. However, indiscriminate DER development can give a negative impact on the operation of existing power systems. The existing power system operation is optimized for the hourly net load pattern, but the integration of DERs changes it. In addition, since ToU (Time-of-Use) tariff and Demand Response (DR) programs are very sensitive to changes in the net load curve, it is essential to predict the hourly net load pattern accurately for the modification of pricing and demand response programs in the future. However, a long-term demand forecast in South Korea provides only the total amount of annual load (TWh) and the expected peak load level (GW) in summer and winter seasons until 2030. In this study, we use the annual photovoltaic (PV) installed capacity, PV generation, and the number of EV based on the target values for 2030 in South Korea to predict the change in hourly net load curve by year and season. In addition, to predict the EV charging load curve based on Monte Carlo simulation, the EV users’ charging method, charging start time, and State-of-Charge (SoC) were considered. Finally, we analyze the change in hourly net load curve due to the integration of PV and EV to determine the amplification of the duck curve and peak load time by year and season, and present the risks caused by indiscriminate DERs development.

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Section: Introductionmentioning

confidence: 99%

Analysis of Challenges Due to Changes in Net Load Curve in South Korea by Integrating DERs

Kim

et al. 2020

Electronics

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“…According to the activity plan of renewable energy sources, local governments and renewable energy producers are actively installing and operating large scale PV systems in the distribution system. However, when the PV systems were interconnected and operated in distribution systems, many problems related to power quality such as voltage fluctuation in distribution system have occurred [1][2][3][4][5]. Under these circumstances, the power company has installed SVR in order to keep voltages of customers within allowable voltage limits in distribution feeders with PV systems [6,7].…”

Section: Introductionmentioning

confidence: 99%

Voltage Control Method of Micro Hydropower Generators for Voltage Stabilization in Distribution Feeder with Renewable Energy Sources

2020

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This paper analyses the problem of voltage control by step voltage regulator (SVR) in the primary feeder with large-scaled PV systems, and presents operation ranges and the voltage control limit of micro hydropower generator (MHG) with power factor (PF) control function. In addition, this paper evaluates the voltage impact in primary feeders depending on voltage control modes of MHG, and then proposes an optimal voltage control algorithm. Furthermore, from the simulation results based on the proposed algorithm, it is verified that it can contribute to voltage stabilization in the distribution system with large-scaled PV systems.

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Solar Insolation Prediction Based on Machine Learning: Error Analysis on Data Similarity and Predictive Model Uncertainty

Hong,

Lee

2024

ksles

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Estimating the uncertainty of net load of 2030 Renewable Generation

Cited by 4 publications

References 5 publications

Analysis of Challenges Due to Changes in Net Load Curve in South Korea by Integrating DERs

Analysis of Challenges Due to Changes in Net Load Curve in South Korea by Integrating DERs

Voltage Control Method of Micro Hydropower Generators for Voltage Stabilization in Distribution Feeder with Renewable Energy Sources

Solar Insolation Prediction Based on Machine Learning: Error Analysis on Data Similarity and Predictive Model Uncertainty

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