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

Chi-Yeon Kim ,Soo-Hwan Cho,Dong-Keun Kim ,Chae-Rin Kim

doi:10.3390/electronics9081310

Abstract

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.

Highlights

With the adoption of the 2015 Paris Agreement, which is the basis for the new climate regime, interest in reducing greenhouse gas (GHG) emissions is increasing worldwide
A net load curve in a day is obtained by removing a PV generation curve from a load load curve [21]
The load curve and net load curve are predicted to confirm the change of the net load curve for each season by year considering high PV and EV penetrations until 2030

Summary

Introduction

With the adoption of the 2015 Paris Agreement, which is the basis for the new climate regime, interest in reducing GHG emissions is increasing worldwide. 16% of man-made carbon dioxide (CO2 ) is produced by motor vehicles (cars, trucks, and buses); increasing the number of EV is essential to reducing GHGs [4]. A net load curve (or pattern) in a day is obtained by removing a PV generation curve from a. A net load curve (or pattern) in a day is obtained by removing a PV generation curve from a load load curve [21]. To determine the future net load curve, it is necessary to predict the future load load curve and the future PV generation curve. We GDP, electricity price, population, on [16]

Methods

Results

Conclusion