IMPACT STUDY OF AUTO GENERATION CONTROL (AGC) APPLICATION ON SOLAR PV PENETRATION AND ADDING ANCILLARY SERVICE COST

• Main Author: Urfan Qinthara, Muhamad
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/64853
• Institution: Institut Teknologi Bandung

ABSTRACT IMPACT STUDY OF AUTO GENERATION CONTROL (AGC) APPLICATION ON SOLAR PV PENETRATION AND ADDING ANCILLARY SERVICE COST By Muhamad Urfan Qinthara NIM: 23219356 (Master’s Program in Electrical Engineering) The Paris Agreement on climate change, Indonesia's decision to go towards Zero Emission in 2060, plus the very significant decline in Solar PV prices in the last 10 years, forced the energy producer sector, especially power generation, to move towards an energy transition. In the next few years, it is not impossible that the LCOE of Solar PV is equal to or even lower than the variable cost of Coal Powe Plant. However, Solar PV which is classified as Variable Renewable Energy (VRE) has intermittent characteristics because Solar PV is very dependent on the amount of irradiation and the brightness of the air entering the earth until it reaches the earth's surface. On the other hand, the load curve forecasting generally has an error or difference with the actual load curve. So that uncertainty must be responded to by generators operating on electric power systems. Therefore, secondary reserves are needed to respond to the uncertainty of the load curve forecasting and fluctuations from solar PV. In this study, the Java-Bali electricity system is modeled with 5 regions and is connected to the transmission and transfer limits of each. The modeling is done with the help of PLEXOS software. In this study, 4 simulation scenarios were carried out consisting of scenario 1 regarding the analysis of the condition of the system in the existing state. Then scenario 2 by adding a reserve requirement of 8%/10min to the load curve at each interval to respond to errors that can occur from the previously predicted load curve. In scenario 3, generation expansion planning is carried out by applying a reserve of 8%/10min for the needs of load curve fluctuations and 33%/10min for fluctuations that occur in PLTS. In scenario 3 optimizing solar PV penetration as well as the need for flexibility to support solar PV fluctuations as well as fluctuations in the load curve. In scenario 4, adjustments are made to the power plant lean by increasing it by 2x with the original value of 1%/Min for PLTU to 2%/Min. while for gas generators such as Gas Turbine, Gas Engine, and Combine Cycle Gas Turbine (CCGT), which originally had 2%/min, it increased by 2x to 4%/min. similar to what was done in scenario 3, what was done in scenario 4 was generation expansion planning and production simulation. From the four scenarios, analysis was carried out in several ways, such as the average Capacity Factor (CF) for each 5 generator, the energy mix, generation stacking for the operating pattern in one day, as well as an analysis of the cost changes that occurred in each scenario. Determination of ancillary service cost refers to the Generation Marginal Price (GMP). GMP is the highest ratio to the lean capability of each generating unit. In this study, CCGT of Muara Karang GT 1.3 became GMP with a variable cost value of 7.8 cent$/KWh and a lean capability of 2 MW/min. in other words the GMP of the system is 3.9 cent$/KWh. From the four scenarios that have been simulated in this study, it was found that adding reserve requirements to support fluctuations in the load curve or fluctuations in solar PV has an impact on increasing the overall variable cost system. In addition, the activation of Automatic Generation Control (AGC) to contribute secondary reserves causes an additional cost of 28.4 Rp/KWh in scenario 2, then the additional cost increases to 36.7 Rp/KWh in scenario 3, then the additional cost increases again to 49.2 Rp/KWh against scenario 1 or existing conditions. Another impact of the increase in solar PV in the Java Bali system is the decrease in the average CF of coal which occurs due to solar PV penetration during the day. However, the availability of flexibility possessed by the system in scenario 2 is higher, then it increases in scenario 3, and the flexibility of the Java-Bali system is even higher in the simulation with scenario 4. Keywords: Secondary Reserve, Ancillary Services cost, Production Simulation, Generation Expansion Planning, Load Curve Fluctuation, Solar PV Fluctuation.