*2.3. Hourly Simulation and Scenario Analysis*

The hourly simulation used Python for the Power System Analysis (PyPSA) Modeling Framework [25]. The PyPSA environment provides a framework for the buses, lines, loads, generators, and storage, units among many other parameters. In this simulation, since Kyushu was modeled as a single point, only one bus was used, and all the loads, generators, and storage units were connected directly to this bus. The single-bus network was constructed based on Figure 8, where the coal generator, the Kyushu demand, and the transmission demand were directly connected to a single bus. The rest of the generators was then connected to a sub-bus, which was then connected to the main bus. Creating the sub-bus ensured that the PHES could not charge from the coal generator, which prevented the optimizer from generating and storing more power from coal for later use. For this study, the synthetic load and solar power generation profile for the representative years (Table 4) were used iteratively during the optimization.

**Figure 8.** Configuration of the single-bus network used in the optimization.

The installed solar capacity was increased by 1 GW increments from 0 GW until 20 GW. The latest known capacities for the other generators as of FY2019 are shown in Table 5, which was consolidated based on various sources [27,30,31]. Although the nuclear, geothermal, and biomass could change within the year, as a baseload, they were fixed to their respective maximum capacities to provide consistency throughout the years under simulation. Hydropower generation was based on the daily dispatch capacity calculated using the total daily dispatch in the 2019 data. The simulator allocated the hourly dispatch based on the optimization. However, minimum and maximum dispatch were still considered based on the actual data. The PHES was treated as both a generator and a load with a maximum transfer capacity of 2.3 GW, a total capacity of 13.8 GWh, and round trip efficiency of 0.70% (0.84% one way).


**Table 5.** Generators in Kyushu as of FY2019.

The optimization aims to minimize the coal capacity while ensuring energy balance. The hourly resolution was used due to the limitation of the available data. Solar energy is preferred as long as the minimum operating output or ramp limit seen in Table 5 for coal and LNG are satisfied. Since LNG might become a future bottleneck, LNG quota (in TWh) is used as a constraint in the simulation. LNG quota (*LNGTWh quota*) is defined as the maximum total annual electricity generation used in the optimization with the maximum generation capacity of 5.25 GW.

Using the recently published resource utilization data from KyEPCO [32], it was determined that the company generated 8 TWh from LNG in 2019 through their 4.625 GW LNG plants. This generation represents 20% LF for the company. An independent power producer owns the other 0.625 GW LNG power plants in the region, which are composed of mixed gas power generators. Assuming these IPP plants are running at a higher LF of 40%, it was determined that the LNG plants generated around 10 TWh in 2019. Using 10 TWh as the base case, the simulation gradually incremented the LNG quota by 20%, 60%, and 100%, yielding 12, 16, 20 TWh LNG quota. A report from Japan's Ministry of Economy, Trade, and Industry (METI) [33] showed that LNG is more economical than coal at LF < 60%; thus, the scenario analysis also explored 28 TWh (60% LF). Preliminary exploration also showed that increasing the quota further has a minor impact on the emission and cost unless more LNG capacity is installed; thus, this was not explored any further. Additional LNG quota could also increase energy security risk given the LNG market situation.

A summary of the LNG quota scenarios is shown in Table 6. The scenarios (*LNGTWh quota*2– *LNGTWh quota*4) reflects one way to reach each of the identified quota from the base case (*LNGTWh quota*1). For the 12, 16, and 20 TWh scenarios, KyEPCO could increase their efficient power plants' LF. Increasing it further would require KyEPCO to increase their steam LNG plants' LF plants and coordinate with the IPP to increase their production.



Capacity (Cap) in MW; load factor (LF) in %; generation (Gen) in TWh.
