Selected ‘Starter Kit’ energy system modelling data for Taiwan (#CCG)


 Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to energy system modelling, causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Taiwan, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.


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Description of Content The total power generation capacity in Taiwan is estimated at 46109.64 MW in 2018 [3,4,5,6].The estimated existing power generation capacity is detailed in Table 1 below [3,4,5,6].The methods used to calculate these estimates are described in more detail in Section 2.1.and the ASEAN Centre for Clean Energy (ACE) [7,8] and are applicable to Asia.Projected cost reductions for renewable energy technologies were estimated by applying the cost reduction trends from a 2021 IRENA report focussing on Africa [9] to these Asia-speci c current cost estimates.These projections are presented in Table 3.The cost and performance of parameters of fossil electricity generation technologies are assumed constant over the modelling period.Country-speci c capacity factors for solar PV, wind and hydropower technologies in Taiwan were sourced from Renewables Ninja and the PLEXOS-World 2015 Model Dataset [3,10,11], as well as an NREL dataset [12].Capacity factors for other technologies were sourced from IRENA and ACE [7] and are applicable to Asia.Average capacity factors were calculated for each technology and presented in the table below, with daytime (6am -6pm) averages presented for solar PV technologies.For more information on the capacity factor data, refer to Section 2.1.The combined losses in electricity transmission and distribution in Taiwan in 2014 are estimated based on a study by Singh and Kumar [13].It was then assumed that combined losses would be reduced to 5% by 2050, falling in a linear fashion.Combined transmission and distribution e ciency in Taiwan is therefore assumed to reach 93.0% and 95.0% in 2030 and 2050 respectively.The combined costs of power tansmission and distribution are estimated based on a report by the Economic Research Institute for ASEAN and East Asia (ERIA) [14], which gives cost estimates for several real-life projects in ASEAN.For more detail, see section 2.In the following table, the techno-economic parameters associated with the transmission and distribution network are presented.Taiwan has an estimated 1230kb/d domestic re nery capacity [15].In the OSeMOSYS model, two oil re nery technologies were made available for investment in the future, each with different output activity ratios for Heavy Fuel Oil (HFO) and Light Fuel Oil (LFO).The technoeconomic data for these technologies are shown in Table 5.

Emission Factors
Fossil fuel emit several greenhouse gases, including carbon dioxide, methane and nitrous oxides throughout their operational lifetime.In this analysis, only carbon dioxide emissions are considered.These are accounted for using carbon dioxide emission factors assigned to each fuel, rather than each power generation technology.The assumed emission factors are presented in Table 7.  8 and 9 show estimated domestic renewable energy potentials and fossil fuel reserves respectively in Taiwan.

Electricity Supply System Data
Data on Taiwan's existing on-grid power generation capacity, presented in Table 1, were extracted from the PLEXOS World dataset [3,4,5] using scripts from OSeMOSYS global model generator [23].PLEXOS World provides estimated capacities and commissioning dates by power plant, based on the World Resources Institute Global Power Plant database [5].These data were used to estimate installed capacity in future years based on the operational life data in Table 2. Cost, e ciency and operational life data in Table 2 were collected from reports by IRENA and ACE [7,8], which provide estimates for these parameters by technology in ASEAN and other Asian countries.The costs of renewable energy technologies are expected to fall in the future.In order to calculate estimated cost reductions in the region, technology-speci c cost reduction trends from a very recent IRENA report focussing on Africa [9] were applied to the current Asia-speci c cost estimates [7,8].For offshore wind, the cost reduction trend was instead taken from a technology-speci c IRENA report on the future of wind [25] since it is not featured in [9].The resulting cost projections are presented in Table 3 and Figure 2. It is assumed that costs fall linearly between the data points provided by IRENA and that costs remain constant beyond 2040 when the IRENA forecasts end (except for offshore wind, where the IRENA forecast continues to 2050).Fixed costs for renewable energy technologies in each year were estimated by calculating a certain percentage (ranging from 1-4% depending on the technology) of the capital cost in that year, as done by IRENA [9].An illustrative example of a zero-order least-cost energy scenario for Taiwan produced using the data presented in this paper.
Projected costs of renewable energy technologies for selected years to 2050 [7,8,9] Figure 3

Figures Figure 1
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Table 1 A
table showing the estimated installed capacity of different power plant types in Taiwan for 2015-2018

Table 2 A
table showing techno-economic parameters for electricity generation technologies

Table 3 A
table showing capital cost projections for renewable energy technologies up to 2050 Figure 2 A graph showing capital cost projections for renewable energy technologies from 2015-2050

Table 4 A
table showing cost and performance parameters for power transmission and distribution technologies

Table 5 :
[19]no-economic parameters for re nery technologies[15,16]costs are provided for both imported and domestically-extracted fuels.The fuel price projections until 2050 are presented below.These are estimates based on Asia-speci c cost estimates produced by the Asia Paci c Economic Cooperation (APEC) and ERIA[17.18], with an international average biomass price in 2020 assumed for imported biomass[19].More detail is provided in Section 2.2. Assumed

Table 9 :
[17]mated Fossil Fuel Reserves[17]primarily collected from the reports and websites of international organizations, including the International Renewable Energy Agency (IRENA), the Asia Paci c Economic Cooperation (APEC), the Economic Research Institute for ASEAN and East Asia (ERIA), the International Energy Agency (IEA), and the Intergovernmental Panel on Climate Change (IPCC).The data sources used are detailed in this section. Data