تجزیه و تحلیل هزینه در هزینه های کاهش انتشار CO2 با توجه به سیاست های طرف عرضه برای بخش برق تایوان

Because Taiwan is an island nation, it is difficult to obtain energy from external power suppliers; therefore, advance planning and scheduling of power development is crucial. This study uses a multi-objective planning method to minimize the cost of power generation and reduce carbon dioxide emissions by decreasing the dual objective of building the power supply scheduling model and the target year. This is conducted according to simulations of future carbon emission reduction policies for the scheduling of power supply situations. The results show that nuclear units will be able to reduce the power generation electricity costs and carbon dioxide emissions effectively; renewable energy has excellent potential to reduce emissions, and the cost of solar power technology with high fossil fuel prices will gradually enhance its cost competitiveness. Gas, although the cleanest fossil fuel, cannot be underestimated for its carbon dioxide emissions. As fossil fuel prices increase, gas will gradually experience a reduction in carbon reduction benefits; integrated gasification combined cycle with carbon capture and storage technology will replace part of the oil and gas power generation, and in addition to the reduction of carbon dioxide and costs, will achieve the goal.

Electricity demand is similar to technological products. With advancements in technology and the stabilization of society, electricity has become an irreplaceable necessity in people's lives. However, electricity is and always has been difficult to store. With no reserves in stock, instantaneous electricity demand often requires immediate power production. Planning and construction for large power plants and power transmission and distribution infrastructure are time consuming and capital intensive. Meanwhile, Taiwan is an island nation unable to connect to external sources of energy. Accurate forecasting of future demand for power, however, can facilitate appropriate development and dispatching of power sources. This can simultaneously avoid stagnation in industrial development and reduce the difficulties caused to people's lifestyles, resulting from an insufficient supply of power and avoiding waste of resources and idle power plants because of over investments. Therefore, power demand forecasting is a crucial topic for the power industry. The economy has flourished since the industrial revolution. Behind this advanced economization is a vast consumption of fossil fuels. Fig. 1 displays the speed of primary energy demand growth, in which fossil fuels continue to occupy an indispensable standing. International Energy Agency, 2010b and International Energy Agency, 2010c estimated that CO2 emissions will double between 2007 and 2050 (see Fig. 2). Full-size image (34 K) Fig. 1. World primary energy supply. Source: International Energy Agency, 2010a. Figure options Full-size image (20 K) Fig. 2. IEA CO2 emission estimates. Notes: In this chapter, unless otherwise noted, industry includes blast furnaces and coke ovens, as well as the non-energy use of petrochemical feedstocks. Industrial-process emissions are excluded. Others includes agriculture, fishing and foresty. Unless otherwise indicated, all material derives from IEA data and analysis. Source: International Energy Agency, 2010c Figure options Overall, analysis of the total energy consumed in Taiwan shows that power accounted for the highest proportion at 48.6% in 2010. In addition, coal-fired units were the main power supply structures in Taiwan, accounting for 49.91% in 2010, which caused the level of CO2 emissions from the power sector to surpass that of other sectors (Fig. 3 and Fig. 4). Consequently, to achieve the government's reduction target, the power sector is frequently considered as the starting point for reduction endeavors. The development of a system for supporting power technology development decisions to achieve multiple objectives, such as a stable power supply, CO2 reduction, and low costs, is a crucial topic. Full-size image (30 K) Fig. 3. Power generation structure in Taiwan. Source: The Bureau of Energy, Ministry of Economic Affairs, 2011; compiled in this study. Figure options Full-size image (32 K) Fig. 4. CO2 emissions in Taiwan by sector. Source: The Bureau of Energy, Ministry of Economic Affairs, 2010. Figure options Plans for a complete and stable national power supply system, in addition to depending on multiple expert opinions, must consider recent international trends in power development and should gradually conform to environmental awareness. Long-term power supply planning is a lengthy process requiring readjustments to any point. This study used multi-objective planning to construct a power supply model. Using past historical data and various corresponding energy policies, including data on private power plants and cogeneration under both CO2 emission limits and the open market, various scenarios were simulated to enhance understanding on the ideal future power supply scenario. This study can act as a reference for future power planning development and power industry decision makers. Therefore, the primary research objectives were as follows: (1) to examine emerging technologies and future directions of CO2 reduction in the domestic and foreign power sector, constructing a simulated scenario for the application of CO2 reduction technologies; and (2) to construct a power supply planning model simulating CO2 reduction potential and relative costs for each technology and scenario using either economization of power generation or reduction of greenhouse gases as the objective. The power supply model comprised a demand-side power load forecasting model and a supply-side power supply planning model. However, because demand-side data are excessively complex and cannot be easily obtained, and considering that the main objective of this study was to investigate the effects that incorporating novel technologies, such as renewable energy and supercritical coal-fired units, has on power supply scheduling, we focused on reviewing literature related to the power supply planning model. Chen et al. (1993) conducted a detailed review of the various power load demand forecasting methods. The results showed that before the 1970s, the power companies in various countries typically employed inexpensive and simple statistical methods (e.g., trend analysis and extrapolation forecasting methods) to predict the power load demand required by the country in the future. Blok et al. (1993) discussed the potential for improving energy efficiency in the Netherlands by 2000 using a database of 300 energy conservation techniques. The investigation results showed that an emissions reduction of 41% was technically feasible with the application of all energy conservation techniques. The Dutch government's policy aims to increase energy efficiency by approximately 20% between 1990 and 2000. Based on our study results, we determine that this figure is feasible and can be achieved by applying energy conservation techniques with net negative CO2 emission reduction costs. However, we also surmise that compared to those currently applied, stronger energy conservation incentives are required for the future. Regarding the power supply planning model, Lai (1997) developed a power load forecasting model using a back-propagation artificial neural network algorithm and according to various regional developments to predict the power demand of different regions. Furthermore, based on the regional power demands and various potential power supply sources, the multi-objective planning method was adopted to construct a power supply planning model, which was then used as a reference for supply-side power planning. The simulation results indicated that power industries will be affected by adjustments in power prices resulting from increasing power generation costs. In addition, the establishment of private power plants will impact the coal-fired units of the Taiwan Power Company (Taipower). For cases entailing a lack of policy tools to regulate the power generation ratio, a strategy that allows markets to freely determine the power supply structure is a feasible compromise. Oliveira and Antunes (2004) adopted the mixed integer linear programming method for multi-objective planning to construct a power generation expansion planning model. The model objectives include achieving minimum total generation expansion costs, minimum environmental impact, and minimum environmental costs. The simulation results showed that the natural gas-combined cycle unit was the optimum choice for power generation expansion. Hung et al. (2008) employed the mixed integer linear programming method to establish a long-term power development planning model. Accounting for various limitations, such as the fuel percentage of a unit, CO2 emissions, and the characteristics of power generation units, the purpose of the model was to determine the fuel costs of the units, variable operation and maintenance costs, fixed operation and maintenance costs, and total carbon tax minimization. The results were then used as a reference to simulate a scenario where a power generation-related policy was implemented in the power sector for 20 years. Based on the nuclear-free homeland policy, the results indicated that coal-fired and gas-fired power generation units would remain the primary sources of power supply in the future, and that the unit capacity of coal-fired units would increase most significantly. Tekiner et al. (2010) adopted the mixed integer linear programming method and the Monte Carlo simulation method to construct a power generation unit expansion and construction planning model. The model objectives were to minimize costs and pollution emissions. The simulation results showed that in concurrent considerations of minimizing CO2 and costs, the nuclear energy and wind energy units would be first incorporated in the expansion and construction planning. When pursuing cost minimization without considering the environmental consequences, the percentage of coal-fired units would increase. Furthermore, CO2 reduction targets would decrease the use of coal-fired units, and wind turbine units and gas-fired combined cycle units would be employed as substitutes. Delgado et al. (2011) examined the influence that the nuclear energy option would have on the costs of Spain's long-term power generation system and CO2 emissions using a stochastic linear model and considering various fossil fuel and carbon price scenarios and different stability and supply security restrictions. Their findings showed that CO2 emissions could be reduced without considering the nuclear generation option; however, the power generation costs would be higher. Moreover, the development of clean coal technologies would affect the adoption of nuclear power generation methods. Based on the studies discussed above, overall awareness of environmental sustainability has increased substantially in recent years, from initially only considering minimizing the total power generation costs when planning power supply scheduling, to considering minimizing both the total power generation costs and CO2 emissions. Thus, to achieve the goals of minimizing the total power generation costs and CO2 emissions, we employed the multi-objective planning method to construct a power supply planning model. The scenario simulation method was adopted to investigate the influences that various novel low-carbon technologies and the carbon-free energy policy implemented during a future target year have on the deployment, costs, and CO2 emissions of a unit, which are all affected by power supplies. In addition, this study examined the policy options of each target year and applied the cross-constraint method to establish a non-inferior solution set and investigate the marginal rate of substitution for costs and CO2. The results were then compared with the power generation changes of various units to provide a supply scheduling reference for relevant power units or sectors.

This study used multi-objective planning to construct a power supply planning model for the main island of Taiwan. Based on the simulation of the effects on the policy implementation for future domestic supply-side CO2 reduction policies in the power sector, and using the cross-constraint method proposed by Lai (1997), a compromising solution was achieved between the mutually exclusive objectives of minimizing both power generation costs and CO2 emissions to enhance understanding of the replacement relationship between the two factors. The change in power output confirmed the sequence for introduction of generator units into the power dispatch. Practically, this method can be directly applied; however, depending on the region, modifications to the unit parameters, such as power generation costs and installed capacity, are required. The following section provides conclusions for a reference, based on the results of this study's simulations.