Nuclear and Photovoltaic (PV) Modeling

Additionally, the recent version of DNE21 incorporates a nuclear module, which describes in detail the nuclear fuel cycle and advanced nuclear technology. The new model takes account of the availability of advanced nuclear technologies, such as nuclear fuel cycle and fast breeder reactors, which can drastically improve the usage efficiency of natural uranium resources. Light-water reactors (LWR), light-water mixed oxide fuel reactors (LWR-MOX), and fast breeder reactors (FBR) are considered specific kinds of nuclear power generation technologies. This model considers four types of nuclear fuel and spent fuel (SF): fuel for initial commitment, fuel for equilibrium charge, SF from equilibrium discharge, and SF from decommissioning discharge. Fuel for initial commitment is demanded when new nuclear power plants are constructed. Equilibrium charged fuel and equilibrium discharged SF are proportional to the amount of electricity generation. Decommissioning discharged SF is removed from the cores of decommissioned plants. This model also considers time lags of various processes in the system for initial commitment, equilibrium charge, equilibrium discharge, and decommissioning discharge. Supply and demand balances of each type of fuel and SF during the term interval (10 years) were formulated to consider the effects of the time lags mentioned above. In the nuclear waste management process, SF, which is stored away from power plants, is reprocessed or disposed of directly. Uranium 235 and Plutonium (Pu) can be recovered through reprocessing of SF. Recovered Uranium 235 is recycled through a re-enrichment process. Some of the recovered Pu is stored if necessary and the remaining Pu is used as FBR fuel and LWR-MOX fuel. In this model, it is assumed that SF of FBR is also reprocessed after cooling to provide Pu.

A new photovoltaic power (PV) module was incorporated in the most recent version of the model. The intermittent characteristics of PV power generation due to changes in weather conditions are taken into account by stochastic programming. The model considers two states of weather conditions (sunny and cloudy) and the amounts of PV power generation are calculated by node, year, season, time, and weather. Each city node has its own occurrence probability of sunny days by season. When it is cloudy, the level of PV power generation output may drop substantially as compared to a sunny day. It is necessary to ready other types of power generation to compensate for the PV output drops. As a result, this model can calculate a more realistic power generation mix. It is assumed that the effective amounts of solar radiation for each node on sunny days and cloudy days are 80 and 30 % of the theoretical maximum value, respectively. The value of the occurrence probability of sunny days for each node and each season was estimated by comparing the theoretical maximum solar radiation with the actual measurement value.

Model Simulation

Simulation Assumptions and Settings

Table 5.1 shows data on nuclear fuel cycle [2] and photovoltaic costs. FBR is assumed to be available after the year 2030, and PV capital cost is reduced by 2 % per annum up to the year 2050 through technological progress. The maximum electricity supply by PV is limited to less than 15 % of the electric load for each time period when it is available, and that by wind power is less than 15 % of the electricity demand of all the periods. However, if water electrolysis or electricity storage is used, the upper limits on their supply share no longer apply. Natural uranium and depleted uranium contain 0.711 and 0.2 % U-235, respectively. In this simulation,

Table 5.1 Assumed cost data

Fig. 5.2 World energy demand scenario

the energy demand scenario is given exogenously with reference to SRES-B2 (Special Report on Emissions Scenarios-B2) by IPCC (Intergovernmental Panel on Climate Change) [3]. Figure 5.2 shows the world energy demand scenario.

Here we assume two cases for model simulation. One case is the no CO2 regulation case (Base case) and the other is the CO2 regulation case (REG case). The REG Case is the scenario to halve CO2 emissions by the year 2050 for the world as a whole, and thereafter the emissions are regulated so that atmospheric CO2 concentration is maintained at a level avoiding some 2 °C increase in the average global temperature from pre-industrial levels. Furthermore, in the REG case the developed countries (high-income OECD countries) are assumed to reduce CO2 emissions by 80 % compared with 2,000 levels.

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