Coproducing methanol and electricity provides an opportunity to balance the load from coal gasification systems. With this process, synthesis gas from the gasifier is passes over a methanol catalyst and the unreacted gas burned in a power plant. The Air Products LPMEOH process is particularly suited for once through type operations since a high methanol conversion can be achieved in a single pass through the catalyst. Biomass co-feedstocks such as sewage sludge have been considered as feeds for coal gasifiers but were not evaluated in this study.
4.8 Electric Power Generation
Two scenarios for electric power generation were developed to reflect future power plant additions and retirements. CEC modeled the mix of power generation by estimating the new power plants to have an adequate supply of resources for future demand levels. Since some fundamental changes have occurred in the electric industry, traditional resource planning methods were not used to develop the two scenarios presented in the study. The CEC’s RAM3 Model was used to evaluate supply adequacy concerns.
Multisym™ model runs were done with and without EV loads to calculate the incremental emissions (pounds per MWh) for the year 2010. Incremental results are presented for each California air basin and for other large regions of the West.
In order to determine the amount of electricity that electric vehicles may draw from power plants in the year 2010, many assumptions were made about the number of EVs that are expected to be connected to the grid, their operational efficiency and likely annual miles traveled. These assumptions were included in a simple probability model that calculates the effect of uncertainty on a range of predicted outcomes. Figure 4-3 displays results from many combinations of assumptions generated with this simple probability model. The results show that, under various combinations of assumptions, approximately 1,000 GWh is a reasonable estimate of energy needed by EVs statewide in 2010.
Figure 4-3. Projected Power Demand for EVs in 2010
3 Reliability Assessment Model developed by Albert Belostosky, Ph.D.