(106f) New Technology Integration Approach for Energy Planning with Carbon Emission Considerations

Authors: 
Ahmed, S., PPG
Du, J., Carnegie Mellon University
Ydstie, B. E., Carnegie Mellon University
Douglas, P. L., University of Waterloo
Elkamel, A., University of Waterloo


This paper considers the impact of new technology integration on the performance of a power grid consisting of a variety of power generation plants. As industry is confronted with the challenge of moving toward a clearer and more sustainable path of production, an approach to integrating new technologies into the existing process is needed to achieve industrial challenges. The new methodology is based on four major steps. If the improvement in the process is not sufficient to meet business needs, new technologies can be considered. Financial risk assessment and reliability risk analysis help alleviate risk of investment.

The reduction in carbon emissions is projected to be accomplished through a combination of fuel balancing, fuel switching, and switching to new technologies (carbon capture and sequestration). The fuel balancing technique is used to decrease carbon emissions by adjusting the operation of the fleet of existing electricity-generating stations. The technique of fuel-switching involves switching from carbon-intensive fuels to less carbon-intensive fuels, such as switching from coal to natural gas. Carbon capture and sequestration are applied to meet carbon emission reduction requirements. Power plants with existing technologies consist of fossil fuel stations, a nuclear station, hydroelectric stations, a wind station, pulverized coal stations, and natural gas combined cycle (NGCC) stations. Hypothesized power plants with new technologies include solar stations, wind stations, pulverized coal stations, and NGCC and integrated gasification combined cycle (IGCC) stations, with and without capture and sequestration.

The process is formulated as a mixed integer linear programming model and implemented in GAMS (General Algebraic Modeling System). The optimization model is applied to an existing Ontario Power Generation (OPG) fleet, the largest electric utility company in Ontario Canada. The goal is to meet a given CO2 reduction target while minimizing the cost of electricity. In addition, five planning scenarios are considered: a base load demand, a 1.0% growth rate in demand, a 5.0% growth rate in demand, a 10% growth rate in demand, and a 20% growth rate in demand. A sensitivity analysis study is done in order to investigate the effect of parameter uncertainties on coal price and natural gas price.

The optimization results demonstrate how to achieve the carbon emission/mitigation goal, while minimizing costs and also determining the configuration of the OPG fleet in terms of generation mix, capacity mix, and optimal configuration. Existing technologies, namely fuel balancing and fuel switching, can achieve reduction in carbon emissions by up to 40% in existing power plants for electricity demands with up to 20% growth. Carbon reductions of up to 60% can be achieved when new technologies are integrated for every scenario. Furthermore, cost of electricity decreases when new technologies are integrated in every scenario.

Sensitivity analysis results indicate that increases in coal and natural gas prices do not change the optimal generation mix and configuration.