Economic feasibility of calcium looping under uncertainty

Abstract

An emerging calcium looping process has been shown to be a promising alternative to solvent scrubbing, which is regarded as the most mature CO2 capture technology. Its retrofits to coal-fired power plants have the potential to reduce both energy and economic penalties associated with the mature CO2 capture technologies. However, these conclusions have been made based on the deterministic outputs of the economic models that have not considered uncertainties in the model inputs. Therefore, this study incorporates a stochastic approach into the economic analysis of the retrofit of such emerging CO2 capture technology to the coal-fired power plant. The stochastic analysis revealed that levelised cost of electricity (LCOE) and specific total capital requirement were highly affected by the uncertainty in the input variables to the process and economic models. The most probable values for these key economic performance indicators were shown to fall between 75 and 115 €/MWelh, and 2100 and 2300 €/kWel,gross, respectively. Interestingly, the most probable LCOE values for the coal-fired power plant will fall between 50 and 150 €/MWelh. This indicated that the calcium looping retrofit scenario can become economically favoured, mainly due to the high economic penalties incurred by unabated coal-fired power plant associated with carbon tax. Importantly, the outputs of the stochastic economic assessment aligned well with the deterministic results reported in the literature. As the latter were generated using different sets of assumptions regarding the process and economic models, the stochastic approach to the economic assessment can minimise the impact of the model assumptions on estimates of the key economic parameters. Moreover, by indicating the probability of particular outputs, as well as ranking the model input variables according to their influence on the key economic performance, such analysis would allow making more insightful decisions regarding further funding 2 and development of the calcium looping process. Finally, use of the stochastic approach in the economic feasibility assessment enables a more profound and reliable comparison of the different calcium looping retrofit configurations, as well as benchmarking different CO2 capture technologies.

Performance analysis of a double calcium looping‐integrated biomass‐fired power plant: Exploring a carbon reduction opportunity

“…These simulation studies were carried out using the aspenONE software. The properties of flue gas, calcium sorbents, thermal oil, and organic fluid were calculated by employing Peng‐Robinson‐Boston‐Mathis (PR‐BM) as property method in the aspenONE simulation software . The biomass composition, operating conditions and system parameters used in this simulation study are shown in Tables and .…”

“…A number of successful demonstration projects on CaL all over the world proved its viability as CO 2 capture technology . Its feasibility to retrofit the existing power plants with less energy and economic penalty along with plant load flexibility makes it one of the sustainable CO 2 capture options . Since the CaL reactors operate at sufficiently high temperatures, a large part of the heat can be recovered in the integrated power plant, which reducing the energy penalty.…”

Techno-economic feasibility of power to gas–oxy-fuel boiler hybrid system under uncertainty

“…To account for the uncertainty in the input variables to the techno-economic models, the stochastic approach is implemented by following the procedure presented in Fig. 3 and described in detail elsewhere [22,24]. First, the PtG process model was developed in Aspen Plus ® and the corresponding economic model was built in MS Excel, as detailed in Section Deterministic assessment methodology.…”

“…Consideration of the uncertainty in the operating conditions at the process design stage can reduce the occurrence of the failures associated with vibration stresses and unstable operation [25e27], equipment overheating [25], and other failures associated with poor design and increased complexity [28]. By indicating the probabilities of possible outcomes, a stochastic approach to evaluation of the process performance provides a more profound insight into the investment decision-making process and may potentially lead to a different outcomes compared to the deterministic approach [24].…”

“…It has been shown to be an accurate approximation model for systems with multiple inputs and outputs [31], even for highly nonlinear systems [30,32]. It has also been shown to perform better than generic quadratic multi-variable polynomial model in approximation of nonlinear energy systems [24]. Data required to the construction of the ANN are derived from a large number of deterministic simulations in Aspen Plus ® .…”