(717c) Optimal Dispatch of Energy Systems Considering Penetration of Renewables and Power Plant Health | AIChE

(717c) Optimal Dispatch of Energy Systems Considering Penetration of Renewables and Power Plant Health


Kim, R. - Presenter, West Virginia University
Wang, Y., West Virginia University
Vudata, S. P., West Virginia University
Bhattacharyya, D., West Virginia University
Lima, F. V., West Virginia University
Turton, R., West Virginia University
The growing deployment of variable renewable energy (VRE) sources such as wind and solar, due to the rapid decrease in the cost of renewables and increase of societal and cultural pressures, has given rise to heightened concerns regarding the challenges in the integration between different fossil and renewable energy systems[1]. These challenges arise from the intermittent nature of the VRE sources, the reliability of the grid for always having to supply the demand load, and the limited alignment between wind/solar energy generation and electricity demand[2]. To cope with these challenges, fossil-fueled-based power plants may have to cycle their load more often. An increase in baseload power plant cycling may lead to operating regions with prohibitive stresses on equipment that increase the wear-and-tear and additionally may require the power plant to operate below the minimum load. One current grid operators’ response to these challenges is to restrict the usage of renewables, by reducing their power output. However, such measures are not desirable as the solar and wind VRE are known to have zero marginal costs and zero emissions to dispatch[3].

A preliminary framework[4] was introduced considering reduced-order models of fossil-fueled power plants, such as supercritical pulverized coal (SCPC)[5] and natural gas combined cycle (NGCC)[6] power plants, combined with energy storage units[7], under different penetration of renewables and stress assessment. The storage unit is comprised of sodium sulfur batteries, which are advanced secondary batteries that can be used for various power system applications. At the grid level, sodium sulfur batteries have high potential for electrical storage due to their high energy density, low cost of the reactants, and high open-circuit voltage[7]. The results of the framework implementation showed that the NGCC provided most of the flexibility and indicated a necessity towards increasing grid flexibility to accommodate higher penetration levels of VRE.

Based on the previous implementation results, in this presentation, the developed framework is enhanced to provide a more comprehensive analysis. In particular, the formulated problem for optimal dispatch considers the body stress limitation of the NGCC drum, as well as reheat and superheater temperature constraints under more challenging VRE penetration rates[8]. Additional post-optimization analyses are performed regarding stress in shell-branch connections (e.g., drum-downcomer junction) and equivalent CO2 emissions. Different VRE penetration levels and curtailment actions are also considered in this study. The obtained results are insightful and show the level of flexibility required from the plant as the grid moves forward to integrate more VRE, the stress behavior during dispatch, and the environmental performance. Ultimately, the generated ramping rates and optimal dispatch of different energy modules can be sent to a lower-level optimizer[9] and advanced model-based controllers[10].


[1] REN21 Renewable Energy Policy Network for 21st Century. Available at: http://www.ren21.net/status-of-renewables/global-status-report/. Accessed on April 16, 2018.

[2] Greening the Grid. Demand Response and Storage. Available at: http://www.greeningthegrid.org/integration-in-depth/demand-response-and-.... Accessed on April 7, 2019

[3] National Renewable Energy Laboratory (NREL), (2016). Energy Storage Requirements for Achieving 50% Solar Photovoltaic Energy Penetration in California. Technical Report NREL/TP-6A20-66595.

[4] Kim, R., Vudata, S. P., Wang, Y., Bhattacharyya, D., Lima, F.V., Turton, R., (2019). Scheduling of Baseload Power Plants and Batteries with Integration of Renewables. AIChE Annual Meeting, Orlando, FL.

[5] Zhang, Q., Turton, R., Bhattacharyya, D., (2016). Development of Model and Model-Predictive Control of an MEA-Based Postcombustion CO2 Capture Process. Industrial and Engineering Chemistry Research, 55, pp. 1292-1308.

[6] Wang, Y., Bhattacharyya, D., Turton, R., (2020). Evaluation of Novel Configurations of Natural Gas Combined Cycle (NGCC) Power Plants for Load-Following Operation using Dynamic Modeling and Optimization. Energy & Fuels, 34, pp. 1053-1070. doi: 10.1021/acs.energyfuels.9b03036

[7] Schaefer, S., Vudata, S. P., Bhattacharyya, D., Turton, R., (2020). Transient Modeling and Simulation of a Nonisothermal Sodium-sulfur Cell. Journal of Power Sources, 453, doi: 10.1016/j.jpowsour.2020.227849

[8] Kim, R., Wang, Y., Vudata, S. P., Bhattacharyya, D., Lima, F. V., Turton, R., (2020). Dynamic Optimal Dispatch of Energy Systems with Intermittent Renewables and Damage Model. In preparation for publication.

[9] Kim, R., Lima, F. V., (2020). A Tchebycheff-based Multi-objective Combined with a PSO-SQP Dynamic Real-time Optimization for Cycling Energy Systems. Chemical Engineering Research and Design, 156, pp. 180-194. doi: 10.1016/j.cherd.2020.01.020

[10] He, X., Lima, F. V., (2019). Development and Implementation of Advanced Control Strategies for Power Plant Cycling with Carbon Capture. Computers & Chemical Engineering, 121, pp. 497-509. doi:10.1016/j.compchemeng.2018.11.004