(471g) Optimal Design and Operation of a Semi-Closed Oxy-Combustion Combined Cycle Power Plant | AIChE

(471g) Optimal Design and Operation of a Semi-Closed Oxy-Combustion Combined Cycle Power Plant


Teichgraeber, H. - Presenter, Stanford University
Brandt, A., Stanford University
Optimal design and operation of a semi-closed oxy-combustion combined cycle power plant

Holger Teichgraeber1 Adam Brandt1

1Department of Energy Resources Engineering, Stanford University, Stanford, California 94305-2220, USA

As gas turbines provide flexibility to energy systems today, in a low carbon future energy system, natural-gas-based power systems with CO2 capture may take over that role. Hence, we analyse the design and operations of an oxyfuel-based CCS system that is designed to operate flexibly on timescales of order one hour. Such a system can provide an intermediate level of supply flexibility beyond that provided by short response batteries. Such a system could also fill gaps in seasons of low renewable energy availability. (e.g., winter).

Specifically, we present optimal design and hour-to-hour operation of a flexible semi-closed oxy-combustion combined cycle power system. Our method includes co-optimization of the required air separation unit used to produce O2. Computational optimization is used to maximize net present value, including both operational and design optimization. Operating profit is increased through running the air separation unit at full capacity at times of low electricity prices, storing oxygen and running the oxyfuel-combustion combined cycle at full load in times of high electricity prices. This avoids energy-intensive air separation when the economic penalty is the greatest.

The system consists of a cryogenic air separation unit, oxygen storage facilities, a natural gas combustion turbine, a heat-recovery steam generator, a steam turbine and a CO2 compression unit. In this integrated system, all components are represented in a modular fashion using energy and mass balances. The air separation unit is modelled for operation at full capacity and partial load based on industrial data. The gas turbineâ??s, steam turbineâ??s and CO2 compression unitâ??s partial load operation are modelled based on existing literature. In order to model the oxyfuel-combustion gas turbine, the partial load gas turbine model is expanded with pure oxygen combustion and a recirculation fluid cycle. The heat recovery steam generator model is based on previous work [1]. System configuration and the sizing of various components have a substantial impact on operations and system economics.

The system in this work is able to operate flexibly and its overall operation including time-varying electricity prices is optimized. It also includes the air separation unit and an oxygen storage facility within the system boundary. Amongst all system components, the air separation unit is the least flexible and gaseous or liquid oxygen storage would be beneficial in order to provide fast ramping in case of changing electricity prices.

We maximize net present value (NPV) which is a function of design and operational decision variables. A similar optimization approach has been taken and described in previous work [2]. The design optimization is formulated as a mixed integer nonlinear programming problem. It uses the operational optimization as an inner loop in order to find the maximum NPV. This problem is solved using an algorithm that consists of Particle Swarm Optimization (PSO) and Mesh Adaptive Direct Search (MADS). The optimal operation maximizes annual profit using a Sparse Nonlinear OPTimizer (SNOPT) algorithm with multiple starting points due to the nonconvexity of the problem.

[1] Kang, Charles A., Adam R. Brandt, and Louis J. Durlofsky. "Optimizing heat integration in a flexible coalâ??natural gas power station with CO 2 capture." International Journal of Greenhouse Gas Control 31 (2014): 138-152.

[2] Brodrick, Philip G., Charles A. Kang, Adam R. Brandt, and Louis J. Durlofsky. "Optimization of carbon-capture-enabled coal-gas-solar power generation." Energy 79 (2015): 149-162.