Despite notable developments in solvent-based Post-combustion Carbon Capture (PCC) processes, the implementation of this technology in a power plant still burdens notable energy penalty mainly due to solvent regeneration. The energy penalty though varies by the type of power plant and by different techno-economic studies, is estimated to be above 20% (Khalilpour & Abbas, 2010). This results in serious reduction in power plant load.
One of the ways for power plants to reduce the profit loss, due to reduction of power load, is to schedule their carbon capture process. Considering the fact that the legal carbon capture requirements will be annual-based, a power plant would be able o choose to operate its PCC process in full capacity when the market electricity price is not high (e.g. off-peak). Contrarily, at a time with high electricity demand, the PCC process can be ramped down (or maybe shut-down) to allow maximum power generation. This strategy is very important for societies with liberated electricity markets.
In a monopoly electricity market, the government is usually responsible for investment in power plants and for satisfying the society electricity demands. In such condition, the load plan of power plants is defined by regional demand. Contrarily, in a liberated electricity market, such as in Australia, power plant operators plan their loading based on market price. This means that a combination of various factors such as weather temperature, working-day/holiday and others results in different demand and defines market electricity price (usually at every 30-minute interval). Consequently, the wholesale electricity price shows high volatility. Therefore, it is vital and economically attractive to study the dynamic behavior of power plants integrated with PCC process. This can allow power operators to analyze the complicacy of decision-making and load scheduling in tomorrow’s power plants.
In this study we present our recent simulation study of a coal-fired power plant with solvent-based PCC. The study presents results that examine the behavior of the power plant with changes in load, flue gas flowrate and/or composition, electricity demand, etc. Interesting insight is shed on the effects of dynamic behaviors of the power plant on the PCC process sizing. Overall performance of the plant is also assessed in terms of various parameters such as solvent type and key operating conditions.