Captive Power Plant Research Articles

Optimal Dispatch of Coal-fired Power Units with Carbon Capture Considering Peak Shaving and Ladder-type Carbon Trading

In the context of the low-carbon transformation of the power system, carbon markets, and carbon capture technologies have become important means to promote energy conservation and emission reduction. The rapid development of renewable energy poses a challenge to the regulation capability of the power system, and energy storage technology is currently an important means to enhance the regulation capability of the power grid. To reduce the carbon emission level of the power system, improve the system economy and the ability to consume renewable energy, this paper proposes a multi-energy complementary system (MECS) with carbon capture power plant (IFCCPP) considering ladder-type carbon trading (LCT) and energy storage. The optimal dispatch model was developed with the objective of minimizing the overall operating cost. The results indicated that the integration of IFCCPP and LCT has better economic and environmental benefits than separate applications. The integration of the two modes can reduce the total cost by 504.33 k$ and carbon emission by 39232.63 t, which verifies the rationality of integrating the two modes. The LCT produces more significant emission reduction effects due to its higher benefits when carbon emissions are lower. The traditional carbon trading mechanism reduces 4779.88 t of carbon emissions, and LCT reduces 38574.45 t.

Considering Carbon–Hydrogen Coupled Integrated Energy Systems: A Pathway to Sustainable Energy Transition in China Under Uncertainty

The low-carbon construction of integrated energy systems is a crucial path to achieving dual carbon goals, with the power-generation side having the greatest potential for emissions reduction and the most direct means of reduction, which is a current research focus. However, existing studies lack the precise modeling of carbon capture devices and the cascaded utilization of hydrogen energy. Therefore, this paper establishes a carbon capture power plant model based on a comprehensive, flexible operational mode and a coupled model of a two-stage P2G (Power-to-Gas) device, exploring the “energy time-shift” characteristics of the coupled system. IGDT (Information Gap Decision Theory) is used to discuss the impact of uncertainties on the power generation side system. The results show that by promoting the consumption of clean energy and utilizing the high energy efficiency of hydrogen while reducing reliance on fossil fuels, the proposed system not only meets current energy demands but also achieves a more efficient emission reduction, laying a solid foundation for a sustainable future. By considering the impact of uncertainties, the system ensures resilience and adaptability under fluctuating renewable energy supply conditions, making a significant contribution to the field of sustainable energy transition.

Study on the Economic Operation of a 1000 MWe Coal-Fired Power Plant with CO2 Capture

The flexible operation of carbon capture units is crucial for the economic performance of coal-fired power plants equipped with CO2 capture systems. This paper aims to investigate the impact of electricity, CO2, and fuel prices on the economic operation of such plants. A novel economic optimization model is proposed, integrating a static model of the carbon capture system with a particle swarm optimization algorithm. A new concept, the CO2 boundary price, is introduced as a key metric for determining the operating conditions of CO2 capture units. The CO2 boundary price rises when the power load decreases due to the decline in power generation efficiency, and it also increases with rising fuel prices, as the cost of steam for CO2 capture increases. Additionally, when the objective is to meet power load demand, CO2 prices have a great influence on the operation of CO2 capture units, assuming fixed coal and electricity prices. However, when the primary goal is to maximize plant profitability, the system’s operational conditions are strongly influenced by the relative prices of electricity and CO2. The proposed optimization model and the uncovered price-effect mechanisms provide valuable insights into the economic operation of carbon capture power plants.

Decarbonization management of solvent-storage carbon capture power plant

Decarbonization management of solvent-storage carbon capture power plant

Low-carbon optimal scheduling of an integrated electricity, heat-and-gas energy system considering a biomass gas and carbon capture power plant

Abstract In light of enhancing the extraction level of biomass energy and rectifying the efficiency of integrated energy system (IES) operations in the backdrop of the “ twin carbon” policy, we present an enhanced scheduling methodology for IES incorporating biomass gas and carbon absorption power plants, addressing the constraints of linear carbon trading. Initially, an organizational blueprint for the combined exploitation of biomass-laden gas, electricity-to-gas, and carbon absorption power plants is established. Secondly, we devise a ladder-like configuration of carbon trading mechanisms to counterbalance the inadequacies of standard persistent carbon trading schemes. Subsequently, this advanced form of carbon trading is incorporated into the IES framework and is optimized using the ultimate goal of minimizing system expenditures. Lastly, evaluations across diverse scenarios demonstrate that the proposed sequential carbon trading significantly enhances the economic viability of the system, and the accompanying simulation corroborates the validity of our proposed model.

Flexibility analysis on absorption-based carbon capture integrated with energy storage

Post-combustion carbon capture in power plants is essential in reducing greenhouse gas emission. As the available heat in the plant is instable in time, it becomes a challenge to maintain the efficient operation of capture system. The lean/rich solvent storage proves to be a potential way for the capture system to keep high CO2 capture rate. However, the performance of the integrated system under different operating conditions is not fully evaluated, especially for the match criterion of lean/rich solvent process. The impact factors of single and coupled operating conditions of solvent storage still remain unclear. In this work, system performance during peak/off-peak period is first evaluated. Results indicates that heat duty, split ratio, solution concentration and absorption solvent flow rate are key factors for CO2 capture rate. Then, system performance under continuous operation is explored at the global CO2 capture rate from 0.918 to 0.978. It demonstrates that maintaining a relatively equal CO2 capture rate during peak/off-peak period efficiently improves the global CO2 capture rate, which can be achieved by adjusting flow rate and split ratio of solvent. Finally, volume and cost of integrated CO2 capture with solvent storage are compared with that of CO2 capture with heat storage. The volume of solvent storage decreases by over 69% and the cost of solvent storage decreases by over 84%, which indicates a promising application in terms of technical and economic aspects.

Efficiency improvement and flexibility enhancement by molten salt heat storage for integrated gasification chemical-looping combustion combined cycle under partial loads

Chemical-looping combustion offers a promising carbon capture technology for coal-fired power generation. Enhancing the operational flexibility and energy efficiency of such plants is crucial for achieving primary energy savings and renewable energy accommodation. In this study, the operating characteristics of an integrated gasification chemical-looping combustion combined cycle (IGCLCCC) under various loads are studied, and the deterioration mechanism of its thermodynamic performance is revealed. Further, an IGCLCCC scheme coupled with molten salt heat storage is proposed and evaluated from thermodynamic performance and operational flexibility. Study results indicate that the net efficiency of the IGCLCCC reaches 37.7% under 30% load, which is superior to those of conventional CO2 capture power plants under full load. Adopting the heat storage system significantly improves the operational flexibility and energy efficiency of the IGCLCCC by expanding its operating range from 30.0∼100.0% to 25.7∼105.3%. The equivalent round-trip efficiency of the heat storage system reaches 134.6% due to the upgrading of the thermal energy from the exhaust gas of the air turbine from original low levels to high levels driven by the exergy saving during the oxygen carrier-air reaction because of the air preheating to a high temperature.

Low-carbon economic dispatching strategy based on feasible region of cooperative interaction between wind-storage system and carbon capture power plant

The high penetration of new energy into the grid is an effective method for reducing carbon emissions. However, the randomness and uncertainty of large-scale wind power (WP) output pose challenges to the grid dispatch operation and increase the requirements for carbon emission control. This paper proposes a low-carbon economic dispatching strategy based on the feasible region (FR) of cooperative interaction between WP and flexible resources to promote the consumption of WP and reduce carbon emissions. In particular, energy storage (ES) and carbon capture power plant (CCPP) are used as a set of adjustable flexible resources, and the power FR of WP, ES and CCPP is constructed to provide a visualization reference for grid scheduling. Then, a two-stage robust optimization (RO) dispatching FR-based model considering WP consumption capacity is proposed to cope with the operational risk of WP output stochasticity for power grid. Finally, the column constraint generation algorithm (C&CG) is used to solve the problem and evaluate low carbon level in the system according to the carbon flow theory. The simulation results verified the effectiveness of the suggested approach demonstrated by the modified IEEE 39-bus and IEEE 118-bus test cases.

Carbon Neutrality Computational Cost Optimization for Economic Dispatch With Carbon Capture Power Plants in Smart Grid

To achieve carbon neutrality, reducing carbon emissions is crucial in dispatching problems in smart grid. Though renewable energy such as wind power has low carbon emissions, it suffers from random generation, which makes the thermal power necessary for a stable supply power system. To reduce carbon emissions, the thermal power plants are transformed into carbon capture power plants, which brings new challenges to economic dispatch algorithms. Besides, there are usually many constraints to keep the security operation of power systems, which incurs a large problem scale and high computational cost. Most existing methods either do not consider reducing carbon emissions, or suffer from high computational costs. In this paper, a framework for the carbon capture plants with wind power to reduce both running costs and carbon emissions is designed to support carbon neutrality. To reduce computational cost, initial-training and fine-tuning are used. A deep neural network is employed to describe the relationship between users' load and the constraints, which provides guides for finding the active constraints. Therefore, the problem scale can be significantly decreased, making the optimal dispatching strategy obtained quickly. The experimental results on real-world data show that the proposed framework can obtain the optimal strategy efficiently.

Techno-Economic Evaluation on Solar-Assisted Post-Combustion CO2 Capture in Hollow Fiber Membrane Contactors

In this study, a novel system which integrates solar thermal energy with membrane gas absorption technology is proposed to capture CO2 from a 580 MWe pulverized coal power plant. Technical feasibility and economic evaluation are carried out on the proposed system in three cities with different solar resources in China. Research results show that the output capacity and net efficiency of the SOL-HFMC power plant are significantly higher than those of the reference power plant regardless of whether a TES system is applied or not. In addition, the CEI of the SOL-HFMC power plant with the TES system is 4.36 kg CO2/MWh, 4.45 kg CO2/MWh and 4.66 kg CO2/MWh lower than that of the reference power plant. The prices of the membrane, vacuum tube collector and phase change material should be reduced to achieve lower LCOE and COR values. Specifically for the SOL-HFMC power plant with the TES system, the corresponding vacuum tube collector price shall be lower than 25.70 $/m2 for Jinan, 95.20 $/m2 for Xining, and 128.70 $/m2 for Lhasa, respectively. To be more competitive than a solar-assisted ammonia-based post-combustion CO2 capture power plant, the membrane price in Jinan, Xining and Lhasa shall be reduced to 0.012 $/m, 0.015 $/m and 0.016 $/m for the sake of LCOE, and 0.03 $/m, 0.033 $/m and 0.034 $/m for the sake of COR, respectively.

Research on Optimal Operation of Power Generation and Consumption for Enterprises with Captive Power Plants Participating in Power Grid Supply–Demand Regulation

Wind and solar power curtailment and the difficulty of peak regulation are issues that urgently need to be addressed in the process of China’s new electric power system. Enterprises with captive power plants (ECPPs) are large-capacity power consumers and producers, with significant optimization and adjustment potential on both the supply and demand sides. This paper aims to promote the active participation of ECPPs in grid supply–demand regulation and proposes an optimization model for the power generation and consumption of ECPPs based on a day-ahead, intra-day two-stage dispatching model. First, targeting demand response scenarios, mathematical models for analyzing the potential of ECPPs to participate in power grid supply–demand regulation are proposed. Then, an optimization model for ECPP generation and consumption with load regulation is established, and a two-stage dispatching model is proposed to fully mobilize the regulation flexibility of ECPPs. Finally, a robust dispatching model considering price uncertainty is established based on information gap decision theory. The case results show that ECPPs can reduce the curtailment rate in a region by approximately 9%, alleviate the peak pressure of the power grid, reduce carbon emissions by 1373.55 tons, and promote low-carbon development for themselves. Meanwhile, considering price uncertainty strengthens the risk resistance capability of ECPPs and provides a basis for their willingness to participate in supply–demand regulation.

Bidding Strategy for Wind and Thermal Power Joint Participation in the Electricity Spot Market Considering Uncertainty

As the proportion of new energy sources, such as wind power, in the electricity system rapidly increases, their participation in spot market competition has become an inevitable trend. However, the uncertainty of clearing price and wind power output will lead to bidding deviation and bring revenue risks. In response to this, a bidding strategy is proposed for wind farms to participate in the spot market jointly with carbon capture power plants (CCPP) that have flexible regulation capabilities. First, a two-stage decision model is constructed in the day-ahead market and real-time balancing market. Under the joint bidding mode, CCPP can help alleviate wind power output deviations, thereby reducing real-time imbalanced power settlement. On this basis, a tiered carbon trading mechanism is introduced to optimize day-ahead bidding, aiming at maximizing revenue in both the electricity spot market and carbon trading market. Secondly, conditional value at risk (CVaR) is introduced to quantitatively assess the risks posed by uncertainties in the two-stage decision model, and the risk aversion coefficient is used to represent the decision-maker’s risk preference, providing corresponding strategies. The model is transformed into a mixed-integer linear programming model using piecewise linearization and McCormick enveloping. Finally, the effectiveness of the proposed model and methods is verified through numerical examples.

Day-Ahead and Intraday Two-Stage Optimal Dispatch Considering Joint Peak Shaving of Carbon Capture Power Plants and Virtual Energy Storage

The anti-peaking characteristics of a high proportion of new energy sources intensify the peak shaving pressure on systems. Carbon capture power plants, as low-carbon and flexible resources, could be beneficial in peak shaving applications. This paper explores the role of carbon capture devices in terms of peak shaving, valley filling, and adjustment flexibility and constructs a virtual energy storage model utilizing various flexible loads on the demand side. Also, it proposes a joint peak shaving strategy involving carbon capture devices and virtual energy storage. Considering the predictive error characteristics of wind power and load across different time scales, this study establishes a day-ahead and intraday two-stage rolling regulation peaking model based on carbon capture power plants and virtual energy storage to fully leverage the diverse response speeds and peak shaving capabilities of various types of flexible loads. Initially, the model calculates the net load curve after implementing a demand response system, aiming to minimize the load peak–valley difference. Subsequently, within the intraday period, it seeks to minimize system operating costs by precisely allocating peak shaving resources as per demand, thus aiming for economic efficiency while ensuring the system’s peak shaving capability.

Quantification and assessment of hazardous mercury emission from industrial process and other unattended sectors in India: A step towards mitigation

Hazardous pollutants like Mercury (Hg) have emerged as a pressing challenge in recent times where the expanding industrial sector is regarded as the major source in developing country India. In this study, we are trying to identify all possible industrial sectors at district level to quantify Hg emission load across India for the year 2019 using IPCC methodology where the country-specific technological emission factors are used. We have included 5 major sectors out of which emission from coal combustion in thermal power plants accounts for 186.5 t/yr of Hg emission followed by non-ferrous metal production (88.3 t/yr), captive power plants (65.5 t/yr) and fly ash generation from various manufacturing industries (45.9 t/yr). A total of 459.4 t/yr of Hg is released into the ecosystem in 2019 with an uncertainty of ± 48%. This study also estimated that about 233 million people living in and around 10 km periphery of major industrial zones with as many as 17 million people residing near the 10 major hotspots are susceptible to hazardous Hg emissions directly or indirectly. This information would be quite useful in formulating future Hg emission control strategies in India. Environmental ImplicationsPresent study is the first-of-its-kind quantification of Hg emission load from the Industrial process and many unattended sectors over India, which will not only give an insight into potential hotspots regions across the country but also assess the population exposed to it. It will provide aid in tracking the mercury burden to match the international conventions. The findings suggest that about 233 million people are likely to be exposed to hazardous Hg emissions. It will also enlighten the government, policymakers, stakeholders and people about their mercury footprint and envision protecting the biomes and formulating future control strategies in India.

A Distributed Multi-Timescale Dispatch Strategy for a City-Integrated Energy System with Carbon Capture Power Plants

In city-integrated energy systems containing electric–thermal multi-energy sources, the uncertainty of renewable energy sources and the fluctuation of loads challenge the safe, efficient, economic and stable operation of the integrated energy systems. This paper introduces a novel approach for the operation of a carbon capture plant/CHP with PV accommodation within a city-integrated energy system. The proposed strategy aims to maximize the utilization of photovoltaic (PV) power generation and carbon capture equipment, addressing issues related to small-scale CHP climbing constraints and short-term output regulation. Additionally, this paper presents a multi-timescale optimal scheduling strategy, which effectively addresses deviations caused by PV fluctuations and load changes. This was achieved through a detailed analysis of the CHP climbing constraints, carbon capture equipment operation and real-time characteristics of PV power generation. This paper introduces a fully distributed neural dynamics-based optimization algorithm designed to address multi-timescale optimization challenges. Utilizing rolling cycles, this algorithm computes both day-ahead and real-time scheduling outcomes for urban integrated energy systems. Theoretical analyses and numerical simulations were conducted to validate the precision and efficacy of the proposed model and algorithm. These analyses quantitatively evaluate the scheduling performance of PV power generation and carbon capture CHP systems across various timescales.

Generation Expansion Planning for Solvent-Storaged Carbon Capture Power Plants Considering the Internalization of the Carbon Emission Effects

Carbon capture power plants (CCPPs) can effectively eliminate the carbon-locking effect of coal-fired power generation systems, which constitute one of the essential technical pathways to achieve low-carbon transformation of the power structure. Capable of decoupling CO2 absorption and separation in terms of time, CCPPs equipped with solvent storage have stronger operational flexibility while promoting the realization of carbon emission reduction targets. Therefore, this study focuses on the generation expansion planning of power systems containing solvent-storaged carbon capture power plants (SSCCPPs). First, a mathematical model is proposed for SSCCPPs considering new operation characteristics of power generation-carbon capture. Second, the per kilowatt-hour carbon emission coefficient (kWh-CEC) of various power plants is analyzed by life cycle assessment (LCA), and a bilateral stepped carbon trading model is established to quantify power plants' whole life cycle carbon emission effects. Third, a generation expansion planning model considering the internalization of carbon emission effects is developed to explore the benefits of planning SSCCPPs in wind-coal intensive power systems and multi-energy integrated systems. The simulation results on the modified IEEE RTS-96 system and IEEE HRP-38 system have validated the economic and low-carbon performance of planning SSCCPPs in the system.

Enhancing envrionmental sustainability via interval optimization for low-carbon economic dispatch in renewable energy power systems: Leveraging the flexible cooperation of wind energy and carbon capture power plants

In response to pressing environmental challenges, the power system is gradually developing towards a more efficient, clean, and sustainable direction. Carbon capture power plants (CCPPs) and wind power generation will play a significant role in this eco-friendly transformation. However, the high energy consumption of CCPPs and the anti-peak regulation characteristics of wind power lead to contradictions in their coordinated operation during peak shaving, restricting the system's low-carbon economic development. Aiming at the above challenges, an interval optimization method is proposed to coordinate wind power and CCPPs. Firstly, a flexible operation model of CCPPs is established, and the coordinated scheduling mechanism of wind power joint carbon capture operation and load-side demand response is introduced to optimize the system carbon emission through low carbon scheduling on both sides of the source and load. Secondly, interval numbers are used to manage the uncertainty of wind power output, and the interval-optimized scheduling model of wind power combined CCPPs is established. To solve the proposed model, the improved interval possibility method is adopted to transform the uncertain model into a deterministic one, which is solved by the CPLEX solver. Finally, the simulation outcomes using the IEEE 30-bus system framework reveal that the proposed approach significantly enhances the coordination between CCPPs and wind power. Notably, when compared to scenarios that solely focus on CCPPs, the proposed method achieves a substantial reduction in total costs by 16.67 % and decreases carbon emissions by 26.53 %. This sets a significant reference for low-carbon economic dispatch within power systems, providing key insights and foundational guidelines for future implementations, as well as novel strategies and technological support for the sustainable transformation of the power system towards lower carbon emissions.

Dynamic Stepwise Carbon Trading Game Scheduling with Accounting and Demand-Side Response

Abstract With the help of cooperative game theory, this study constructs an integrated demand response economic game scheduling model for carbon trading, aiming to maximize collective and individual benefits. The model effectively reduces the system operating cost by adjusting the electricity price to incentivize PDR-VGU output. The impacts of price demand and integrated flexible operation demand on the coordination degree of carbon trading and the optimized dispatch results under different scenarios are analyzed in depth. It is found that when considering the carbon trading mechanism, the system operating cost and carbon emissions are reduced by RMB 2,129 and 9.63 tons, and RMB 2,350 and 11.96 tons, respectively, showing a win-win situation in terms of economy and environmental protection. In addition, the energy time-shift strategy implemented in the carbon capture power plant system effectively balances the peak-to-valley difference of thermal power output, further reducing the cost.

Coordinated Low-Carbon Dispatching on Source-Demand Side for Integrated Electricity-Gas System Based on Integrated Demand Response Exchange

With the exploration of deep decarbonization around the world, the contradiction between the low-carbon operation and energy supply in energy systems has been aggravating. There is an urgent need to tap the interactive potential between source and demand sides. In view of the current lack of efficient incentive measures for low-carbon energy consumption, an integrated demand response exchange (IDRX) mechanism is proposed to promote the coordinated low-carbon dispatching on source-demand side for integrated electricity-gas system (IEGS). The value model of IDRX for emission reduction is built to measure the ability of multi-energy load aggregators (MELAs) for decarbonization, and guide the IEGS operator to trade with the appropriate MELAs. An IDRX market clearing model is established based on non-cooperative game theory to allocate the decarbonization benefits among the entities in IEGS, thereby motivating the low-carbon demand response of users. Combined with the optimal operation of carbon capture power plant and power-to-gas (CCPP-P2G) on the source side, a two-stage low-carbon dispatching model for IEGS is established. Case studies are carried out with seasonal and uncertainty scenarios to verify the effectiveness of IDRX in emission mitigation and highlight the economic benefits of the proposed low-carbon dispatching model.

Thermal economy simulation study for a carbon capture power plant with combined heat and power based on absorption heat pump technology

The Combined Heat and Power (CHP) system represents an energy-efficient and environmentally-friendly approach to energy utilization. However, in the context of the “carbon peaking and carbon neutrality” strategy, ensuring low-carbon operation of CHP systems becomes imperative. In this study, based on absorption heat pump (AHP), an extraction condensing carbon capture (EC&CC) CHP coupled system and a low-pressure cylinder zero-output carbon capture (LCZ&CC) CHP coupled system are proposed, respectively. Furthermore, under the 100 % turbine heat acceptance (THA) operating condition, a variable operating condition study of heating load and carbon capture capacity is conducted. The results demonstrate that under identical heating load, the EC&CC CHP coupled system has superior thermal economy, with an average reduction of 1011.03 kJ/kWh in heat consumption of power generation and 34.54 g/kWh in coal consumption of power generation compared with the LCZ&CC CHP coupled system; For equivalent carbon capture capacity, the LCZ&CC CHP coupled system has superior thermal economy, with an average reduction of 771.28 kJ/kWh in heat consumption and 26.35 g/kWh in coal consumption of power generation compared with the EC&CC CHP coupled system. The EC&CC CHP coupled system has lower CO2 capture heat consumption, resulting in an average reduction of 135.67 t/h in carbon capture extraction compared with the LCZ&CC CHP coupled system. This study can provide guidance for optimizing the design of carbon capture CHP coupled systems.