Fossil Fuel-fired Power Plants Research Articles

CFD simulation of a circulating fluidized bed carbon capture system using a solid-supported amine sorbent

Carbon capture, utilization, and sequestration (CCS) is one of the key technologies to reduce the emission of carbon dioxide, including that from exiting flue gas of fossil fuel-fired power plants. In this study, the two-fluid model approach was used to simulate the hydrodynamics of the entire circulating fluidized bed (CFB) loop of the integrated carbonation and regeneration sections using the mass and momentum equations and constitutive relations for both the gas and solid phases. Then, the verified models of the non-reactive simulation of the CFB loop were combined with species, energy equations, and carbonation regeneration rate of reactions for both phases to simulate the entire circulating fluidized bed carbon capture unit. The predicted extent of CO2 capture in this system showed the potential of continuous carbon capture using amine-based solid sorbents through the circulating fluidized bed CO2 capture unit.

Scope of conceptual development of Resilient supercritical Light water-cooled reactor (SCWR-R)

The research and development (R&D) of Supercritical Light Water-cooled Reactor (SCWR) has been based on the matured Generation III light water-cooled reactor (LWR) technology and the supercritical fossil fuel-fired power plant (SC-FPP) technology. The plant concept has unique features such as the simple and compact plant system and the high thermal efficiency. Currently, the Japanese concepts are being further developed at Waseda University with focuses on improving resilience of SCWR. This study proposes and presents the overall scope of the new Resilient SCWR (SCWR-R) concept with focuses on two viewpoints: (1) SCWR can utilize variety of different core designs ranging from thermal to fast spectrum for multi purposes (e.g., Pu breeding, Minor Actinide burning) with the same plant system to respond to different fuel cycle needs; (2) severe accident management of SCWR-R can be developed with the combination of IVR and PCV with S/C to minimize the PCV internal contamination by radioactive materials, which should greatly reduce post-severe accident management. To establish the SCWR-R concept, the multi-level physics simulation methodology is currently being developed to evaluate the debris criticality, cooling and radioactive aerosol management during the severe accident.

Retirement of US fossil fuel-fired power plants will increase water availability

Nearly two-thirds of fossil fuel-fired electricity generation capacity in the United States is expected to reach its typical end of life by 2035. While the closure of fossil fuel-fired power plants will help advance decarbonization goals, the cessation of water use for fossil fuel-fired power plant cooling - the largest water user in the US - will also impact the nation’s water resources. We assess when, where, and how much water will be made available upon the expected retirement of the nation’s nearly one thousand fossil fuel-fired power plants by combining a lifespan-based model of fossil fuel-fired generator retirements for the US fossil fuel-fired electricity generation fleet with a national-scale hydrologic model. We show that annual water withdrawals and consumption of fossil fuel-fired power generators will be significantly curtailed (85 % and 68 % reduction, respectively) by 2035 if these generators follow their typical retirement timeline. Most rivers with fossil fuel-fired power plants diverting and/or discharging water will have a net increase in annual streamflow after plant retirement (maximum decrease of 2 %, maximum increase of 57 % by 2050), with the most pronounced increases occurring in the summer months. The retirement of fossil fuel-fired power plants will lead to a large relative change (>5%) in streamflow at least one month per year by 2050 in 31 subbasins. The retirement of power generators was shown to produce noticeable streamflow impacts up to hundreds of kilometers downstream. By the retirement of the last US fossil fuel-fired power generator, 2.6 billion m3 of water that was once consumed by these power plants could be made available for other uses. In addition to the global benefits of reduced greenhouse gas emissions, the notable increases in streamflow and water availability in many US rivers due to the retirement of fossil fuel-fired power plants could benefit local water users and ecosystems.

Mathematical model of a power boiler operation under rapid thermal load changes

Due to the current need for coal-fired power units to cooperate with renewable energy sources, they should be characterized by a high flexibility of operation. An in-house mathematical model of a natural circulation power boiler was developed to analyse whether such cooperation is possible. A new method to simulate the heating of several surfaces located parallel in one flue gas duct is proposed. The correctness of the results obtained using the developed model was verified experimentally. A test was performed in a fossil fuel-fired power plant involving a rapid increase in the steam mass flow rate at the boiler outlet. The model verification consisted of comparing the measured and computed temperature and mass flow rates of the fluids at several boiler locations. To estimate the accuracy of the results obtained using the developed model, relative errors and root-mean-square errors were calculated. The small values of these errors indicate the correctness of the results obtained with in-house developed computation methods. The mathematical models presented in this study can be used in power unit simulators. In particular, they can be applied to create in-house models of other power boilers intended for cooperation with renewable energy sources under fast-changing loads.

Comprehensive evaluation of electricity generation and emission reduction potential in the power sector using renewable alternatives in Vietnam

The electricity generation in developing countries is primarily fossil fuel-oriented, leading to substantial air and greenhouse gas (GHG) emissions. It is projected that Vietnam's GHG emissions will be increased significantly by 2030 due to heavy reliance on fossil fuel-fired power plants in rapid economic development. This study projected and evaluated the benefits of adopting green and renewable sources (i.e., municipal solid wastes (MSW) and solar power) in terms of its electricity generation and emission reduction (in CO2e) in 2030. The Life cycle assessment (LCA) was adopted to investigate the potential emission reduction per unit of electricity generation (kg CO2e/ kWh) from the waste-to-electricity process under different operational conditions (i.e., collection, operation, and disposal). The results show that for future solar power generation, 9557 GWh of electricity with 8219 Gg CO2e of GHG emission saving was projected in 2030 under the average estimation scenario, while for waste-to-electricity, 12,991 GWh of electricity with 4910.5 Gg CO2e saving was projected. Overall, the results illustrate appreciable GHG emission savings from adopting green and renewable energy practices. It sets out a good example for developing countries who are seeking ways of curbing their growing GHG emissions to combat global climate change. It should be aware that although a considerable emission reduction in the thermal power sector is anticipated through adopting renewable and green alternatives, it is still important for the Vietnam government to limit or stop the growth of fossil fuel-fired power plants (especially for coal-fired) for the future environmental sustainability.

Insight and Comparison of Energy-efficient Membrane Processes for CO2 Capture from Flue Gases in Power Plant and Energy-intensive Industry

Membrane systems for CO2 capture have become increasingly attractive due to their higher energy efficiency, smaller footprint, and lower environmental impact. However, membrane systems should be operated at the optimal condition for a given separation scenario to achieve a significant cost-reduction benefit. This work paid particular attention to the insight of membrane system design and comparison of different membranes for various post-combustion CO2 capture scenarios. The four membranes demonstrated at pilot scale have been investigated for carbon capture in the cement factory and fossil fuel-fired power plants, and the specific cost of <20 $/tonne CO2 captured for both Polaris and PolyActive membranes were found in the scenarios where the flue gases contain high-content CO2 of >13 vol.%. The membrane units with an estimated footprint of fewer than 7 standard 40-foot containers can be realistically installed in a cement plant. It is recommended that the deployment of membrane systems for CO2 capture should be prioritized in the energy-intensive industries due to a relatively smaller gas volume to be processed compared to power plants. Moreover, membrane systems are better to be operated at a moderate CO2 capture ratio of 70-80 % and pursuing a very high capture ratio of 90 % will not be economically beneficial.

Dry cooling retrofits at existing fossil fuel-fired power plants in a water-stressed region: Tradeoffs in water savings, cost, and capacity shortfalls

This study investigates the performance, cost, and generating capacity impacts of switching from wet cooling towers to dry cooling systems to reduce the consumptive water use at existing fossil fuel-fired power plants in a water-stressed region. Retrofit analysis of dry cooling is conducted on a unit-by-unit basis for both coal-fired and gas-fired power plants. Unit-level results are then aggregated to the regional level. Based on regional averages, retrofitting dry cooling systems in lieu of wet cooling towers decreases total annual plant water consumption at existing coal- and gas-fired power plants by 93% and 100%, respectively, while increasing the levelized cost of electricity generation by approximately 12% and 18%, respectively. Based on a nominal regional water price, this cost increase corresponds to an average cost of consumptive water savings of $2.5 and $5.9 per cubic meter of water saved at coal and gas plants, respectively, if retrofit difficulty is minimal. Over the course of a year, the change in monthly net regional generating capacity from dry cooling retrofits exhibits a seasonal pattern, with the largest shortfalls occurring in July. The average monthly reduction in net capacity is estimated at 0.7% and 1.2% of the regional nameplate capacity for coal- and gas-based plants, respectively. Dry cooling retrofits thus lead to tradeoffs in water savings, cost, and capacity shortfalls, which vary with power plant characteristics. The tradeoffs identified here can fill existing knowledge gaps to better inform electric power industry water management policies, planning, and decision-making in water-stressed regions.

The effect of fossil fuel-based electricity plant location on property values: evidence from Australia

ABSTRACT This article investigates the effect of fossil fuel-fired power plant locations on the value of neighbourhood properties in the state of New South Wales, Australia. Fossil fuels account for a significant proportion of electricity generation in Australia. Thus, there are growing community concerns regarding the possible negative environmental effects of these power plants given the high levels of emissions produced by these plants. Such concerns could potentially impact on property values. We use a comprehensive dataset with the exact location of each property to estimate the effects of existing fossil fuel-fired power plants on the value of neighbourhood properties. We use spatial econometric models to estimate these effects with controls over several property characteristics and the type of power plant. Our results suggest that coal-fired power plants have significant negative effects on property values within a specific radius. These effects are likely to be lower but still negative for properties in the vicinity of gas-fired and gas reciprocating power plants.

Overcoming Metastable CO2 Adsorption in a Bulky Diamine-Appended Metal-Organic Framework.

Carbon capture at fossil fuel-fired power plants is a critical strategy to mitigate anthropogenic contributions to global warming, but widespread deployment of this technology is hindered by a lack of energy-efficient materials that can be optimized for CO2 capture from a specific flue gas. As a result of their tunable, step-shaped CO2 adsorption profiles, diamine-functionalized metal-organic frameworks (MOFs) of the form diamine-Mg2(dobpdc) (dobpdc4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) are among the most promising materials for carbon capture applications. Here, we present a detailed investigation of dmen-Mg2(dobpdc) (dmen = 1,2-diamino-2-methylpropane), one of only two MOFs with an adsorption step near the optimal pressure for CO2 capture from coal flue gas. While prior characterization suggested that this material only adsorbs CO2 to half capacity (0.5 CO2 per diamine) at 1 bar, we show that the half-capacity state is actually a metastable intermediate. Under appropriate conditions, the MOF adsorbs CO2 to full capacity, but conversion from the half-capacity structure happens on a very slow time scale, rendering it inaccessible in traditional adsorption measurements. Data from solid-state magic angle spinning nuclear magnetic resonance spectroscopy, coupled with van der Waals-corrected density functional theory, indicate that ammonium carbamate chains formed at half capacity and full capacity adopt opposing configurations, and the need to convert between these states likely dictates the sluggish post-half-capacity uptake. By use of the more symmetric parent framework Mg2(pc-dobpdc) (pc-dobpdc4- = 3,3'-dioxidobiphenyl-4,4'-dicarboxylate), the metastable trap can be avoided and the full CO2 capacity of dmen-Mg2(pc-dobpdc) accessed under conditions relevant for carbon capture from coal-fired power plants.

Optimizing regional electricity trading with Carbon Emissions Pinch Analysis

The global effort to decarbonize electricity production requires the concurrent phaseout of fossil fuel-fired power plants coupled with the installation of new renewable energy capacity. The requirement for the latter capacity may be prohibitive in cases where deep greenhouse gas emissions cuts are sought. Electricity trading among countries provides an opportunity to aggregate electricity sources and demands and reduce incremental new renewable energy generation. Carbon emissions limits of each country can be met if a renewable energy certification system is in place. In this work, modified Carbon Emissions Pinch Analysis (CEPA) approaches were developed to determine the minimum renewable energy target for a group of countries with an electricity trading agreement. CEPA is implemented here both graphically and via the Automated Targeting Model (ATM). The effectiveness of this approach for carbon-constrained energy planning is illustrated using three case studies, which include a case study based on countries in the Association of Southeast Asian Nations (ASEAN). The case study results show that electricity trading can reduce new aggregated renewable energy capacity by 9 TWh. Furthermore, the case studies demonstrate reduced investments in renewable energy generation capacity and avoiding energy assets from being stranded in some cases.

Energy efficiency of power plants meeting multiple requirements and comparative study of different carbon tax scenarios in Thailand

The most recent power generation policy adopted by the government of Thailand focusses on three different areas: security, to ensure a stable power supply; economy, to ensure that the costs associated with implementation of facilities is appropriate; and ecology, to reduce environmental emissions and social impacts. In order to address these requirements, this study proposes a practical model modification for assessing the energy efficiency of power plants. Specifically, stochastic frontier analysis (SFA) with inefficiency effects was applied to both renewable energy and fossil fuel-fired power plants in Thailand. The empirical results showed that power plant capacity was positively correlated with plant efficiency, and that plant age was negatively correlated with efficiency. In addition, in terms of efficiency scores, renewable power plants tended to be 7.13% more efficient than fossil-fuel plants, and base-load power plants were 9.44% more efficient than peak-load plants. In addition, the efficacy of four different carbon tax scenarios and their effects on the technical efficiency of power plants were evaluated. The results of the tax-rate analysis demonstrated that even low carbon taxes (e.g., 1 USD/tCO2e) can encourage the notable cleaner energy system.

The mutual benefits of renewables and carbon capture: Achieved by an artificial intelligent scheduling strategy

Renewable power and carbon capture are key technologies to transfer the power industry into low carbon generation. Renewables have been developed fast, however, the intermittent nature has imposed higher requirement for the flexibility of the power grid. Retrofitting carbon capture technologies to existing fossil-fuel fired power plants is an important solution to avoid the “lock-in” of emissions, but the high operating costs hinders their large scale application. The coexistence of renewable power and carbon capture opens up a new avenue that the deployment of carbon capture can provide additional flexibility for better accommodation of renewable power while excess renewables can be used to reduce the operating costs of carbon capture. To this end, this paper proposes an artificial intelligence based optimal scheduling strategy for the power plant-carbon capture system in the context of renewable power penetration to show that the mutual benefits between carbon capture and renewable power can be achieved when the carbon capture process is made fully adjustable. An artificial intelligent deep belief neural network is used to reflect the complex interactions between carbon, heat and electricity within the power plant carbon capture system. Multiple operating goals are considered in the scheduling such as minimizing the operating costs, renewable power curtailment and carbon emission, and the particle swarm heuristic optimization is employed to find the optimal solution. The impacts of carbon capture constraint mode, carbon emission penalty coefficient, carbon dioxide production constraints and renewable power installed capacity are investigated to provide broader insight on the potential benefit of carbon capture in future low-carbon energy system. A case study using real world data of weather condition and load demand shows that renewable power curtailment can be reduced by 51% with the integration of post-combustion capture systems and 35% of total carbon emission are captured by the use of excess renewable power through optimal scheduling. This paper points out a new way of using artificial intelligent technologies to coordinate the couplings between carbon and electricity for efficient and environmentally friendly operation of future low-carbon energy system.

Duck curve leveling in renewable energy integrated grids using internet of relays

Power grids are undergoing deregulation, privatization, and decentralization worldwide. The smart grid allows the integration of clean power renewable energy technologies to the utility grid through mini, micro, and nano grids. Conventional centralized power grids used to rely on fossil fuel-fired power plants which are being replaced worldwide with solar, wind, small hydro, geothermal, biomass, wave, and alternative energy technologies. Installed solar and wind power generation capacity has surpassed 1300 GW in 2020. Solar and wind powers rise during the day and fall during the evening. Consumer demand increases steadily during the evening and peaks after sunset when solar generation becomes zero and wind power falls substantially. Decentralized smart grid faces duck curve limitation on the integration of renewable energy technologies as centralized utilities used to face the peak-hours issue. Smart grid operators have no effective solution of load peaking after sundown except keeping fossil fuel-fired plants on standby to ride through the duck curve. We present a solution to the duck curve problem by integrating smart load shedding devices in micro and nano grids to adjust their demand frugally during peak hours to support the national grid. Information and communication (ICT) technologies that enabled the internet of things (IoT) have been attempted to facilitate smart load shedding in nano grids. ICT enabled voltage transformers (VT) and current transformers (CT) supply signals to heuristic rules based multifunction smart relaying system. Smart meters, instrument transformers, and status monitoring field devices generate a massive amount of data. The research designed an IoT and LabVIEW based software platform to carry out demand-side management. Under frequency (UF) and under-voltage (UV) relaying functions were used to conduct load shedding in nano grids. This nanoscale demand-side management experiment paves the way to ride through utility-scale duck curve setback. This PT/CT data based economic solution performs at nanoscale same as ABB PML 630 load shedding controller. This UF and UV relaying based multifunction relay starts shedding loads when frequency falls below <1% and voltage below 10% of rated values. Our load shedding scheme has successfully functioned on nanoscale 5 kW system. The future study section proposes to integrate big data technologies in-home energy management system (HEMS) through extract, transform and load (ETL) pipeline to import data from PT/CT and circuit breakers (CB) integrated smart meter to transform it according to requirement by loading data into Hadoop “big data” processing platforms for utility-scale load management with help of day-ahead load and weather-dependent renewable power generation forecasting techniques.

Towards Defining Reasonable Minimum Composition Thresholds – Impacts of Variable CO2 Stream Compositions on Transport, Injection and Storage

The collaborative project “Impacts of impurities in CO2 streams captured from different emitters in a regional cluster on transport, injection and storage (CLUSTER)” aimed to set up recommendations on how to define “reasonable minimum composition thresholds” that CO2 streams should meet when accessing CO2 transport pipeline networks. Within CLUSTER, we investigated potential impacts of CO2 streams with different and temporally variable compositions and mass flow rates along the whole CCS chain. Investigations included, amongst others, impacts on: • corrosion of pipeline steel, • pipeline network design and related transport costs, • alteration of well bore cements, • pressure development and rock integrity, • geochemical reactions, and • petrophysical and geomechanical rock properties. All investigations are based on a generic CCS chain scenario. In this scenario, CO2 streams are captured from a spatial cluster of eleven emitters and collected in a regional pipeline network. Emitters comprise seven fossil fuel-fired power plants equipped with different capture technologies, two cement plants, one refinery and one integrated iron and steel plant. In total, 19.78 Mio t CO2 (including impurities) are captured in the emitter cluster annually. The combined CO2 stream is transported in a trunk line with a length of 400 km (100 km of these offshore) and is injected into five generic storage structures. The storage reservoirs are saline aquifers of the Buntsandstein. The investigations revealed beneficial and deteriorating impacts of different impurities and combinations thereof. Overall, no fundamental technical obstacles for transporting, injecting and storing CO2 streams of the modelled variable compositions and mass flow rates were observed. Based on the results, the CLUSTER project team recommends not to define “minimum composition thresholds” for CO2 streams as strict threshold values for each individual impurity in the stream. Instead, CO2 stream compositions and variabilities for specific CCS projects should be constrained with regard to a set of parameters including i) the overall CO2 content, ii) maximum contents of relevant impurities or elements, iii) acceptable variability of CO2 stream composition, and iv) impurity combinations to be avoided.

A Modelling Framework for the Conceptual Design of Low-Emission Eco-Industrial Parks in the Circular Economy: A Case for Algae-Centered Business Consortia

This article describes a unique industrial symbiosis employing an algae cultivation unit (ACU) at the core of a novel eco-industrial park (EIP) integrating fossil-fuel fired power generation, carbon capture, biofuel production, aquaculture, and wastewater treatment. A new modelling framework capable of designing and evaluating materials and energy exchanges within an industrial eco-system is introduced. In this scalable model, an algorithm was developed to balance the material and energy exchanges and determine the optimal inputs and outputs based on the industrial symbiosis objectives and participating industries. Optimizing the functionality of the ACU not only achieved a substantial emission reduction, but also boosted aquaculture, biofuel, and other chemical productions. In a power-boosting scenario (PBS), by matching a 660 MW fossil fuel-fired power plant with an equivalent solar field in the presence of ACU, fish-producing aquaculture and biofuel industries, the net CO2 emissions were cut by 60% with the added benefit of producing 39 m3 biodiesel, 6.7 m3 bioethanol, 0.14 m3 methanol, and 19.55 tons of fish products annually. Significantly, this article shows the potential of this new flexible modelling framework for integrated materials and energy flow analysis. This integration is an important pathway for evaluating energy technology transitions towards future low-emission production systems, as required for a circular economy.

Integrated forward/reverse logistics thin-film photovoltaic power plant supply chain network design with uncertain data

Unique features of solar energy, such as the low cost of operation and low pollution, make photovoltaic power plants attractive. Despite the advantages of these power plants, such as low cost of operation and operating without pollution, their high establishment cost compared to that of the conventional fossil fuel-fired power plants prevents their rapid growth. Therefore, designing and optimizing an efficient supply chain network will help to develop the photovoltaic industry. This study proposes a bi-objective model to design and optimize a thin-film photovoltaic power plant supply chain network integrating reverse logistics. The first objective minimizes the costs of supply chain network design, which optimizes decisions from suppliers to disposal centers. The second objective maximizes the efficiency of the data envelopment analysis model to find suitable locations of facilities. As there is uncertainty in electricity demand prediction and perfect foresight is not possible, a fuzzy-robust programming approach is devised to cope with the uncertain parameters. The validity and practicality of the proposed approach are investigated by a case study based on real-world data. Finally, K-Means clustering is incorporated into the model to analyze the installed photovoltaic capacity of different cities in each period. The results show that using an optimistic approach to deal with uncertainty reduces the total cost by 20% in comparison with using a pessimistic approach. The results also provide helpful insights for decision-makers and policymakers in allocating and optimizing the operation of facilities by considering the real-world characteristics of the candidate locations.

Enhanced SO2 Resistance of Tetraethylenepentammonium Nitrate Protic Ionic Liquid-Functionalized SBA-15 during CO2 Capture from Flue Gas

Post-combustion carbon capture using amine-based adsorbents is a highly competitive approach to control CO2 emissions from fossil fuel-fired power plants. However, it is well-known that amine-based...

Multiobjective multi-verse optimization algorithm to solve combined economic, heat and power emission dispatch problems

This study implements a potent Multiobjective Multi-Verse Optimization algorithm to solve the highly complicated combined economic emission dispatch and combined heat and power economic emission dispatch problems. Solving these problems operates the power system integrated with cogeneration plants economically and reduces the environmental impacts caused by the pollutants of fossil fuel-fired power plants. A chaotic opposition based strategy is proposed to explore the search space extensively and to generate the initial populations for the multiobjective optimization algorithm. An effective constraint handling mechanism is also proposed to enable the population to remain within the bounds and in the feasible operating region of the cogeneration plants. The algorithm is applied to standard test functions, four test systems including a large 140 bus system considering valve-point effects, ramp limits, transmission power losses, and the feasible operating region of cogeneration units. The Pareto Optimal solutions obtained by the algorithm are well spread and diverse when compared with other optimization algorithms. The statistical analysis and various performance metrics used indicate the algorithm converges to true POF and is a viable alternative to solve the highly complicated combined economic emission dispatch and combined heat and power economic emission dispatch problems.

Thermodynamic study of solarized supercritical carbon dioxide cycle

The supercritical carbon dioxide cycle run on the utilization of carbon dioxide uses emissions from fossil fuel-fired power plants. In this study, the supercritical carbon dioxide cycle is powered by solar energy using heliostat fields. The operating range of supercritical carbon dioxide cycle permits for the integration of low-temperature cycles for effective utilization of the heat remaining unutilized in it. This paper considers the supercritical carbon dioxide cycle for its energy analysis. It aims for the optimal utilization of heat available with the exhaust from the sCO2 cycle. Results obtained based on parametric variation have been presented and analyzed here. At the turbine inlet pressure of 290 bar, the turbine inlet temperature of 700oC in sCO2 cycle and cycle efficiency is obtained as 16.56 % and specific work output is 174.6 KJ/kg of sCO2.

Fuzzy Optimization of Direct and Indirect Biomass Co-Firing in Power Plants

Co-firing of biomass in fossil fuel-fired power plants is a mature technology option for reducing greenhouse gas emissions. Up to 10 % of fossil fuel energy input can be displaced by biomass without the need for major retrofits. Co-firing may be done directly or indirectly. However, direct co-firing has the disadvantage of being less flexible with the use of different types of biomass. Indirect co-firing, on the other hand, overcomes this limitation by using a gasifier which converts the biomass into syngas and biochar. The syngas can then be used for co-firing, while biochar can be applied to soil as a form of carbon sequestration. This process stores the carbon initially fixed by biomass through photosynthesis in the soil, and results in the net transfer of part of the carbon in biomass from the atmosphere to the soil. Biochar thus acts as a negative emissions technology with potential for scale-up in the near future. The utilization of biomass for co-firing in a fleet of thermal power plants can be optimized as a carbon management network, subject to biomass availability and the presence of suitable biochar sinks. In this work, a fuzzy mixed integer linear programming model is developed to minimize net carbon emissions in such a system, taking into account parametric uncertainties in the storage capacities of the biochar sinks. It is assumed that there is the option to use direct, indirect or no co-firing in each power plant in the system. The model is illustrated using a case study.