Taking the Guesswork Out of Decarbonizing Pulp and Paper Mills

Over the past decade, the pulp and paper industry has made significant strides to improve the sustainability of its forestry practices and mill operations. Today, around two-thirds of the power and steam consumed in mills is produced via “circular” practices, including the combustion of byproduct materials like black liquor, solids, and other rejects. Waste heat recovery (WHR) systems are also common and reduce the need for unnecessary auxiliary heating via boilers.

Even with the industry’s growing focus on efficiency and the environment, most mills still rely heavily on fossil fuels to meet many of their power and steam requirements (either through onsite generation or external power and steam purchases).

Supplemental energy production accounts for roughly 15 percent and 23 percent of the total operating costs for virgin pulp mills and paper production lines, respectively^1,2. It also contributes to a substantial portion of the industry’s carbon footprint. In the US alone, an estimated 31.2 million metric tons of CO₂e emissions from mills are attributed to supplemental energy production³.

Improving the energy efficiency of processes inside mills and the energy systems used for powering operations is essential for reducing overall plant costs and meeting near- and long-term emissions targets. However, with many technologies and optimization strategies available, decision makers often need more certainty when planning their capital projects.

Siemens Energy’s model-based Energy System Design (ESD) approach can help remove the guesswork associated with decarbonization investment decisions by helping stakeholders identify the optimal combination of technologies and operating strategies.

WEIGHING OPTIONS FOR PLANT MODERNIZATION

While the pulp and paper industry has made real progress in improving efficiency and sustainability in recent years, significant opportunities still exist to reduce the energy consumption of core processes. Figure 1 shows the energy usage of industry-standard technology against state-of-the-art technology available today and the ultimate thermodynamic minimum for the most energy-intensive processes inside pulp and paper mills. The improvement potential adds up to a total opportunity of 48 percent energy savings over the industry standard.

Reliance on historical practices and increasingly cheap and available carbon-intensive fuel sources, such as natural gas, has slowed the widespread adoption of modern, energy-efficient technologies. However, investing in improving these areas is unavoidable as regulators, investors, and the public’s expectations to decarbonize operations continue to grow.

At the same time, government programs like the US Inflation Reduction Act (IRA) and the EU Green Deal Industrial Plan have begun to incentivize the implementation of “green” technologies via investment and production tax credits. This has created opportunities for scope 1 and scope 2 emissions reductions through several strategies, including:

• Hybridization of power systems (i.e., integration of renewable energy).
• Substituting coal with biomass and natural gas as the supplemental fuel source.
• Replacing traditional boilers with combined heat and power units.
• Electrifying heat through electrically powered boilers, heat pumps, Turbo Heater technology, etc.
• Upgrading recovery boiler units to gasification with combined cycle technology.
• Steadily improving heat recovery from pulp and paper-making processes, including de-inking, drying, cooking, etc.

USING A MODEL-BASED ESD APPROACH

With a wide range of emissions-reducing technologies now available, stakeholders often need help identifying which decarbonization investments to make when planning capital projects. A strategy or technology that delivers a high return on investment for one site may not be suitable for another.

Siemens Energy ESD can help ensure that mills implement the right technologies and operating strategies for energy system expansions, upgrades, and modernizations. ESD is a model-based engineering optimization analysis that selects and sizes energy conversion and storage assets to supply thermal and electrical power to a mill or individual paper production line. It supports the optimization of energy systems for mills by evaluating the following inputs:

• Energy system loads: electrical, steam (high/intermediate/low pressure), hot water, or chilled water demand on an hourly or sub-hourly basis.
• Options for purchasing and/or selling commodities, including electricity, natural gas, and other residuals.
• Potential for integration with local renewable sources, such as solar PV arrays or wind turbine generators.
• Local climate conditions to account for asset impacts such as gas turbine or chiller performance.
• Existing mill assets for potential integration within the energy system design.

Siemens Energy also works closely with customers to understand their technology preferences, the study’s overall objective, and what constraints must be considered. While most customers seek energy systems with a minimum total cost of ownership, ESD studies can also target lower carbon emissions, primary energy use, energy-system-specific water consumption, or any combination of these.

Once the customer’s energy needs, targets, and site-specific boundary conditions are thoroughly understood, a collection of energy conversion and storage technologies is defined and modeled regarding performance and cost. Each technology is then included as an option within an optimization model. The model evaluates different collections of assets, including their interconnections, to identify the most competitive energy system and asset dispatch strategy for powering the mill.

Because each study input is subject to uncertainty, a collection of scenarios is strategically defined. A few parameters are then selected to inform sensitivity analyses, which help identify the most robust energy system design against a mill’s requirements, targets, and the uncertainty of future information (e.g., the price of electricity).

REAL-WORLD ESD APPLICATION

Siemens Energy performed an ESD study for a paper mill considering expanding its production capacity by installing a new paper line. The additional electrical and steam demand was estimated at 40 MWe and 85 MWth, respectively. The customer was investigating onsite generation to improve power and steam supply security and to take advantage of existing tax credit opportunities.

Siemens Energy was tasked with producing turnkey solutions for power and steam, including the lowest-cost approach and options for maximizing carbon emissions reductions, and associated cost profiles. The ESD study began by establishing a reference case to demonstrate the capabilities of Siemens Energy’s modeling tools and to establish a baseline for comparing other energy system designs.

The customer’s originally proposed energy system design used a gas boiler and a combined-cycle power plant to provide steam and power to the new paper machine. The combined cycle power plant included a gas turbine engine with an auxiliary burner, a heat recovery steam generator, and a high-pressure (HP) turbine. The gas turbine and HP turbine would connect to generators to produce electricity. A grid connection facilitated the purchase of low-cost electricity and its potential sale back to the utility.

The reference system was modeled using Siemens Energy’s optimization tool and verified to be within 0.2 percent of the customer’s expected performance based on the new paper machine’s loads, assets’ performance, and costs. Once verified, the energy system model was adapted to represent the prospective production line’s expected electrical and steam loads.

Having established the reference case, a set of energy conversion and storage technologies was defined and modeled concerning performance and cost. The complete collection of design options is shown in Fig. 2.

The optimization environment was first used to identify the lowest-cost system by comparing many combinations of the available assets, their interconnections, and their operation. An additional constraint ensured that a minimum amount of backup steam capacity was always available across the energy system. The analysis considered uncertainty in inputs, such as electricity prices, and optimal dispatch strategies for each asset.

Overall, the cost optimization study identified energy system designs that consistently outperformed the original reference design by reducing cost and carbon emissions by an average of 17 percent. In one considered future scenario, an alternative design offered cost savings of 22.1 percent while emitting 26.8 percent less CO₂ than the reference system.

The design shown in Fig. 3 offered the estimated lowest cost, second lowest CO₂ emissions, and average standard deviation across all scenarios, making it a robust energy system against all future scenarios.

After identifying the design with the lowest total cost of ownership, the complete superstructure shown in Fig. 2 was re-optimized to find the lowest-cost energy system design across a series of progressively more aggressive constraints on the maximum carbon emissions allowed.

Modern technologies, including battery energy storage, a solar array, and a small amount of low-carbon fuel were required to reduce the carbon emissions of the lowest-cost system design by 10 percent. This led to a slight increase in overall costs, which can be seen visually in Fig. 4 by moving down (lower CO₂ emissions) and to the right (higher cost).

Adding a more advanced solar array and flue gas waste heat recovery using a heat pump were identified as ways to further reduce the system’s carbon emissions. Replacing natural gas with clean fuel, such as green hydrogen, would be necessary to eliminate the system’s carbon emissions completely.

While these results are specific to the mill’s unique boundary conditions and requirements, they illustrate the value an ESD study can provide when planning for decarbonization at the mill or fleet level.

INCORPORATING POWER INTELLIGENCE

Once a design has been implemented, mills can explore how to leverage data from energy assets to increase plant reliability and uptime and continuously reduce energy consumption per unit produced. The mill’s power management system (PMS) is critical in this regard, as it serves several vital functions, including advanced switching and monitoring, generation management, and load-shedding for black-out prevention. These functions are crucial to balancing power generation and the electrical load consumed.

For example, Siemens Energy’s Power Intelligence PMS can integrate and control the different energy producers (e.g., gas turbines, solar arrays or wind turbines, batteries) and auxiliary systems (e.g., compressors, heat pumps, electrolyzers, etc.) within a mill.

The PMS increases the overall level of automation in power generation and electrical power distribution, thereby facilitating the work of plant operators and ensuring overall availability. In addition, it helps minimize the effect of power generation and grid supply outages on paper production. Power Intelligence also supports plant energy managers with user-friendly dashboarding and holistic, automated reporting to ensure complete transparency on energy consumption and carbon footprint reductions. This helps track progress toward ESG targets.

A HOLISTIC APPROACH TO DECARBONIZATION

Historically, pulp and paper mills have purchased and commissioned energy assets for a single purpose. Improvements to the overall mill system have then logically proceeded by upgrading the efficiency of each asset. While this method can deliver incremental cost and emissions reductions, achieving the lowest possible total cost of ownership and carbon intensity per unit of production requires a more holistic approach that considers the performance of each asset and its interplay within the collective energy system.

Siemens Energy’s model-based ESD methodology supports total plant efficiency by delivering concepts for energy system solutions, complete with technology selection, sizing, and operation within one integrated optimization procedure. This helps eliminate the guesswork associated with planning capital projects by helping stakeholders understand the actual costs of decarbonizing their mills.

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