Decarbonisation Technology – August 2021

Improve energy efficiency while reducing CO 2 emissions sustainably A solution that captures real-time process data can optimise furnace operations, energy losses and carbon emissions into the atmosphere

Avnish Kumar LivNSense Technologies Private Limited

T he petrochemical industry accounts oil and natural gas, and it is estimated that 60% of a plant’s energy consumption comes from furnace operations. This article focuses on the optimisation of furnace operations to achieve greenhouse (GHG) emissions reduction. While most furnaces are designed for a thermal efficiency of 70-90%, actual operating efficiencies are much lower. Plant managers are constantly challenged by operating conditions and the need for continuous optimisation due to: for 6% of the energy usage in the US. Roughly half of that comes primarily from • Deterioration in throughput over the furnace’s lifetime • Increased wastage of consumables and raw materials • Unpredictable and longer downtimes, leading to lost production and increased costs • Increased energy losses and carbon emissions As a furnace ages, these challenges exacerbate, leading to early replacement. While modern furnaces have electronics that gather data, there is little or no ability to perform real-time analytics and predict events in advance or provide predictive insights into interventions needed for optimal operation. A typical 500 KTA capacity ethylene plant consumes 30 MW hours of electrical energy per year. Even a 1% reduction in energy consumption from furnace operations will reduce millions of tonnes of emissions into the atmosphere (equivalent savings of £5 billion/year). With the World Economic Forum (WEF) driving ‘The Net-Zero Challenge’ to reduce

carbon emissions globally, LivNSense is driving the future of energy efficiency through its Cognitive Funace4.0 platform. This enables an innovative solution, CarbonSense, to improve energy efficiency while reducing CO 2 emissions sustainably and cost-effectively. Understanding furnace operations Combustion sources such as furnaces play a critical role in the process industry and require large amounts of fuel (gas, fuel oil). As a result, combustion efficiency directly influences the performance and operational costs of production facilities. Also, furnaces do not constantly operate under the design conditions, which is another major cause of efficiency issues. However, efficiency is not the only concern. Compliance with emission standards and safety are significant challenges too. Incomplete combustion occurs when insufficient excess air is supplied to burn all the fuel completely. As a result, large amounts of CO and H 2 are formed, making the burner extremely inefficient. LivNSense’s Cognitive Furnace4.0- CarbonSense solution is primarily built to leverage artificial intelligence (AI) and the Internet of things (IoT) to improve the operation of continuous process industries, such as petrochemicals, chemicals and metals. The solution captures real-time process data and generates predictive recommendations, enabling the operator to optimise furnace operations, energy losses and carbon emissions.