Abstract
Natural gas is a fossil fuel that has been widely used for various purposes, including residential and industrial applications. The combustion of natural gas, despite being more environmentally friendly than other fossil fuels such as petroleum, yields significant amounts of greenhouse gas emissions. Therefore, the optimization of natural gas consumption is a vital process in order to ensure that emission targets are met worldwide. Regarding residential consumption, advancements in terms of boiler technology, such as the usage of condensing boilers, have played a significant role in moving towards this direction. On top of that, the emergence of technologies such as smart homes, Internet of Things, and artificial intelligence provides opportunities for the development of automated optimization solutions, which can utilize data acquired from the boiler and various sensors in real-time, implement consumption forecasting methodologies, and accordingly provide control instructions in order to ensure optimal boiler functionality. Apart from energy consumption minimization, manual and automated optimization solutions can be utilized for balancing purposes, including natural gas demand response, which has not been sufficiently covered in the existing literature, despite its potential for the gas balancing market. Despite the existence of few research works and solutions regarding pure gas DR, the concept of an integrated demand response has been more widely researched, with the existing literature displaying promising results from the co-optimization of natural gas along with other energy sources, such as electricity and heat.