Energy savings in building heating systems have the largest return of investment. Radiator systems are designed to provide thermal comfort in buildings at all times. Thus, the water temperatures and mass flow are designed for full load. However, heating systems most often operate under part load, which leads to unanticipated heat losses. Also data suggests that rogue radiators are often the source of non-optimal heating system operation. Based on detailed monitoring of a heating system in a public school building, this project seeks to optimize water temperatures and massflow and capture the rogue radiators without compromising the indoor comfort. Data in cloud and optimization algorithms are handled best if the candidate is willing to learn simple web- and API-programming.
Interest in web-programming is necessary