DREAM is a software development project backed by hardware and artificial intelligence. We made partnership with hardware manufacturers, utility companies, universities and specialist of the sector.
Onur Energy, a licensed energy service company, is recognized in energy services and software dev. with 50+ various efficiency projects including energy management, auditing, certification, baselining, measurement as well as EU 7th FP funded BRICKER project aiming min 50% reduction in building energy demand using both renewable energy and efficiency measures. Moreover, to expand our AI skills, we're getting academic support from science people with patents in the topic.
Our D.R.E.A.M is the orchestration of the power supply & demand by automatically shifting, scheduling or shedding peaks to minimize economic losses, to maximize grid efficiency and to reduce involved GHG emissions, by the help of AI, IoT and smart data.
Increasing utilization of distributed energy resources, renewable energy, electric vehicles, changing customer needs, and electrification of more systems makes it harder, to close the gap between supply and demand efficiently. An overloaded grid causes more losses in generation, transmission and distribution. Inefficiencies add up and cause heavier costs to operate. Moreover, depending on the country’s energy generation assets, handling high demand peaks typically require more fossil fuels as more natural gas and coal plants start to operate. Thus, directly account for more green house gas emissions and a dirty grid.
D.R.E.A.M. platform is one of the important part of electric grids. Increasing share of distributed energy generation resources blurring traditional boundaries between generation, transmission and distribution. Smart Grid getting these all points to be communicated, collaborated, monitored and managed ready. Significant GHG emission will be observed due to have better central and building energy managements.
DREAM functionality can be divided into demand-side management (DSM) and continuous energy performance monitoring (CEPM). DSM begins with estimation. Inner temperature, humidity, VOCs, luminance and historical consumption trends give day ahead consumption estimation by deep learning algorithms. Decision process, with the combination of these estimations and electrical market prices, actuates embedded smart load manager (eSLM) to reduce peak power demand, by shifting, dimming or shedding of electrical loads. Furthermore, this process determines the amount of energy will be purchased from the market. Machine learning based CEPM function can be described as long term live monitoring that can detect consumption anomalies and inefficiencies in building automation system (BAS). Thus allowing discovery of practical energy conservation potentials and reporting optimal operation parameters. DREAM system consists of DSM, CEPM eSLM modules and integrates them using best business practices.
our best values
our team
Onur Günduru
Artificial Intellegence
Ferit Deniz Güner
Server Administration
Onur Çay
Energy Systems
Hakan Karaağaç
Web Development
Emre Yaman
Energy Systems
Abdullah Atilla
Energy Systems
