Over the past year, Europe has experienced unprecedented energy cost volatility caused primarily by the unfolding geopolitical crisis and fueled by the consumption recovery after two years of the pandemic. The dramatic surge in energy costs is apparent when comparing the Q3 figures for 2021 and 2022. The countries that have suffered the most are those whose energy mix is skewed toward natural gas as a primary energy source. This is all part of a challenging European decarbonization plan involving industry, mobility and housing with ambitious targets for 2030-35. SOLAR TURBINES looks at the energy system as a highly integrated and interconnected whole – a network increasingly benefiting from the contribution of renewable energy, but also affected by the need to ensure its availability and stabilty.
For this reason, Solar is the primary partner for energy solutions based on latest generation turbogas integrated with SMART digital architectures operating in the big data sphere.
Powering the future through sustainable, innovative energy solutions
Digital SMART systems and energy optimization
This refers to an energy optimization system that can interface with the different energy markets (i.e. Spot, Day Ahead, Ancillary Services) that allows us to increase the efficiency of cogeneration while reducing fuel consumption and CO2 emissions. Through digitization, we can also control, along with the CHP plant, all production parameters (steam demand, electricity demand, load changes, and paper machine set-up). These parameters are then integrated with each other and the various factors exogenous to the production system, such as the cost of CO2 and hourly carbon intensity, the cost of gas and electricity, the grid frequency, and the nodal electrical load of the area to which it belongs.
The SMART concept expressly consists of this integrated approach to the internal and external world.
The energy optimization system developed by Solar Turbines can continuously monitor these parameters. If the customer decides to maximize the yield or minimize CO2 emissions, the system will suggest operational set points to achieve the target.
The optimum with Solar Turbines’ Turbogas
Solar Turbines’ energy optimization system fits within the framework of decision support systems models based on the integrated management of energy supply and use from disparate sources available in the local grid and their availability or variation. As mentioned above, it can instantly suggest the best way to operate.
For example, it will choose whether to favor the make option in electric control over thermal control or the buy option by taking supplies directly from other sources.
Of the possible solutions, it will opt for the one able to provide the company with the most significant benefit, the smallest loss or minimization of carbon intensity.