In this study, the load fluctuation of the main engine is considered to be a disturbance for the jacket coolant temperature control system of the low-speed two-stroke main diesel engine on the ships. A nonlinear PID temperature control system with satisfactory disturbance rejection performance was designed by rapidly transmitting the load change value to the controller for following the reference set value. The feed-forwarded load fluctuation is considered the set points of the dual loop control system to be changed. Real-coded genetic algorithms were used as an optimization tool to tune the gains for the nonlinear PID controller. ITAE was used as an evaluation function for optimization. For the evaluation function, the engine jacket coolant outlet temperature was considered. As a result of simulating the proposed cascade nonlinear PID control system, it was confirmed that the disturbance caused by the load fluctuation was eliminated with satisfactory performance and that the changed set value was followed.

As the Photovoltaic system market increases, various technologies are emerging to improve system operation efficiency. Such additional systems of the power generation system are generally referred to as ‘Balance of System’, for example a panel cooling, a panel cleaning and a panel angle adjusting apparatus. In this paper, we discuss an algorithm to calculate the target temperature of cooling in response to changes in the installation environment conditions of the power generation system so that the efficiency improvement rate target set by the user can be achieved with respect to the control method of the cooling water injection system among various panel cooling apparatuses. In order to calculate the target temperature of cooling, the output enhancement coefficient is calculated experimentally based on the temperature change according to the solar radiation condition of the PV panel, and the required reduction temperature of each irradiation condition is calculated considering the efficiency improvement rate. In addition, the efficiency improvement ratio is calculated considering the installation condition of the general power generation system without a separate control group. The thermal performance coefficient of the PV panel test body for calculating the expected temperature of the PV panel is calculated experimentally. The target temperature of cooling is calculated as the sum of the expected temperature of the PV panel and the required reduction temperature, and the injection system that tracks the target temperature by cooling water injection is constructed and compared with the power generation improvement rate and the user setting efficiency improvement rate.