Assessing the feasibility of using the heat demand-outdoor temperature function for a long-term district heat demand forecast Model Predictive Control of an Organic Rankine Cycle System Model Predictive Control of an Organic Rankine Cycle System

District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. Abstract Organic Rankine Cycle (ORC) waste heat recovery systems offer promising engine fuel economy improvements for heavy-duty on-highway trucks. An ORC test rig with parallel evaporators to recover both tailpipe and EGR waste heat from a 13L heavy duty diesel engine was developed and used in this work to demonstrate a novel control strategy based on Model-Predictive Control (MPC). The main control objectives for the ORC system are: (i) regulation of working fluid temperature, (ii) safe turbine operation - away from 2-phase region, and (iii) maximization of waste heat recovery. The MPC uses a built-in moving boundary evaporator model to predict future system response and generate optimal actuator reference commands. Two variants of MPC were considered in this work: an adaptive linear MPC (LMPC) and a nonlinear MPC (NPMC). Compared with the traditionally used PID controller, MPC demonstrates more accurate temperature control and improved disturbance rejection in simulation. Finally, the LMPC and NMPC controllers were implemented on the ORC test rig and showing promising initial test results. Abstract Organic Rankine Cycle (ORC) waste heat recovery systems offer promising engine fuel economy improvements for heavy-duty on-highway trucks. An ORC test rig with parallel evaporators to recover both tailpipe and EGR waste heat from a 13L heavy duty diesel engine was developed and used in this work to demonstrate a novel control strategy based on Model-Predictive Control (MPC). The main control objectives for the ORC system are: (i) regulation of working fluid temperature, (ii) safe turbine operation - away from 2-phase region, and (iii) maximization of waste heat recovery. The MPC uses a built-in moving boundary evaporator model to predict future system response and generate optimal actuator reference commands. Two variants of MPC were considered in this work: an adaptive linear MPC (LMPC) and a nonlinear MPC (NPMC). Compared with the traditionally used PID controller, MPC demonstrates more accurate temperature control and improved disturbance rejection in simulation. Finally, the LMPC and NMPC controllers were implemented on the ORC test rig and showing promising initial test results. © Ltd. Peer-review under responsibility of the scientific committee of the IV International Seminar on ORC Power Systems.