A supervisory control approach in economic MPC design for refrigeration systems

Abstract

Abstract-A model predictive control at supervisory level is proposed for refrigeration systems including distributed local controllers. Prediction of the electricity price and outdoor temperature are assumed available. The control objective is to minimize the overall energy cost within the prediction horizon. The method is mainly developed for demand-side management in the future smart grid, but a simpler version can be applied in the current electricity market. Due to the system nonlinearity, the minimization is in general a complicated nonconvex optimization problem. A new supervisory control structure as well as an algorithmic pressure control scheme is presented to rearrange the problem to facilitate convex programming. A nonlinear continuous time model validated by real data is employed to simulate the system operation. The results show a considerable economic saving as well as a tradeoff between the saving level and the design complexity.

Model-Based Predictive Control Scheme for Cost Optimization and Balancing Services for Supermarket Refrigeration Systems

“…We can model the power consumption by using (11) to replace power consumption by cooling capacity, however it is divided by the COP. In Shafiei et al [2013b], it is explained that for the case where the condenser fan is fixed in a speed (usually close to maximum), the average value of the COP is highly correlated with the value of the outdoor temperature. Outdoor temperature predictions are fairly accurate and can be used to predict the COP in (13).…”

“…Optimal power consumption or storage of energy is achieved by minimization of a cost function over a prediction horizon, Rawlings and Amrit [2009]. A strategy where an MPC is used as a supervisory controller to generate references for local controllers is shown by Shafiei et al [2013b] for operating cost minimization in refrigeration systems. Hovgaard et al [2012] presents an MPC algorithm to optimize cost of operation as well as providing normal ancillary services, where a non-convex optimization problem is put forward.…”

From Consumption to Prosumption - Operational Cost Optimization for Refrigeration System With Heat Waste Recovery

“…A linear model predictive control (MPC) approach has been presented among others in Larsen (2005), where the authors focus on set-point optimization. In Shafiei et al (2013), Hovgaard et al (2011), Hovgaard et al (2012, authors present various forms of linear economic MPC for supervisory control. In Pedersen et al (2014), Pedersen et al (2013), the authors use a "leaky bucket" model for high level representation of groups of refrigeration units and solve the optimization problem using linear economic MPC as well.…”

“…Furthermore, we disregard the dynamics of the expansion valve, and model the evaporator assuming that cooling capacity can be controlled as in Shafiei et al (2013). We assume that the refrigerant mass flowṁ r can be treated as a control variable.…”

Model predictive control for flexible power consumption of large-scale refrigeration systems

“…This problem is addressed in [6] using nonconvex model predictive control in a real-time pricing market. In [7], the evaporation temperature is controlled in a separated loop while a supervisory MPC is proposed for energy cost optimization.…”