Economic Health-Aware LPV-MPC Based on System Reliability Assessment for Water Transport Network

Abstract

This paper proposes a health-aware control approach for drinking water transport networks. This approach is based on an economic model predictive control (MPC) that considers an additional goal with the aim of extending the components and system reliability. The components and system reliability are incorporated into the MPC model using a Linear Parameter Varying (LPV) modeling approach. The MPC controller uses additionally an economic objective function that determines the optimal filling/emptying sequence of the tanks considering that electricity price varies between day and night and that the demand also follows a 24-h repetitive pattern. The proposed LPV-MPC control approach allows considering the model nonlinearities by embedding them in the parameters. The values of these varying parameters are updated at each iteration taking into account the new values of the scheduling variables. In this way, the optimization problem associated with the MPC problem is solved by means of Quadratic Programming (QP) to avoid the use of nonlinear programming. This iterative approach reduces the computational load compared to the solution of a nonlinear optimization problem. A case study based on the Barcelona water transport network is used for assessing the proposed approach performance.

Approaches, Advances, and Applications in the Sustainable Development of Smart Cities: A Commentary from the Guest Editors

“…To this extent, their study is closely aligned with the concept of zero-energy building, which aims to achieve a higher level of building sustainability by having a balance in building energy consumption and production [21,22]. Additionally, Pour et al [23] and Olszewski et al [24] suggest that the utilization of renewable energy and efficient water transport network systems can contribute to more than better energy efficiency or environmental protection.…”

“…Olszewski et al [24] in their work, 'A Multi-Agent Social Gamification Model to Guide Sustainable Urban Photovoltaic Panels Installation Policies' present a model of social gamification to stimulate the photovoltaic panels installation process, and ultimately, to make cities more environmentally sustainable. A health-aware control approach for drinking water transport networks is proposed by Pour et al [23] in their study entitled 'Economic Health-Aware LPV-MPC Based on System Reliability Assessment for Water Transport Network'. Kwon et al [45] consider that thermal comfort (such as the urban heat island effect) is a public health issue and identify environmental factors that contribute to thermal comfort in cities.…”

A two-layer control architecture for operational management and hydroelectricity production maximization in inland waterways using model predictive control

“…MPC is an appropriate control approach for inland waterways management, as it is solved as an online optimization problem and its design framework is simple yet powerful. Its main principle consists in calculating an input sequence that steers the predicted system response to the setpoints optimally while respecting the constraints [38]. Then, the set of operational objectives can be achieved by minimizing a multi-objective cost function that can be established as the weighted aggregate of different terms, each related to a particular objective.…”

Health-aware Model Predictive Control including Fault-tolerant Capabilities for Drinking Water Transport Networks

“…Considering the control action u i (k) as the scheduling variable related to each actuator and state in the augmented MPC model, it can be considered (20) as an LPV model. In this way, by following the MPC-LPV approach in [1], the MPC optimization problem can be formulated as a QP problem by using an estimation of scheduling variables.…”

“…These networks require advanced supervisory-control approaches to guarantee and maintain optimal performance even in faulty situations. Water consumption can change in both the short and the long term, ordinarily represented by different time-based models according the zone [1]. Therefore, better modelling and forecasting of demands will improve the modelling and control of DWNs.…”