# Advanced Control and Fault Detection Strategies for District Heating and Cooling Systems--A Review
## 3 Overview of Fault Detection and Diagnosis (FDD) in DHC Systems  
It is evident that the exploitation of innovative DHC solutions requires the whole system to operate as efficiently as possible [95]. However, several authors [96, 97, 98, 99] have proved that faults taking place during the operation of energy systems can normally be responsible for up to 40% of their total energy use. Several factors, such as compensation actions triggered by control algorithms or lack of proper maintenance practice, can make these faults remain undetected. Indeed, the manual identification of these faults gets very complicated even if the suboptimal operation of the system is known. This makes the tasks of human maintenance operators really costly, since they only take actions on the system when the indoor environmental thresholds are not met. In this context, automated fault detection and diagnosis (FDD) methods and tools play a key role to assist building and DHC system operators [100]. One typical operating problem in district heating systems indicated by [PERSON] and [PERSON] (2014) [25] is the heat carrier loss through water leakage. Water losses occur for several reasons and the corresponding magnitudes of losses also vary. A review of FDD methods to address this problem is presented in Section 3.1. Other operating problems are higher temperature levels due to high return temperatures caused by typical malfunctions such as set-point errors in substations and customer heating systems or short-circuit flows in the thermal grid [25]. Since the reduction in the supply temperature is the main objective of 4 GDH and 5 GDHC in order to exploit renewable and low-grade excess heat sources, assuring a low return temperature is a key aspect in these innovative DHC solutions [24]. In order to avoid malfunctions and faults, maintenance planning becomes crucial to achieve a good service for customers and maintain an economical retrofit for owners. The concept of maintenance includes the administration, control, implementation and quality of those activities, which will ensure that design availability levels and asset performance are achieved in a reasonable way to meet economical and functional objectives. Some definitions of classic maintenance strategies that can be applied are:  
* Corrective maintenance is performed to determine, separate and fix a fault so that the failed equipment or facility can be brought back to an operational condition, which lies within in-service operations tolerances. * Preventive maintenance is performed on a regular basis on a piece of equipment in order to reduce the probability of failure, and it involves a systematic check-up of equipment, thus enabling to detect and correct potential problems. * Condition-based maintenance consists of a strategy different from preventive maintenance because the maintenance action relies on the actual condition of an asset, rather than average or expected life statistics, to decide what maintenance needs to be done. It imposes that maintenance should only be performed when some indicators show marks of decreasing performance or imminent failure. * Predictive maintenance is an extension of condition-based maintenance where precise techniques and formulas are used to detect incipient faults and predict their evolution, so the maintenance action can be scheduled before the critical failure in the equipment occurs. Predictive maintenance generally applies non-destructive testing technologies and other specific online methods depending on the type of equipment or process being monitored. * Proactive maintenance sets corrective actions focused on failure root causes, not on failure symptoms, unlike predictive or preventive maintenance. There is a huge range of different fault detection (FD) techniques as classified by [PERSON] et al. (2017) [101]. FD methods may be model-based or based purely on process history data, both of them are also called \"internally based\" methods.