\r\n\tEqually important are the consequences deriving from the extraordinary nature of the present times. The COVID-19 pandemic and the restrictive measures to contain the infection (lockdown and "physical distancing" in primis) have revolutionized the lives, and a distortion/modification of habits, rhythms, arrangements will continue to be necessary. \r\n\tGovernments have implemented a series of actions to mitigate the spread of infections and alleviate the consequent pressure on the hospital system. On the other hand, the Covid-19 pandemic has caused a series of other cascading effects that will probably be much more difficult to mitigate and which expose to complex consequences. The past two years have brought many challenges, particularly for healthcare professionals, students, family members of COVID-19 patients, people with mental disorders, the frail, the elderly, and more generally those in disadvantaged socio-economic conditions, and workers whose livelihoods have been threatened. Indeed, the substantial economic impact of the pandemic may hinder progress towards economic growth as well as progress towards social inclusion and mental well-being.
\r\n
\r\n\t \r\n\tAlthough in all countries the knowledge on the impact of the pandemic on mental health is still limited and mostly derived from experiences only partially comparable to the current epidemic, such as those referring to the SARS or Ebola epidemics, it is likely that the demand for intervention it will increase significantly in the coming months and years. The extraordinary growth of scientific research in the field of neuroscience now offers the possibility of a new perspective on the relationship between mind and brain and generates new scenarios in understanding the long wave of the pandemic and in the prospects for treatment. Moreover, the pandemic also has led to opportunities to implement remote monitoring and management interventions.
\r\n
\r\n\t \r\n\tOverall this volume will address the complex relationship existing between COVID-19, mental health, acquired knowledge, and possible interventions taking a highly multidisciplinary approach; from physiological and psychobiological mechanisms, and neuromodulation through medical treatment, psychosocial interventions, and self-management.
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\n
1. Introduction
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The production of energy is an immense challenge for the coming years. Indeed, the energy requirements for industrialized societies are increasing [1]. Nowadays, 80.9% of world production of primary energy is supplied from fossil resources [2]. The scarcity of conventional energy and the environmental problems caused by its use have led to the usage of other renewable sources such as solar photovoltaic energy. It is stimulated first by the availability of solar resources in most part of the globe particularly in Africa where there is a strong solar resource and secondly by the decrease in the cost of photovoltaic equipment during the last decade [3], an average of 0.7 $/kWh in 2016 and 0.5 $/kWh in 2020. The production capacity of solar photovoltaic energy within the last three decades has witnessed a yearly increase of 44.2% between 1990 and 2010, to reach a production capacity of 99.2 GW in 2012 [4]. Global installed PV capacity at the end of 2016 was reported as 310 GWp [5]. The price of photovoltaic module dropped by 80% between 2009 and 2015 to reach the actual cost which is less than 1 USD/Wp [6]. PV is widely used in many applications nowadays [7].
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The use of renewable energies has increased significantly in Cameroon these recent years since it is demonstrated that the access to modern forms of energy can contribute effectively to the revival of economy and reduction of poverty. In many countries around the world, the use of renewable energy contributes expanding employment opportunities which lead to promoting human development [8]. Recently Cameroon has embarked on the use of renewable energy, which has led to the creation of a directorate of renewable energy in the ministry of energy and water. Investments have been made in the public investment budget (PIB) for the installation of renewable energy systems particularly solar energy [1], for example, public lighting in cities and the countryside by using solar street lights, solar power plants for the villages’ electricity supply, battery charging stations in villages, and solar power supplies for community centers. However, as they are installed in outdoor environment, continuous exposure to harsh environmental conditions (sun beam, rainfall, etc.) may reduce the optimal performance of the system. PV systems are difficult to implement because they encounter problems among which is the problem of servicing and maintenance. An effective operation and maintenance (O and M) program enables PV system production to reach its expected level of efficiency, which will consequently strengthen end users’ confidence in such systems [9].
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The field performance of photovoltaic systems has been extensively studied for many applications especially in countries with strong database of solar resource [9]. However, these databases are used exclusively for assessing the electrical performance of the system [10]. To model the annual performance of photovoltaic modules, their performance characteristics are needed [11, 12]. The available information from manufacturers are typically limited to temperature coefficients, short circuit current \n\n\nI\nsc\n\n\n, open circuit voltage \n\n\nV\noc\n\n\n, and maximum power \n\n\nP\nmax\n\n\n, at rating conditions (G = 1000 W/m2, Tc = 25°C, AM = 1.5). The information is useful when one want to compare photovoltaic module performance at rating conditions but are inadequate to predict annual field performance under typical operating conditions [13]. It is demonstrated that there is difference between expected power production forecasts and field experience of photovoltaic arrays [14]. It has been shown that the relative performance ranking at rating conditions may not agree with the ranking based on monthly or annual performance. Faults in PVS may cause a huge amount of energy loss. A monitoring study was conducted on a test PV system by Firth et al. [15], and it was reported that the annual power loss due to various faults is about 18.9%.
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Failures that occur in the PV systems can cause system shutdown. The main components involved are PV modules, cabling, protections, converters, and inverters. Failures are mainly caused by external operating conditions which are shading effects, module soiling, inverter failure, and aging of PV modules [16]. The line-to-line fault (LLF), ground fault (GF), and arc fault (AF) are tree catastrophic failures encountered in PV arrays [17]. PV system maintenance and performance are related to good inspection and monitoring. These are important in determining life-cycle costs and servicing requirements. Photovoltaic energy is seen as a viable option for decentralized energy production; the sustainability of these systems does not only depend on the initial system cost but also on the cost of maintenance and the lifetime related to the maintenance operations used [18, 19]. This chapter presents an overall of existing faults encountered in both DC and AC sides over a period of 9 years in more than 20 PV systems in Cameroon; this chapter also proposes detection techniques with a fault detection procedure (the breakdown tree diagram) that is intended to facilitate interventions on all components of PV systems.
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2. Maintenance strategies
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Maintenance strategies are the “heart” of the maintenance planning process. They are responsible for defining the “maintenance actions” based on the information obtained from the system and preprocessed. Maintenance strategies are corrective, preventive, condition-based, opportunistic, focused-on-reliability, and production strategies [20]. The questions when, what, who, where, why, and how are the system interventions that should be executed or not, in order to keep the system functions alive [21]. One of the maintenance objectives is to reduce the failure occurrence, increase the availability, and extend the system life (or at least in the mean time until the next failure).
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3. Maintenance technique management
\n
A maintenance schedule, planning, and management are important for the evaluation of the health condition components and the incipient fault diagnosis. Different aspects of the operation and maintenance of renewable energy systems were proposed by [20, 22]. A generic structure of asset management which integrates business decisions to optimize investment decisions related to maintenance is presented by [23], and it consists of eight blocks of sequential management. In physical asset management, the maintenance optimization is a concern, because in general, the assets deteriorate as it is being raised and both the failure risk and cost increase [24]. Maintenance management model of assets is presented in Figure 1 below.
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Figure 1.
Maintenance management model [25].
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4. Operation and maintenance of the photovoltaic systems
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4.1 Preventive maintenance
\n
Preventive maintenance consists of a regular observing passage and a frequent replacement of exhausted constituents of the system. Preventive maintenance can be systematic or conditional. Systematic preventive maintenance consists of changing worn out materials according to a preestablished schedule [26]. Preventive maintenance is scheduled at regular time intervals, independent of component wear, or if it still executes its function satisfactorily [26]. Preventive maintenance scheduling could be done using several strategies; the most common are usually with a minimal cost target that are based on the budget allocation for maintenance in accordance with the system priorities [27, 28]. The objective of this type of maintenance is to ensure the reliability of the system and to maintain the system in its state of initial efficiency [29].
\n
\n
\n
4.2 Corrective maintenance
\n
It consists of the setup of a breakdown system. It is usually done in two stages: palliative corrective maintenance (fixing) which involves the start off of a system which is partially or totally broken up while waiting for a permanent repair of this system. In this case, the speed with which interventions are done is considered, and the action must take place as fast as possible for quicker start off of this system [20]. The goal of this action is not to repair the breakdown but to permit the system to fulfill part or the totality of it function [20]. Curative corrective maintenance (repairing) is a final setup of all the worn out elements of the system. Contrary to the fixing action, the repairing action is a planned one. In this case, the quality of the intervention is more important than speed. In the case of corrective maintenance on photovoltaic systems, diagnosis diagrams are first done in order to ease and help workers to determine the worn out elements knowing the causes of the breakdown. The essence of the approach “run-to-failure” or corrective maintenance is to replace the component with a new one when it is not able to perform its function [26].
\n
\n
\n
4.3 PV systems fault detection techniques
\n
There are several techniques for the detection of faults in PV systems; these techniques are summarized in Figure 2. These techniques have helped in improving the system reliability and lifetime of PV systems. The classification of different fault detection techniques to identify the type and location of the fault occurring in DC and AC sides of PV system is given in [27, 16, 28]. Although other techniques are simple to implement, most of them require monitoring and analysis of the electrical performance of photovoltaic (PV) systems.
\n
Figure 2.
Fault detection techniques in DC and AC side of PV system [27, 29].
\n
\n
\n
4.4 Types of faults encountered in PV systems
\n
In the field conditions, a number of factors can cause a PV array to reduce its output power. Any factor which reduces the output is considered as “fault” [27, 30]. Generally, faults in PV systems can be classified into two main categories: permanent and temporary. The classification of the most common types of fault in PV system is presented in Figure 3. The main faults encountered in PV systems Installed are presented in the Figure 4 for shading, Figure 5 for soiling and dust, Figure 6 for PV jonction fault and discoloration, Figure 7 for wiring fault, Figure 8 for circuit breaker and inverter, Figure 9 for sulfatation and deep discharge of batteries.
\n
Figure 3.
Classification of faults in DC and AC side of PV systems [27].
\n
Figure 4.
(a) Shading and (b) vegetation and building.
\n
\n
\n
\n
5. Characteristics of the studied PV system
\n
\n
5.1 Backup PV systems
\n
To overcome the problem of power cuts, 20 backup systems have been installed in 20 cities in Cameroon at the end of 2006. These systems are essentially made up of monocrystalline solar modules (Hélios, 80Wc), batteries (Midac, 400 Ah) to backup during power cuts, and charge controllers (Steca, 20A) which regulates the energy flux and protects the batteries from overloading and deep discharge. There are generally three types of controllers [31, 32]: shunt controllers, series controllers, and maximum power point tracking (MPPT) system. The inverter called “inverter-chargers” can be connected to the electricity network in the purpose of supplying the energy of the network, two types of inverters are used C1600-12 and C2600-24 (Studer compact) (Figures 4–9).
\n
Figure 5.
(a) Soiling and dust accumulation and (b) vegetation.
\n
Figure 6.
(a) PV junction box and (b) delamination and discoloration.
\n
Figure 7.
(a) Wiring system fault and (b) poor tightening of connections fault.
\n
Figure 8.
(a) Circuit breaker fault and (b) inverter fault.
\n
Figure 9.
(a) Deep discharge of batteries and (b) sulfation of batteries due to lack of maintenance.
\n
\n
\n
5.2 Photovoltaic water pumping system
\n
Two water pumping systems are installed to provide water to the population of an isolated site located at 10°23 N and 14°26 E. Each system has 13 kWp of PV generator associated to an automatic inverter. The pumping takes place over the sun. The configuration of a field is performed as follows: 51 solar panels all divided into 03 strings of 17 panels. Two pumps P1 and P2 were associated. The characteristics of the PV module used, inverter and motor pump, are specified in Tables 1 and 2.
\n
\n
\n
\n
\n\n
\n
Denomination
\n
Symbol
\n
Value
\n
\n\n\n
\n
Rated maximum power (Pmax)
\n
\n\n\n\nP\nmax\n\n\n\n
\n
255 Wp
\n
\n
\n
Maximum power current (Imp)
\n
\n\n\n\nI\nmax\n\n\n\n
\n
8.13 A
\n
\n
\n
Short circuit current (Isc)
\n
\n\n\n\nI\nsc\n\n\n\n
\n
8.61 A
\n
\n
\n
Maximum power voltage (Vmp)
\n
\n\n\n\nV\nmp\n\n\n\n
\n
31.52 V
\n
\n
\n
Open circuit voltage (Voc)
\n
\n\n\n\nV\noc\n\n\n\n
\n
37.92
\n
\n
\n
Maximum system voltage
\n
\n
1000 V
\n
\n
\n
Operating temperature
\n
\n
(−40 + 85)°C
\n
\n
\n
Temperature coefficient of \n\n\nI\nsc\n\n\n\n
\n
\n\n\n\nα\nIsc\n\n\n\n
\n
−0.58%/°C
\n
\n
\n
Temperature coefficient of \n\n\nV\noc\n\n\n\n
\n
\n\n\n\nβ\nVoc\n\n\n\n
\n
−0.33%/°C
\n
\n
\n
Temperature coefficient of power
\n
\n
−0.41%/°C
\n
\n\n
Table 1.
Characteristics of the PV module used in PVWPS.
\n
\n
\n
\n
\n
\n\n
\n
Inverter Solartech PB11KH
\n
Grundfos SP17-10 pump
\n
\n
\n
Denomination
\n
Value
\n
Denomination
\n
Value
\n
\n\n\n
\n
Rated power
\n
11 kW
\n
Motor type
\n
MS4000
\n
\n
\n
Max solar input power
\n
16 kW
\n
Rated power—P2
\n
5.5 kW
\n
\n
\n
Input string
\n
4
\n
Power (P2) required by pump
\n
5.5 kW
\n
\n
\n
Max input current of each string
\n
15 A
\n
Mains frequency
\n
50 Hz
\n
\n
\n
Max DC input voltage
\n
750 V
\n
Rated voltage
\n
3 × 380–400–415 V
\n
\n
\n
Recommended MPP voltage
\n
500–600 V
\n
Rated current
\n
13.0–13.0–13.4 A
\n
\n
\n
Adapting motor power
\n
9.2–11 kW
\n
Starting current
\n
480–530–550%
\n
\n
\n
Adapting motor voltage
\n
3PH 380-440 V
\n
Cos phi—power factor
\n
0.85–0.81–0.76
\n
\n
\n
Rated AC output current
\n
24A
\n
Rated speed
\n
2850–2860–2870 rpm
\n
\n
\n
Output frequency
\n
0–50/60 Hz
\n
Starting method
\n
Direct online
\n
\n
\n
Conversion efficiency
\n
Max 98%
\n
Rated flow
\n
71 m3/h
\n
\n
\n
Ambient temperature
\n
−10 to 50°C
\n
Rated head
\n
81 m
\n
\n\n
Table 2.
Characteristics of the inverter and the motor pump.
\n
\n
\n
\n
6. Maintenance and fault detection techniques in PV systems
\n
The field inspection process is a key to the development of healthy and safe PV systems. Many works consolidated the most important aspects of a field inspection of photovoltaic system which is the competency of the contractor and installer without taken into account life service of each element and their implication on the failure of the system [33, 34]. Diagnosis procedures consist on visual inspection procedures (array inspection, wire inspection, inverter inspection, inspection of module, and array grounding) and performance monitoring (performance verification, displays, design software, data acquisition systems, sensors) [34]. One of the most valuable techniques for identifying existing problems and preventing future problems is to walk to the site and conduct a thorough visual and hands-on inspection of the PV system components. During these inspections, the parameters to be measured in real times are specified in Table 3.
\n
\n
\n
\n
\n\n
\n
Parameter
\n
Symbol
\n
Unit
\n
\n\n\n
\n
Meteorology
\n
\n
\n
Total irradiance (global), in the plane of the array
\n
\n\n\n\nG\nI\n\n\n\n
\n
W m−2
\n
\n
\n
Ambient air temperature in a radiation shield
\n
\n\n\n\nT\nam\n\n\n\n
\n
°C
\n
\n
\n
Wind speed (may be required by special contract or if the PV array is subject to extreme operating conditions)
\n
\n\n\n\nS\nW\n\n\n\n
\n
m s−1
\n
\n
\n
Photovoltaic array
\n
\n
\n
Output voltage
\n
\n\n\n\nV\nA\n\n\n\n
\n
V
\n
\n
\n
Output current
\n
\n\n\n\nI\nA\n\n\n\n
\n
A
\n
\n
\n
Output power
\n
\n\n\n\nP\nA\n\n\n\n
\n
kW
\n
\n
\n
Module temperature
\n
\n\n\n\nT\nm\n\n\n\n
\n
°C
\n
\n
\n
Tracker tilt angle (optional for systems with tracking arrays)
\n
\n\n\n\nϕ\nT\n\n\n\n
\n
Degrees
\n
\n
\n
Tracker azimuth angle (optional for systems with tracking arrays)
\n
\n\n\n\nϕ\nA\n\n\n\n
\n
Degrees
\n
\n
\n
Energy storage
\n
\n
\n
Operating voltage
\n
\n\n\n\nV\nS\n\n\n\n
\n
V
\n
\n
\n
Current to storage
\n
\n\n\n\nI\nTS\n\n\n\n
\n
A
\n
\n
\n
Current from storage
\n
\n\n\n\nI\nFS\n\n\n\n
\n
A
\n
\n
\n
Power to storage
\n
\n\n\n\nP\nTS\n\n\n\n
\n
kW
\n
\n
\n
Power from storage
\n
\n\n\n\nP\nFS\n\n\n\n
\n
kW
\n
\n
\n
Load
\n
\n
\n
Load voltage
\n
\n\n\n\nV\nL\n\n\n\n
\n
V
\n
\n
\n
Load current
\n
\n\n\n\nI\nL\n\n\n\n
\n
A
\n
\n
\n
Load power
\n
\n\n\n\nP\nL\n\n\n\n
\n
kW
\n
\n
\n
Utility grid
\n
\n
\n
Utility voltage
\n
\n\n\n\nV\nU\n\n\n\n
\n
V
\n
\n
\n
Current to utility grid
\n
\n\n\n\nI\nTU\n\n\n\n
\n
A
\n
\n
\n
Current from utility grid
\n
\n\n\n\nI\nFU\n\n\n\n
\n
A
\n
\n
\n
Power to utility grid
\n
\n\n\n\nP\nTU\n\n\n\n
\n
kW
\n
\n
\n
Power from utility grid
\n
\n\n\n\nP\nFU\n\n\n\n
\n
kW
\n
\n
\n
Backup sources
\n
\n
\n
Output voltage
\n
\n\n\n\nV\nBU\n\n\n\n
\n
V
\n
\n
\n
Output current
\n
\n\n\n\nI\nBU\n\n\n\n
\n
A
\n
\n
\n
Output power
\n
\n\n\n\nP\nBU\n\n\n\n
\n
kW
\n
\n\n
Table 3.
Parameters to be measured in PV systems in real time [35].
\n
When problems are identified, we can use breakdown tree diagrams [36, 37]. Breakdown tree diagram gives a graphical description of the different events that lead to a breakdown resulting to the non-reliability and the stop of the system [37]. The breakdown tree diagram is constructed in a deductive manner. It starts with the peak event right up to the elementary event in arborescence. The peak event for which we seek the probability is often called “feared.” We generally use AND and OR logic gates to define the probability of what is at the cause of the event, to put the situation (what is to be resolved) at the head of the diagram and link it to its causes (events that can be at the origin) by the gate. Once the diagram has been archived, if there is any breakdown, interventions are done from the bottom of the diagram to the top where the problem is detected in the system. Figure 10 shows that for the “feared” event to archived, either event E1 or E2 must have been archived. In the same manner, for the event E1 to be archived, either the base event e1 or e2 must have been archived, and for the event E2 to be archived, both base events e1 and e2 must have been archived at the same time.
\n
Figure 10.
Breakdown tree method.
\n
The failure modes, effects and criticality analysis (FMECA) which is a rigorous and preventive method for identifying potential failures of a system and elements, actions have been defined to be taken to eliminate these failures, reduce their effects, and detect and prevent causes. The method is part of an eight-step process [38] as seen in Figure 11. Several criteria can be used to determine the criticality index. In practice, we assign three notes (each on a scale of 1–10) for each trio cause-mode-effect:
The grade G: severity of the effect, the consequences on the client/user
The grade O: the probability of occurrence, the frequency of occurrence
The grade D: the probability of non-detection, the risk of non-detection
\n
Figure 11.
FMECA approach.
\n
\n\nThe criticality index is obtained\n\nby\n\nC\n=\nG\n∗\nO\n∗\nD\n\nE1
\n
\n
\n
7. Case study
\n
\n
7.1 Photovoltaic backup systems
\n
In order to better study the impact of the two types of maintenance on the system, Figure 12 shows the frequent preventive and corrective maintenance operations carried out on installed PV backup systems during the period 2012–2015, which were kindly followed.
\n
Figure 12.
(a) Number of corrective and preventive maintenance per year on a PV systems and (b) recorded breakdowns per elements.
\n
Figure 12(a) presents the number of preventive and corrective interventions realized on one site within a period of 4 years. This illustration shows the importance of preventive maintenance on PV systems. In effect, the more preventive maintenance are done, the less there are corrective operation realized. It is the case for the years 1, 3, and 4. To estimate the element lifetime before failure, the exploitation of the maintenance files indicated that 25 batteries were damaged on the 82 installed as shown in Figure 12(b); thus, batteries contributed to 64.9% of the breakdowns generated during this studying period. This result shows also that batteries are the most sensitive elements of the PV system charge controllers, cables, and inverters, which contribute, respectively, 13, 8.3, and 5.5% of the breakdown registered.
\n
\n
7.1.1 The causes of breakdown at each element
\n
\n
7.1.1.1 Causes of the battery and cable breakdown
\n
Batteries being one of the vulnerable elements of a PV system, the direct causes of their breakdown are due to late interventions and aging. Figure 13(a) shows the causes of the breakdown of batteries. It appears that five battery breakdowns were caused by the lack of control of the good functioning of charge controllers, and four damaged batteries were due to a late refill of the electrolyte. It has also been noticed that the bad sizing of the generator system and the climatic factors (temperature, humidity) which were not adapted to the good functioning of the batteries cause their breakdown. The most frequently observed breakdown causes of the cables are (Figure 13(b)) cable break age and corrosion which lead to short circuits and worn out cables, and great length cables can also cause the voltage drop and energy losses at the end of the system.
\n
Figure 13.
(a) Damaged batteries and their causes and (b) cables breakdown versus causes.
\n
\n
\n
7.1.1.2 Causes at the level of the inverter and PV module
\n
Breakdown on inverters is frequently caused by overvoltage (Figure 14(a))). They have as origin the nonfunctioning of charge controllers and the frequent interruption of electricity of the network. For PV modules the most frequent causes are Figure 14(b): dust deposit, bad fixing on their supports, and accidental cracking. The first two causes which do not lead to the stop of the system decrease the efficiency of the system (output energy), while the third cause leads to the stop of the system which necessarily needs a replacement.
\n
Figure 14.
(a) Inverters faults versus causes of breakdown and (b) PV module breakdowns versus causes.
\n
\n
\n
\n
7.1.2 The breakdown tree diagram used for the diagnosis of the breakdown in the studied system
\n
During corrective interventions, most of the workers overcome the breakdown without trying to eliminate their causes or without investigating on the causes of the breakdown. The exploitation of maintenance files shows that many elements were replaced within a short period of time. This situation led to frequent breakdown of the system even though the bad element was replaced. It became very important to put in place a breakdown diagnosis method in order to eliminate breakdown and causes. The breakdown tree technique helps to graphically represent the possible combinations of the events that permit the realization of a non-needed predefined event. The breakdown tree is then made of levels of events linked by gate (initially logic gate). By using this representation and a logical deduction (moving from effects to causes), it is possible to cast out the causes from the effects, from the non-needed event to base events, independent to one another and probable (Figure 15).
\n
Figure 15.
Breakdown tree diagram for detecting breakdowns in a PV system.
\n
\n
\n
\n
7.2 Photovoltaic water pumping systems
\n
In PV water pumping systems, the main objective is to collect data, diagnosing the system and proposing and implementing solutions that will optimize the operation of the system in order to satisfy the water need of the population all over the year. Indeed from the collected and measured data, Tables 4 and 5 show the failures we may encounter in our installation as well as the possible causes and solutions.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Components
\n
Failures
\n
Possible causes
\n
Effects on the system
\n
Observable parameter
\n
Criticality
\n
\n
\n
G
\n
O
\n
D
\n
C
\n
\n\n\n
\n
Photovoltaic generator (PVG)
\n
\n\n\n\nV\n\nm\n,\nPV\n\n\n<\n\nV\n\nref\n,\nPV\n\n\n\n\n T = 25°C E = 800 W/m2
\n
• Diode bypass short circuit • Defective module in serial
\n
• Decrease of tension
\n
• Voltage
\n
5
\n
2
\n
2
\n
20
\n
\n
\n
\n\n\n\nI\n\nm\n,\nPV\n\n\n<\n\nI\n\nref\n,\nPV\n\n\n\n\n T = 25°C E = 800 W/m2
• Check and replace the connection wire • Replace the faulty diode
\n
\n
\n
\n\n\n\nP\nmPV\n\n<\n\nP\nrefPV\n\n\n\n T = 25°C E = 800 W/m2
\n
• Shadow-related design flaw • Dirt of the panels
\n
• Clear the objects causing the shadow • Clean the modules
\n
\n
\n
\n\n\n\nP\n\nm\n,\nPV\n\n\n=\n0\n\n\n T = 25°C E = 800 W/m2
\n
• Corrosion or looseness of the connection terminals • Defective fuse
\n
• Tighten or change the connection terminals • Change the fuse
\n
\n
\n
Inverter
\n
\n\n\n\nP\nInv\n\n=\n0\n\n\n T = 25°C E = 800 W/m2
\n
• Inverter failure • Defective power cables or poor tightening at the Inverter input
\n
• Replace the inverter • Remove or replace the power cable
\n
\n
\n
Pump
\n
\n\n\n\nQ\nm\n\n=\n0\n\n\n Not functioning (pumping stop) E = 800 W/m2
\n
• Clogged strainer • Defective wheels • Lowering of the water level
\n
• Unclog the strainer • Change the wheels • Check the water level is at least 1 m above the suction body of the pump during operation
\n
\n
\n
Engine
\n
\n\n\n\nQ\nm\n\n=\n0\n\n\n Not starting E = 800 W/m2
\n
• Defective phases • Low voltage • Defective mechanical sea
\n
• Replace the phases • Change the seals
\n
\n\n
Table 5.
Their solutions to the possible failures in a photovoltaic pumping system according to FMECA.
\n
To facilitate the procedure of these pumping stations, breakdown tree diagram is constructed in a deductive manner as highlighted in the Figure 16. For each event E1, E2, E3 and E4 in the Figure 16, breakdown tree diagram for failures encountered are presented respectively in the Figures 17–20.
\n
Figure 16.
Failure of the photovoltaic pumping systems (events E1, E2, E3, and E4 are shown in Figures 17–20).
\n
Figure 17.
Photovoltaic generator failure tree.
\n
Figure 18.
Inverter failure tree.
\n
Figure 19.
Pump failure tree.
\n
Figure 20.
Pump unit failure diagram.
\n
\n
\n
\n
8. Conclusion
\n
Maintenance operations have a crucial interest in the viability evaluation and the analysis of the life expectancy of a PV system. In this study, we have shown the maintenance techniques which can enable the best diagnosis of breakdown. After the exploitation of maintenance file report data of the twenty backup PV systems and two PV water pumping systems installed in more than 15 towns in Cameroon, it can be concluded that the most vulnerable element of a solar PV system is the battery since this element represents 64.9% of the breakdown recorded. Among the 20 backup PV systems subject of our study, it appears that 50% received their first curative intervention from the 5th year. The FMECA method for PVWPS shows that the criticality of the installation varies from 252 for the inverter, 402 for the PV generator, and 504 for the motor pump. Particular attention must be paid on preventive operations in order to eradicate causes of frequent breakdowns of the components in general and motor pump and batteries in particular. That is why breakdown tree diagram is proposed for the rapid determination of breakdowns on the studied PV systems and the steps or order of detecting breakdowns on a system.
\n
\n\n',keywords:"breakdown diagram, life expectancy, maintenance strategies, backup PV systems, PV pumping systems",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/68880.pdf",chapterXML:"https://mts.intechopen.com/source/xml/68880.xml",downloadPdfUrl:"/chapter/pdf-download/68880",previewPdfUrl:"/chapter/pdf-preview/68880",totalDownloads:1185,totalViews:0,totalCrossrefCites:2,dateSubmitted:"July 21st 2018",dateReviewed:"December 21st 2018",datePrePublished:"August 31st 2019",datePublished:"January 22nd 2020",dateFinished:"August 31st 2019",readingETA:"0",abstract:"The objectives of this work are to examine the causes of the breakdown in the photovoltaic power systems, to propose strategies to solve them, and to evaluate the field lifetime of some elements of the PV systems. The data analyzed were obtained from maintenance records and measurements over a period of 9 years (from 2007 to 2015) for the backup PV systems and 2 years (from 2016 to 2018) for photovoltaic water pumping (PVWPS) systems. It appears from this analysis that 29% of the batteries went bad (leading to curative intervention); this contributed to about 64.9% of the total breakdown registered. Using the failure modes, effects and criticality analysis (FMECA) method for PVWPS, criticality is 252, 402, and 504 for inverters, PV module, and motor pump, respectively. This demonstrates that motor pumps are more sensitive than other elements in the PVWPS. This study also permitted not only to evaluate the quantity of preventive and corrective maintenance impacts on solar PV systems but also to propose maintenance strategies to rapid diagnosis of PV systems.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/68880",risUrl:"/chapter/ris/68880",signatures:"Kodji Deli and Djongyang Noel",book:{id:"8623",type:"book",title:"Maintenance Management",subtitle:null,fullTitle:"Maintenance Management",slug:"maintenance-management",publishedDate:"January 22nd 2020",bookSignature:"Fausto Pedro García Márquez and Mayorkinos Papaelias",coverURL:"https://cdn.intechopen.com/books/images_new/8623.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-514-9",printIsbn:"978-1-83968-513-2",pdfIsbn:"978-1-83968-515-6",isAvailableForWebshopOrdering:!0,editors:[{id:"22844",title:"Prof.",name:"Fausto Pedro",middleName:null,surname:"García Márquez",slug:"fausto-pedro-garcia-marquez",fullName:"Fausto Pedro García Márquez"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"268750",title:"Ph.D.",name:"Kodji",middleName:null,surname:"Deli",fullName:"Kodji Deli",slug:"kodji-deli",email:"delikodji27@yahoo.fr",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"317017",title:"Dr.",name:"Djongyang",middleName:null,surname:"Noel",fullName:"Djongyang Noel",slug:"djongyang-noel",email:"noeldjongyang@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Maintenance strategies",level:"1"},{id:"sec_3",title:"3. Maintenance technique management",level:"1"},{id:"sec_4",title:"4. Operation and maintenance of the photovoltaic systems",level:"1"},{id:"sec_4_2",title:"4.1 Preventive maintenance",level:"2"},{id:"sec_5_2",title:"4.2 Corrective maintenance",level:"2"},{id:"sec_6_2",title:"4.3 PV systems fault detection techniques",level:"2"},{id:"sec_7_2",title:"4.4 Types of faults encountered in PV systems",level:"2"},{id:"sec_9",title:"5. Characteristics of the studied PV system",level:"1"},{id:"sec_9_2",title:"5.1 Backup PV systems",level:"2"},{id:"sec_10_2",title:"5.2 Photovoltaic water pumping system",level:"2"},{id:"sec_12",title:"6. Maintenance and fault detection techniques in PV systems",level:"1"},{id:"sec_13",title:"7. Case study",level:"1"},{id:"sec_13_2",title:"7.1 Photovoltaic backup systems",level:"2"},{id:"sec_13_3",title:"7.1.1 The causes of breakdown at each element",level:"3"},{id:"sec_13_4",title:"7.1.1.1 Causes of the battery and cable breakdown",level:"4"},{id:"sec_14_4",title:"7.1.1.2 Causes at the level of the inverter and PV module",level:"4"},{id:"sec_16_3",title:"7.1.2 The breakdown tree diagram used for the diagnosis of the breakdown in the studied system",level:"3"},{id:"sec_18_2",title:"7.2 Photovoltaic water pumping systems",level:"2"},{id:"sec_20",title:"8. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Deli K, Tchoffo Houdji E, Djongyang N, Njomo D. Operation and maintenance of back-up photovoltaic systems: An analysis based on a field study in Cameroon. African Journal of Science, Technology, Innovation and Development. 2017;9(4):437-448\n'},{id:"B2",body:'International Energy Agency (IEA). Statistics, Renewables Information. 2011\n'},{id:"B3",body:'International Energy Agency (IEA). Technology Roadmap Solar Photovoltaic Energy. 2014\n'},{id:"B4",body:'International Energy Agency. Trends 2013 in Photovoltaic Applications: Survey Report of Selected IEA Countries between 1992 and 2012. Report IEA-PVPS T1-23:2013. 2013\n'},{id:"B5",body:'Moreno-Garcia IM et al. Real-time monitoring system for a utility-scale photovoltaic power plant. Sensors. 2016;16(6):770\n'},{id:"B6",body:'Taylor M, Ralon IA. The power to change: Solar and wind cost reduction potential to 2025. Abu Dhabi, United Arab Emirates: Int Renew Energy Agency (IRENA). 2016. Available from: http://www.irena.org/\n\n'},{id:"B7",body:'Rekioua D, Matagne E. Optimization of Photovoltaic Power Systems. Modelization, Simulation and Control. New York: Springer-Verlag London Limited; 2012. ISBN 978-1-4471-2348-4. DOI: 10.1007/978-1-4471-2403-0\n'},{id:"B8",body:'Mboumboue E, Njomo D. Potential contribution of renewables to the improvement of living conditions of poor rural households in developing countries: Cameroon’s case study. Renewable and Sustainable Energy Reviews. 2016;61:266-279\n'},{id:"B9",body:'Ma T, Yang H, Lu L. Solar photovoltaic system modeling and performance prediction. Renewable and Sustainable Energy Reviews. 2014;36:304-315\n'},{id:"B10",body:'Marion B, Adelstein J, Boyle K. Performance Parameters for Grid-Connected PV Systems, NREL/CP-520-37358. 2005\n'},{id:"B11",body:'Marion B. A method for Modeling the current voltage curve of a PV module for outdoor conditions. Progress in Photovoltaics. 2002;10:205-214\n'},{id:"B12",body:'Kroposki B, Marion W, King DL, Boyson WE, Kratochvil J. Comparison of module performance characterization methods for energy production. In: Paper No. NREL/TP-520-29245. 2002\n'},{id:"B13",body:'Deli K, Djongyang N, Njomo D, Kidmo D. A rainy month performance evaluation of photovoltaic module and performance prediction of the PV water pumping systems under Soudano Sahelian climate conditions. International Journal of Electrical Components and Energy Conversion. 2018;4(1):61-71. DOI: 10.11648/j.ijecec.20180401.17\n'},{id:"B14",body:'Picault D, Raison B, Bacha S, de la Casa J, Aguilera J. Forecasting photovoltaic array power production subject to mismatch losses. Solar Energy. 2010;84:1301-1309\n'},{id:"B15",body:'Firth SK, Lomas KJ, Rees SJ. A simple model of PV system performance and its use in fault detection. Solar Energy. 2010;84(4):624-635\n'},{id:"B16",body:'Mellit A, Tina GM, Kalogirou SA. Fault detection and diagnosis methods for photovoltaic systems: A review. Renewable and Sustainable Energy Reviews. 2018;91:1-17\n'},{id:"B17",body:'Alam MK, Khan F, Johnson J, Flicker J. A comprehensive review of catastrophic faults in PV arrays: Types, detection, and mitigation techniques. IEEE Journal of Photovoltaics. 2015;5(3):982-997\n'},{id:"B18",body:'Pearce JM. Photovoltaics—A path to sustainable futures. Futures. 2002;34:663-674\n'},{id:"B19",body:'EL-Shimy M. Viability analysis of PV power plants in Egypt. Renewable Energy. 2009;34:2187-2196\n'},{id:"B20",body:'Sanz-Bobi MA editor. Use, Operation and Maintenance of Renewable Energy Systems. Green Energy and Technology. Cham, Heidelberg, New York, Dordrecht, London: Springer; 2014. DOI: 10.1007/978-3-319-03224-5\n'},{id:"B21",body:'Nyman D, Levitt J. Maintenance Planning, Coordination and Scheduling. 2nd ed. New York: Industrial Press; 2010\n'},{id:"B22",body:'Hatti M. Operation and Maintenance Methods in Solar Power Plants in Use, Operation and Maintenance of Renewable Energy Systems: Experiences and Future Approaches. Switzerland: Springer International Publishing; 2014. DOI: 10.1007/978-3-319-03224-5\n'},{id:"B23",body:'Crespo A, Moreu P, Gómez JF, Parra C, López M. The maintenance management framework: A practical view to maintenance management. Journal of Quality in Maintenance Engineering. 2009;15(2):167-178\n'},{id:"B24",body:'Tam ASB, Price JWH. A generic maintenance optimization framework. In: 7th Asia Pacific Industrial Engineering and Management Systems Conference, Bangkok, Thailand. 2006\n'},{id:"B25",body:'Hassanain MA, Froese TM, Vanier DJ. Framework model for asset maintenance management. Journal of Performance of Constructed Facilities. 2003;17:51\n'},{id:"B26",body:'Hao Q, Xue Y, Shen W, Jones B, Zhu J. A decision support system for integrating corrective maintenance, preventive maintenance, and condition-based maintenance. Construction Research Congress. 2010. pp. 470-479\n'},{id:"B27",body:'Madeti SR, Singh SN. A comprehensive study on different types of faults and detection techniques for solar photovoltaic system. Solar Energy. 2017;158:161-185\n'},{id:"B28",body:'Triki-Lahiani A, Bennani-Ben AA, Slama-Belkhodja I. Fault detection and monitoring systems for photovoltaic installations: A review. Renewable and Sustainable Energy Reviews. 2018;82:2680-2692. DOI: 10.1016/j.rser.2017.09.101\n'},{id:"B29",body:'Davarifar M, Rabhi A, El Hajjaji A. Comprehensive modulation and classification of faults and analysis their effect in DC side of photovoltaic system. Energy and Power Engineering. 2013;5(04):230\n'},{id:"B30",body:'Colli A. Failure mode and effect analysis for photovoltaic systems. Renewable and Sustainable Energy Reviews. 2015;50:804-809\n'},{id:"B31",body:'Foley G. Photovoltaic Applications in Rural Areas of the Developing World. Vol. 304. Washington, DC: World Bank Publications; 1995\n'},{id:"B32",body:'Labouret A, Villoz M. Solar Photovoltaic Energy, 5th edition, Dunod, English Translation 2010. Dunod, Paris: The Institution of Engineering and Technology; 2009\n'},{id:"B33",body:'DOE EERE. Procuring Solar Energy: A Guide for Federal Facility Decision Makers. 2010. Available from: https://www1.eere.energy.gov/solar/pdfs/47854.pdf\n\n'},{id:"B34",body:'Martifer Solar SA. PVTRIN Training course-Troubleshooting Guide. 2011. Available from: https://ec.europa.eu/energy/intelligent/projects/sites/iee-projects/files/projects/documents/pvtrin_troubleshooting_guide_for_installers_en.pdf\n\n'},{id:"B35",body:'IEC 61724, Photovoltaic System Performance Monitoring Guidelines for Measurement, Data Exchange, and Analysis; Switzerland, Geneva. 1998\n'},{id:"B36",body:'Limnios N, Ziani R. An algorithm for reducing cut sets in fault-tree analysis. IEEE Transactions on Reliability. 1986;35(5):559-562\n'},{id:"B37",body:'Limnios N. Fault Trees, Control System Robotics and Manufacturing. Unites States: ISTE; 2007. ISBN 10: 1905209304; ISBN 13: 9781905209309\n'},{id:"B38",body:'Bun L. Détection et localisation de défauts dans un système photovoltaïque, Laboratoire Génie électrique G2ELAB, Genoble, Rapport de thèse tel-00647189v1 > 2011. 2011\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Kodji Deli",address:"delikodji27@yahoo.fr",affiliation:'
Department of Renewable Energy, National Advanced School of Engineering, University of Maroua, Maroua, Cameroon
Department of Renewable Energy, National Advanced School of Engineering, University of Maroua, Maroua, Cameroon
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Further to that, several emerging robotic technologies are highlighted for their potential applications in next-generation robotic surgery.",book:{id:"5798",slug:"surgical-robotics",title:"Surgical Robotics",fullTitle:"Surgical Robotics"},signatures:"Zheng Wang, Sicong Liu, Jing Peng and Michael Zhiqiang Chen",authors:[{id:"197125",title:"Dr.",name:"Zheng",middleName:null,surname:"Wang",slug:"zheng-wang",fullName:"Zheng Wang"},{id:"197412",title:"Dr.",name:"Sicong",middleName:null,surname:"Liu",slug:"sicong-liu",fullName:"Sicong Liu"},{id:"204520",title:"Dr.",name:"Jing",middleName:null,surname:"Peng",slug:"jing-peng",fullName:"Jing Peng"},{id:"204521",title:"Dr.",name:"Michael",middleName:null,surname:"Chen",slug:"michael-chen",fullName:"Michael Chen"}]},{id:"27417",doi:"10.5772/28013",title:"Utilizing the Functional Work Space Evaluation Tool for Assessing a System Design and Reconfiguration Alternatives",slug:"utilizing-the-functional-work-space-evaluation-tool-for-assessing-a-system-design-and-reconfiguratio",totalDownloads:5403,totalCrossrefCites:4,totalDimensionsCites:7,abstract:null,book:{id:"889",slug:"robotic-systems-applications-control-and-programming",title:"Robotic Systems",fullTitle:"Robotic Systems - Applications, Control and Programming"},signatures:"A. 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Urbanic",authors:[{id:"72425",title:"Dr.",name:"Jill",middleName:null,surname:"Urbanic",slug:"jill-urbanic",fullName:"Jill Urbanic"},{id:"119083",title:"Dr.",name:"Ana",middleName:null,surname:"Djuric",slug:"ana-djuric",fullName:"Ana Djuric"}]}],mostDownloadedChaptersLast30Days:[{id:"27402",title:"Novel Assistive Robot for Self-Feeding",slug:"novel-assistive-robot-for-self-feeding",totalDownloads:6247,totalCrossrefCites:17,totalDimensionsCites:24,abstract:null,book:{id:"889",slug:"robotic-systems-applications-control-and-programming",title:"Robotic Systems",fullTitle:"Robotic Systems - Applications, Control and Programming"},signatures:"Won-Kyung Song and Jongbae Kim",authors:[{id:"64432",title:"Dr.",name:"Won-Kyung",middleName:null,surname:"Song",slug:"won-kyung-song",fullName:"Won-Kyung Song"},{id:"72153",title:"Dr.",name:"Jongbae",middleName:null,surname:"Kim",slug:"jongbae-kim",fullName:"Jongbae Kim"}]},{id:"58074",title:"Robotic Hiatal Hernia Repair",slug:"robotic-hiatal-hernia-repair",totalDownloads:1592,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Robotic surgery has revolutionized medicine during the last 16 years by transformation of the classic operating theaters into computer-mediated working stations. Numerous procedures have been proved to be feasible and safe by using the continuously evolving, various robotic platforms. From the early beginnings of this revolution, challenging operations such as those concerning the gastroesophageal junction, especially in super-obese patients or during redo operations, proved out to have certain benefits when performed robotically, both for patients as well as for surgeons.",book:{id:"5798",slug:"surgical-robotics",title:"Surgical Robotics",fullTitle:"Surgical Robotics"},signatures:"Konstantinos Konstantinidis, Michael Konstantinidis, Savvas Hirides\nand Petros Hirides",authors:[{id:"214804",title:"Prof.",name:"Konstantinos",middleName:null,surname:"Konstantinidis",slug:"konstantinos-konstantinidis",fullName:"Konstantinos Konstantinidis"},{id:"214805",title:"Dr.",name:"Savvas",middleName:null,surname:"Hirides",slug:"savvas-hirides",fullName:"Savvas Hirides"},{id:"220656",title:"Mr.",name:"Michael",middleName:null,surname:"Konstantinidis",slug:"michael-konstantinidis",fullName:"Michael Konstantinidis"},{id:"220657",title:"Dr.",name:"Petros",middleName:null,surname:"Hirides",slug:"petros-hirides",fullName:"Petros Hirides"}]},{id:"27422",title:"Robotic Software Systems: From Code-Driven to Model-Driven Software Development",slug:"robotic-software-systems-from-code-driven-to-model-driven-software-development",totalDownloads:3835,totalCrossrefCites:18,totalDimensionsCites:20,abstract:null,book:{id:"889",slug:"robotic-systems-applications-control-and-programming",title:"Robotic Systems",fullTitle:"Robotic Systems - Applications, Control and Programming"},signatures:"Christian Schlegel, Andreas Steck and Alex Lotz",authors:[{id:"64903",title:"Prof.",name:"Christian",middleName:null,surname:"Schlegel",slug:"christian-schlegel",fullName:"Christian Schlegel"},{id:"150649",title:"Dr.",name:"Andreas",middleName:null,surname:"Steck",slug:"andreas-steck",fullName:"Andreas Steck"},{id:"150650",title:"Dr.",name:"Alex",middleName:null,surname:"Lotz",slug:"alex-lotz",fullName:"Alex Lotz"}]},{id:"55664",title:"Bilateral Axillo-Breast Approach Robotic Thyroidectomy: Introduction and Update",slug:"bilateral-axillo-breast-approach-robotic-thyroidectomy-introduction-and-update",totalDownloads:1841,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Bilateral axillo-breast approach (BABA) endoscopic thyroidectomy was introduced at Seoul National University Hospital in 2004, and it has been used to treat a variety of benign and malignant thyroid diseases. In 2008, we began using the da Vinci robotic system with BABA endoscopic thyroidectomy and reported our initial experiences in 2009. Since then, the outcomes of many clinical studies have been reported. In this chapter, we will introduce the BABA robotic thyroidectomy (RoT) procedure and review evidence for the safety of performing BABA. First, we will introduce the history of BABA RoT, which is based on an endoscopic BABA method. Second, we will review the BABA RoT equipment, operating room (OR) set-up, and the procedures, including surgical indications. Third, technical, oncological, and functional evidence for the safety of performing BABA will be described. Fourth, we will highlight the esthetic superiority of BABA RoT compared with conventional thyroidectomy. Finally, the BABA robotic modified radical neck dissection procedure will be introduced, with mention of our experiences and special concerns. We conclude that BABA RoT is technically, oncologically, and functionally safe. In addition, its esthetic superiority should be emphasized. Further research on the prognosis of patients treated by BABA RoT should follow in the future.",book:{id:"5798",slug:"surgical-robotics",title:"Surgical Robotics",fullTitle:"Surgical Robotics"},signatures:"Do Hoon Koo, Dong Sik Bae and June Young Choi",authors:[{id:"198460",title:"Dr.",name:"Do Hoon",middleName:null,surname:"Koo",slug:"do-hoon-koo",fullName:"Do Hoon Koo"},{id:"200696",title:"Prof.",name:"Dong Sik",middleName:null,surname:"Bae",slug:"dong-sik-bae",fullName:"Dong Sik Bae"},{id:"200697",title:"Prof.",name:"June Young",middleName:null,surname:"Choi",slug:"june-young-choi",fullName:"June Young Choi"}]},{id:"55313",title:"The Surgical Robot: Applications and Advantages in General Surgery",slug:"the-surgical-robot-applications-and-advantages-in-general-surgery",totalDownloads:1916,totalCrossrefCites:2,totalDimensionsCites:4,abstract:"The field of General Surgery with its multiple sub‐specialties has experienced the progression of minimally invasive procedures performed with the robotic technology since the last decade. The robotic applications are extensive and have contributed to the enrichment of the surgical sub‐specialties based on advantages such as increased surgeon control and autonomy, superior instrument dexterity and tissue handling, improved three‐dimensional visualization, wristed articulation, all of this despite the lack of haptic feedback. The sub‐specialties of Colorectal, Hepatobiliary and Pancreatic, Gastric Oncologic, Bariatric, Foregut, Pediatric, Endocrine, and Hernia Surgery, in addition to General Surgery as the principal specialty, have produced several high‐quality randomized controlled trials, meta‐analyses, prospective and retrospective series which have established, in many instances, superior results to those of laparoscopy, and at least non‐inferior outcomes over the years. From the first pioneer single‐surgeon experiences around the world to the most recent large trials, including the first Robotic General Surgery case series in an American community hospital not classified as a tertiary referral center, patients continue to benefit from this technology as surgeons engage in overcoming their learning curve and training their teams, involving their hospital administrators and working with the industry to perfect their techniques for the sake of their patients.",book:{id:"5798",slug:"surgical-robotics",title:"Surgical Robotics",fullTitle:"Surgical Robotics"},signatures:"Rodolfo José Oviedo Barrera",authors:[{id:"204248",title:"Dr.",name:"Rodolfo",middleName:"J.",surname:"Oviedo",slug:"rodolfo-oviedo",fullName:"Rodolfo Oviedo"}]}],onlineFirstChaptersFilter:{topicId:"1270",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[],lsSeriesList:[],hsSeriesList:[],sshSeriesList:[],testimonialsList:[]},series:{item:{id:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517",scope:"Paralleling similar advances in the medical field, astounding advances occurred in Veterinary Medicine and Science in recent decades. These advances have helped foster better support for animal health, more humane animal production, and a better understanding of the physiology of endangered species to improve the assisted reproductive technologies or the pathogenesis of certain diseases, where animals can be used as models for human diseases (like cancer, degenerative diseases or fertility), and even as a guarantee of public health. Bridging Human, Animal, and Environmental health, the holistic and integrative “One Health” concept intimately associates the developments within those fields, projecting its advancements into practice. This book series aims to tackle various animal-related medicine and sciences fields, providing thematic volumes consisting of high-quality significant research directed to researchers and postgraduates. It aims to give us a glimpse into the new accomplishments in the Veterinary Medicine and Science field. By addressing hot topics in veterinary sciences, we aim to gather authoritative texts within each issue of this series, providing in-depth overviews and analysis for graduates, academics, and practitioners and foreseeing a deeper understanding of the subject. Forthcoming texts, written and edited by experienced researchers from both industry and academia, will also discuss scientific challenges faced today in Veterinary Medicine and Science. 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After almost 32 years of teaching at the University of Trás-os-Montes and Alto Douro, she recently moved to the University of Évora, Department of Veterinary Medicine, where she teaches in the field of Animal Reproduction and Clinics. Her primary research areas include the molecular markers of the endometrial cycle and the embryo–maternal interaction, including oxidative stress and the reproductive physiology and disorders of sexual development, besides the molecular determinants of male and female fertility. She often supervises students preparing their master's or doctoral theses. She is also a frequent referee for various journals.",institutionString:null,institution:{name:"University of Évora",institutionURL:null,country:{name:"Portugal"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:3,paginationItems:[{id:"19",title:"Animal Science",coverUrl:"https://cdn.intechopen.com/series_topics/covers/19.jpg",isOpenForSubmission:!0,annualVolume:11415,editor:{id:"259298",title:"Dr.",name:"Edward",middleName:null,surname:"Narayan",slug:"edward-narayan",fullName:"Edward Narayan",profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",biography:"Dr. Edward Narayan graduated with Ph.D. degree in Biology from the University of the South Pacific and pioneered non-invasive reproductive and stress endocrinology tools for amphibians - the novel development and validation of non-invasive enzyme immunoassays for the evaluation of reproductive hormonal cycle and stress hormone responses to environmental stressors. \nDr. Narayan leads the Stress Lab (Comparative Physiology and Endocrinology) at the University of Queensland. A dynamic career research platform which is based on the thematic areas of comparative vertebrate physiology, stress endocrinology, reproductive endocrinology, animal health and welfare, and conservation biology. \nEdward has supervised 40 research students and published over 60 peer reviewed research.",institutionString:null,institution:{name:"University of Queensland",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null},{id:"20",title:"Animal Nutrition",coverUrl:"https://cdn.intechopen.com/series_topics/covers/20.jpg",isOpenForSubmission:!0,annualVolume:11416,editor:{id:"175967",title:"Dr.",name:"Manuel",middleName:null,surname:"Gonzalez Ronquillo",slug:"manuel-gonzalez-ronquillo",fullName:"Manuel Gonzalez Ronquillo",profilePictureURL:"https://mts.intechopen.com/storage/users/175967/images/system/175967.png",biography:"Dr. Manuel González Ronquillo obtained his doctorate degree from the University of Zaragoza, Spain, in 2001. 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