Which device is used to ensure power to a server or network device during short power outages?

1 Introduction

Power outages pose significant economic and social impacts on communities around the world. The increasing reliance of the society on electricity reduces the tolerance for power outages, and consequently highlights the need for enhancing the power grid resilience against natural hazards. Although these hazards are low-probability events, even one occurrence of an extreme event can be catastrophic for infrastructure systems. For instance, in 2017, Hurricane Harvey reached Texas as a Category 4 hurricane and resulted in severe damage to the built infrastructure [1, 2]. While the likelihoods of occurrence are small relative to other disturbances, they are not significantly small. For example, over the past four decades, the state of Texas has experienced weather-related events with a frequency of 1.7 events per year [2]. Thus, it is necessary to prepare infrastructure systems against these low-probability high-consequence events in hazard prone regions by adopting some strategies [3]. Recent extreme weather-related events induced substantial damage in electric infrastructure and left large numbers of customers without power [4]. In fact, extreme climatic events, such as hurricanes, have caused over 80% of the power outages in the United States [5]. As a recent example, on October 2020, Hurricane Zeta hit the Gulf of Mexico and left over 2.6 million residents without power, while it only reached a Category 2 hurricane at its peak [6]. Among the components of the power grid, power distribution networks (PDNs) are the most vulnerable in the face of extreme climatic events [7,8]. Thus, given the devastating regional and national consequences that hurricanes can incur and the ever-increasing reliance of the society on electricity, hurricane resilience enhancement of PDNs is crucial for public safety and economic prosperity.

Resilience is the ability of a system to absorb shocks and to quickly recover from disturbances [9–11]. Resilience is deemed as a comprehensive risk-based measure due to its ability to reflect on both the damage that the system has sustained, which is the concern of reliability, and the recovery performance of the system. Several studies have attempted to improve resilience of PDNs via planning (e.g., [12,13]). An effective strategy for resilience enhancement of PDNs is replacement of deteriorated utility poles with new ones, however, this action is costly. Unlike the corrective maintenance strategy that is applied after the occurrence of a failure, preventive maintenance is performed prior to a potential failure to decrease the likelihood of disruption in the services provided by the system. The latter maintenance contains a wide range of practices, from periodic chemical treatment to replacing poles with new wood poles or even new poles with durable construction materials (e.g., [14,15]). In practice, utility companies perform annual inspection and preventive maintenance actions to ensure the safety of PDNs. In fact, the National Electric Safety Code (NESC) [16] mandates utilities to replace deteriorated wood poles with new ones. The NESC prioritizes replacement of wood utility poles based on the remaining strength of these structures. This strategy is followed in over 90% of US states as a hardening solution to increase the hazard reliability of PDNs [17]. More specifically, the NESC requirement mandates replacing poles, once their remaining strength falls below two-thirds of the initial strength. This preventive maintenance strategy is not adequate, as it does not consider all the factors that affect the failure probability of poles. Reliability-based management can be a remedy to address this limitation of NESC strategy. Although reliability-based management considers the failure probability of poles in finding optimal preventive maintenance actions, it does not take into account the importance of poles for network services in the decision-making process. Similar to reliability-based management, the NESC strength-based strategy also does not consider the risks associated with the failure of poles. For example, a utility pole that serves a few customers can have a higher failure probability than a pole that serves a large number of customers. If the consequences of failure for network services are not considered in the decision-making, replacing the former pole becomes the priority because it plays a more important role in the reliability of the system. However, if the network consequences of failure are considered via a risk-based framework, replacing the latter pole could be more beneficial to the PDN, as it can reduce the number of power outages in the case that a hurricane hits the system. Risk-based management of systems has been investigated for different structures exposed to extreme events, such as bridges [18–20], buildings [21–23], and levee infrastructure systems [24]. In the case of utility poles, risk-based prioritization strategies (e.g., [25,26]) have been proposed as an alternative to the NESC strength–based strategy. For example, the authors proposed a risk metric called expected outage reduction (EOR) to prioritize pole replacements based on the expected power outage reduction if an existing pole is replaced by a new pole [25]. Nevertheless, the lack of integration with optimization techniques questions the optimality of these preventive maintenance strategies.

Given the limited available budget and resources, optimization is required to facilitate optimal preventive maintenance of large systems. Motivated by this fact, the authors developed a mixed-integer nonlinear programming (MINLP) model and solved this model by branch and bound (BB) algorithm to determine the optimal preventive maintenance planning for resilience enhancement of PDNs [27]. In this chapter, the authors investigate the application of an evolutionary algorithm (EA) to determine optimal preventive maintenance actions for life-cycle resilience enhancement of PDNs. More specifically, this chapter presents a decision-making framework for resilience enhancement of PDNs that are susceptible to gradual deterioration and face the risk of exposure to multiple stochastic hurricane events during the decision horizon. The proposed framework integrates modeling of hurricane hazards, performance of physical components of PDNs, and probabilistic resilience quantification to form a nonlinear constrained optimization problem (CoP) with binary decision variables. This optimization model facilitates the risk-based management of PDNs, with the objective of maximizing the life-cycle resilience by determining optimal preventive maintenance actions. The major complexity of this optimization problem arises from the large number of combinations of possible maintenance actions over an extended decision horizon as well as the existing constraints.

Given the complexity and scale of the CoP for resilience enhancement, an EA is presented herein to solve the problem. EAs are a subset of metaheuristic algorithms, which combine the randomization and local search inspired by natural phenomena to solve global optimization problems. Inspired by the biological evolution, EAs have become a type of simple and effective optimization tool without requiring much specific domain knowledge. EAs usually start with a randomly generated population that is evolved over subsequent generations. One key feature of EAs is that the best individuals are combined to form the next generation, allowing the population to be optimized over generations.

EAs include several primary groups of techniques such as genetic algorithm (GA) [28], genetic programming (GP) [29], evolution strategy (ES) [30], and differential evolution (DE) [31]. As an important branch of EAs, DE was originally introduced by Storn and Price [31]. Similar to other EAs, DE is a population-based optimization algorithm that solves difficult optimization problems. The straightforward implementation procedure of DE has increased its application in many fields. DE has three main advantages: (1) it is able to find the true global minimum of a multimodal search space regardless of the initial parameter values, (2) it has fast convergence, and (3) it requires limited control parameters [32]. DE was originally designed for solving unconstrained optimization problems. However, thanks to the popularity and potential of DE, techniques based on DE have been developed for solving CoPs [33–36]. DE has also been applied to problems concerning binary variables [37–45], which fit the profile of the problem discussed herein.

This chapter presents a binary differential evolution (BDE) algorithm for constrained optimization problems and applies the method for optimal resilience enhancement of PDNs. This algorithm, called BICDE, is the integration of the BDE algorithm proposed by Gong and Tuson [38] with the improved (μ+λ)-constrained differential evolution (ICDE) algorithm proposed by Jia et al. [36]. The rest of this chapter is outlined as follows: in Section 2, an overview of the studied PDN is presented and the details of the optimization model are provided. A more detailed introduction of DE, BDE, the constraint-handling strategy, and the IBCDE algorithm is provided in Section 3 of this chapter. Section 4 discusses the results of this study. Finally, in Section 5, conclusions of this chapter are presented.

Emergency Power (NAS Proven)

Although power outages are infrequent in most modern grids, a source of power for critical infrastructure during the unplanned loss of generation is increasingly important, especially in large metropolitan areas. Plans for future inner-city grids include emergency power for safety lighting, traffic control, water supply, and first responder communications during and after severe events such as natural disasters. Multi-megawatt NAS battery systems equipped with G50 or E50 modules can be configured to supply up to 8 h of emergency power. They can also be designed to hold a defined quantity of energy in reserve for emergencies (e.g., 1–4 h equivalent) while conducting the load leveling applications described above.

Minimising the damage

An unscheduled power outage is just that, it is unscheduled and the power simply stops. The primary actions to prepare for power outages are:

Set/adjust machines to ‘fail safe’ or ‘fail to safe’ conditions. A power outage can leave machines in an unsafe or unstable condition. If it is possible, then setting all machines (don’t forget the services) to ‘fail to safe’ is the prime action.

Prepare checklists and procedures for all actions in the event of a power outage, e.g., isolate machines, clear conveyors, clear assembly machines and set machines in correct condition for restart.

Identify any non-electrical energy users and decide the actions to be taken, e.g., if there are gas-fired ‘flamers’ for PP printing then these should be turned off.

Prevent data loss (or corruption) for all computers and controls. This was less critical in the 1980’s when there was less dependence on computers but now a power outage can easily lead to loss of data and perhaps even damage to machines using computer controls.

Uninterruptible power supplies (UPS) are a method of providing continued power for computers and controllers in the event of a power outage. They will never keep a plastics processing site operating in the event of a power outage because they have very limited storage (they are only after all a rechargeable battery and a rectifier). Whilst UPS are simply not big enough for machines, they can be used for computers (and servers) to prevent data corruption and loss, e.g., I am running one right now on this computer to cover the rare event of a power outage in my area. A UPS will last a long time, is transparent in use and will protect data.

Brownouts and blackouts are different things.

Blackouts are a total failure of the supply.

Brownouts are when the supply voltage or frequency fluctuates outside the normal tolerances of the site. These are actually a more common risk but are mostly hidden and sites need to be able to turn off non-core services or operations quickly.

Tip – All office computers (and servers) should be protected by UPS systems. This can be ‘system-wide’ or use an individual UPS for each computer.

Tip – Always gracefully shut-down the computer as soon as possible after the power loss. Do not be tempted to keep working – the UPS will eventually drain and the computer will stop.

Tip – Back-up, back-up and back-up again. A power outage is a nuisance, data loss can be fatal. As a rule of thumb, back-ups should be stored off-site or at least the wing-span of a jumbo jet away from the machine.

It is also strongly recommended that machine computers and controllers are also protected by a UPS. These should be wired in separately from the main supply inside the machine or using a ‘system-wide’ approach and low-voltage cabling (use the wiring diagrams to find where a UPS can be inserted to protect the computers and controllers). This will mean that the controller will still be active in the event of a power outage and prevent data loss or corruption BUT the machine must still be shut-down to prevent activation when the power comes back on.

The ability to cope with brownouts or blackouts is part of the overall business resilience or disaster recovery planning.

Do not leave it too late to test systems and procedures.

Tip – Fit small UPS to all machines to prevent data loss or corruption.

Tip – Gracefully shut-down machine computers and controllers as soon as possible to prevent machine activation in the event of power being restored.

Tip – Make sure that you have back-up copies of all machine settings and data. As with all back-ups, these should be stored away from the machine.

Tip – Robots present a specific problem because they use higher power levels than controllers. If possible, set up a UPS to take robots to ‘safe’ position (and never enter the area unless the power is ‘locked out’).

Assuming a power outage is going to happen then setting up systems to minimise the damage is the first thing to be done.

17.1 Power Quality Equipment

Due to high loss of revenue from power outages or even brief interruptions, the financial institutions often rely up on many types of equipment to provide immunity from loss of power. The basic equipment sets are UPS, standby generators, and alternative ties as shown in Table 17.2 [3]. Alternative ties represent power supplied to the enterprises from multiple power utilities. These methods to suppress the likelihood of loss of power are employed by not only financial institutions, data processing centers, and telecommunication centers but also by refineries and hospitals. Even paper mills and semiconductor chip fabrication faculties make use of UPS and standby generators to avoid costly interruption of production lines.

Table 17.2. Power Quality Equipment Types

24.5 Timing Matters: Case Study of Italy (2003)

One of the most reported and researched power outages occurred in Italy on September 28, 2003. At about 3 a.m., power coming from Switzerland to Italy was cut off as two key transmission lines across the border were damaged in a storm. As a result, all of Italy (except the islands of Sardinia and Elba) remained without power for up to 12 hours. Affecting a total of 56 million people, it was the largest blackout in Italy in 70 years. In the immediate aftermath of the blackout, 110 trains were canceled, with 30,000 people stranded on trains across Italy.

The root causes of the failure of the transmission line and the subsequent power outage have been extensively studied [27–29]. The case of the power outage in Italy is of special significance as it underscores the importance of considering the time of occurrence while estimating the costs of interruption.

The night of September 27, 2003 was the annual overnight festivities, Nuit Blanche (White Night) in Rome. As a result, many people were on the streets and all public transportation was still operating around the time of the blackout, despite the fact that it was very late at night. Several hundred people were trapped in underground trains. Coupled with heavy rain at the time, many people spent the night sleeping in train stations and on streets in Rome. While it was reported that emergency services coped well with the situation, several traffic accidents were said to have been caused as a result of the failure of traffic signals [30].

In recent years, only a limited number of studies took into consideration the specific circumstances of the time of occurrence of interruptions. Yet, information on the services interrupted and their correlation to the time of occurrence can be used to operate the power system more effectively from a societal perspective. For instance, electricity producers, transmission system operators (TSOs), and local network operators can make decisions about maintenance that influence the probability of a supply interruption.

Case studies such as those presented on Cyprus and Italy provide important insights to understanding the implications of outages in existing power systems. The situation may however change as power systems accommodate higher shares of variable renewable energy sources.

Shelter cost

Because of extreme event impacts, including power outage, houses may not be livable, and a proportion of the population will need to seek alternative housing or shelter. There is a difference between sheltering and housing during a postdisaster period [16]. Sheltering represents the activity of staying in a place during or immediately after the disaster where regular daily activities are suspended. Housing is defined as the activity of staying in a place when normal daily activities are returned to normal conditions, but a residence is not suitable for habitation. As a result of this difference, providing a place for people to stay during and after the disaster is based on four stages, which are presented as follows [16,17]:

Emergency shelter, which can be a public shelter, taking shelter at a friend's house, or shelter under a plastic sheet. The duration for emergency shelter is usually from one night to a couple of days. Extensive preparation of food, water, and medication is not necessary for this period.

Temporary shelter, which can be a public shelter or a tent, and lasts up to a couple of weeks. Extensive preparation of food, water, and medication is essential during this stage.

Temporary housing, in which the activities are returned to normal conditions, and people are living in a temporary housing.

Permanent housing, in which people return to their reconstructed homes, or they settle in a new home. In this period everything has returned to predisaster conditions.

The affected customers may or may not pass through all of these stages. In addition, some stages may be applied simultaneously for some customers. Most of the studies include an analysis of temporary housing during the postdisaster stage [18]. The proposed cost model is analyzed during the initial recovery period; therefore, temporary shelter costs are used for the 10-day duration analysis.

Many factors such as quality, durability, security, size, weather resistance, design, privacy, noise, cleanness, and providing necessary services affect the cost of temporary shelter. Also, some customers may stay in a hotel rather than shelters, with an average estimated cost of $150.25 per night. However, a range of $50–100 per night per family is reasonable for the temporary shelter cost, and it is added to the cost model at hour 23:00 of each day and shown in Fig. 4.6.

11.1 Introduction

A reliable supply of electricity free from power outages is vital for the stability and economic development of any country. The generation of electricity nowadays relies on an increasingly complex set of electricity suppliers. These include: fossil-fueled power stations burning coal or oil or natural gas, wood- and biomass-burning power stations, nuclear power stations, and an increasing number of renewable energy resources, which include hydroelectric power, wind turbines, and solar photovoltaic panels. The difficulty comes when the grid operators have to balance exactly the electricity produced against the demand by the customers. With the increasing use of intermittent renewable energy, this becomes progressively more and more difficult, as it is sometimes impossible to forecast the exact amount of energy from solar and wind sources.

As a result of climate change and global warming, it is imperative that we continue developing and using renewable forms of energy, free of carbon. The renewable industry is still in its infancy, as judged by the fraction of electricity (24.5%) presently produced by renewable energy worldwide in 2016 [1]. Most of present global renewable energy is pumped hydroelectricity, which makes up 68% of all renewable forms of energy and 16.6% of all electricity worldwide [1]. The only other renewable forms of energy producing any significant amounts of electricity are solar and wind energy, both of which produce intermittent amounts of electricity, with a total of about 5.5% of all worldwide production [1]. The development and implementation of both solar PV and wind energy (onshore and offshore) have advanced enormously over the past decade, but their production is very much outweighed by hydropower. Unfortunately, solar and wind energy often go to waste as they come on stream when there is no demand for electricity; for example, at night when the wind blows and the demand for electricity is low, or during the middle of the day when the sun shines, and again when the demand for electricity is low. Renewable and intermittent forms of energy, such as wind and solar photovoltaic, need storage facilities to be truly effective. A stockpile of stored energy would make the balancing of the national grid a much easier task.

The advances made in developing solar and wind energy have not been supported by similar advances in storing energy. The main reason for this is that electricity is not easy to store. Many of our present energy sources are indeed stored forms of energy: solid coal, liquid oil, or gaseous methane. As such these carbon-based energy sources are very convenient sources of energy and this makes the development of new and difficult technologies less attractive to persuade investors. We all prefer the status quo to investigating, researching, and finally implementing new ways of doing things.

If the level of back-up renewable energy is small compared to the conventional generation capacity, the implementation of renewable energy can be forecast with reasonable accuracy. However if the level of intermittent renewable energy is large, in relation to base load electricity generation, the task of balancing the demand becomes very much more complex, difficult, and uncertain [2]. For renewable energy to play a major part in supplying electricity to the national grid, it would have to be backed up with large storage facilities.

8.1.3.1 Development history of intelligent status monitoring of power equipment in China

There are three main methods of equipment monitoring in China: power outage test, online monitoring, and condition monitoring; the last two methods do not involve power interruption. In recent years, domestic and foreign scholars researched and achieved a great deal regarding online monitoring and condition monitoring for insulation condition of power transmission equipment, and the development has gone through the following three stages:

The online testing phase began around the 1970s. At that time, the insulation parameters of electrical equipment (mainly the leakage current) were only measured for nonstop power supply. The structure is simple, the test items are very few, and the test equipment must be insulated to the ground. The sensitivity of the test is very poor, so the scope of its application is very small, and it cannot be widely used.

Beginning in the 1980s, there appears a variety of special online test equipment, which makes condition monitoring technology change from traditional analog measurement to digital measurement and makes the test get rid of the traditional measurement mode of connecting the test equipment directly to the test circuit, and the test uses the sensor to convert the electrical signal, which can be directly measured by the digital instrument. At the same time, there is some other test equipment that can reflect the insulation condition through the nonelectric quantity measurement, such as the infrared device, the ultrasonic device, and so on. In this period the representative device is LCD-4 type arrester leakage current tester.

From the beginning of the 1990s, there appears a microcomputer multifunctional insulation condition monitoring system using digital waveform acquisition and processing technology as the core. Advanced sensor technology, computer technology, and digital waveform acquisition and processing technology are used to achieve more insulation condition monitoring (such as dielectric loss tangent tan delta, capacitance, leakage current, partial discharge, chromatography, etc.). This kind of monitoring system can work in real time continuously, and the content is rich, the amount of information is large, the processing speed is fast, and the automation of insulation monitoring is realized.

All in all, although the application of online monitoring in the current stage has its advantages, for the future of smart grid construction, condition monitoring is clearly more attractive, and it has more advantages in long-term development. With the development and application of sensor technology, signal acquisition technology, digital analysis technology, and computer technology, in the future the condition monitoring based on condition monitoring technology will become an important part of smart substations.

12.4.5 The Relationship Between Electricity Storage Systems and PVs

Generally, residential ESS should provide their owners with electricity during a power outage, while saving the owners money on their monthly utility bills. If a resident installs both a storage system and a PV system, the home electricity supply system is robust, further reducing reliance on peak usage. Some expect synergistic effects from storage batteries and a PV system, and install both in their homes. Figure 12.5 shows the current state of installations and intentions, demonstrating that the owners or future owners of PV systems tend to also install storage battery systems, compared to non-PV owners.

Table 12.2 shows a detailed description of the current installations. The number of respondents who use a storage battery alone is 56, though the number of residents who intend to use both an energy storage and a PV system is 123 out of 1397 respondents. Of the 123 respondents, about 71% (87 respondents) indicated that they will install both systems. This result implies that more people assume that the combination of these systems is something like “bread and butter.”

Table 12.2. Cross Tabulation of Ownership Status of and Attitudes Toward PV Systems and Storage Battery Systems

10.4.5 Energy storage in uninterruptible power supplies

UPS is an energy storage application used to prevent losses due to power outages or low power quality conditions. They are commonly used to prevent special and sensitive loads from being affected by power cuts. In addition, UPS can perform power quality correction with their parallel operation types. UPS has long been used in commercial buildings and service buildings such as hospitals or in special facilities such as data centers where energy continuity is important. UPS can preferably be used in residential buildings. As mentioned earlier, UPSs are used for two main purposes. The first is used as a backup power source to prevent power outages. The second serves as a filter task for correcting low power quality conditions. The UPSs used for the first purpose are generally diesel generator systems in traditional applications. It has advantages such as quick start-up and fuel storage. However, there are disadvantages such as noisy operation, releasing exhaust gases, and high fuel costs. The use of different energy storage applications such as grid connected battery energy storage applications or flywheels may eliminate these disadvantages.

Some UPS systems are designed to correct low power quality requirements. Voltage and frequency values expressed by low power quality conditions are not in the required limit values. These corruptions in voltage and frequency values may damage the electrical devices of consumers and may cause problems in the grid if the necessary precautions are not taken. With the use of energy storage in UPSs, voltage spike/peak, voltage swell/surge, voltage sag, undervoltage, noise, and current harmonics problems can be avoided.

Providing UPS functions with distributed energy storage systems operated by distribution companies is very easy. These applications can be used more effectively compared with traditional UPS systems. In addition, benefits can be provided in terms of RES integration into the system in this structure as it becomes more economical [68].

If one of the large power plants fails, the frequency and voltage levels must be maintained to ensure stability and reliability in the power system. The way to achieve this is the total power value of the system is proportionally distributed to other power plants in the system. Other power plants in the system should use an additional reserve capacity with outside normal operating conditions. Power plants need to produce at a value above normal power, and the power value of the disabled plant must be transferred to the grid. To do this, either the plants must be operated below the nominal values or, if necessary, they must be operated with high capacity. These two situations lead to inefficient operation. In the United States, a superconductor magnetic energy storage method has been proposed and designed to meet the additional reserve capacity requirement of the grids in various scientific studies. The method is not used as arbitrage and similar energy storage applications but rather is intended to be used only to tolerate large power losses in the system. However, there are disadvantages such as the need for very high-cost cooling systems and large power converters for such a system. Various energy storage technologies such as batteries, ultracapacitors, and flywheels have the technological infrastructure to meet these needs. With the necessary power converter devices, these applications are possible depending on the grid. Several reserve definitions are possible for grids. Rotary reserve is an energy storage unit capable of power producing up to 10 min. Rotary reserve is a system that can be activated in as short as 10 s to maintain the frequency stability in case of high power losses [69]. The system, which focuses more on frequency regulation rather than energy continuity, is called frequency reactive reserve.

The additional reserve can be defined as an extra generation capacity below or above the highest demand value required to provide the energy needed by the electricity consumers. It is a generation capacity that has an inactive generation capacity or a cut-off load that can be commissioned in less than 10 min if needed. Two types can be provided; either it is activated in a short time when it is in a disabled state, or when it is operating in a way that feeds a certain load that can be cut off. This load is cut, and the generation power is transferred to the grid [70]. Rotary reserve systems are continuously synchronized to the grid, whereas. Additional reserve systems are independent of the grid. Therefore, if necessary, the grid should be supported by using the rotary reserve facilities first, and if necessary, additional reserve capacity should be activated after synchronization.

Backup resource loading is the generation capacity that can be realized in only 1 h. This application can only be used as an auxiliary source for reserve capacity. With the development of technology and reduction in costs, large-scale power applications of energy storage applications are becoming widespread. Scalable energy storage systems can be connected to electricity grids from very different points such as generation units, transmission systems, and distribution system or end consumers. In addition, the connection to the grid can be achieved with very short response times thanks to the power electronics. Thus, it makes the use of energy storage applications as rotary reserves attractive [71].