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Summer Heat and Data Center Growth Compounding East Coast Grid Risks

Aerial view of a coastal cityscape at sunset. Industrial rooftops and power lines are in the foreground, with a glowing, serene sky.

1. Introduction: The Fragile Equilibrium of the Modern Grid

The electric grid of the Eastern United States, particularly the sprawling territory managed by the PJM Interconnection, stands at a historical inflection point. For nearly a century, the fundamental mandate of grid operation has been the maintenance of equilibrium: a precise, second-by-second balancing act where the generation of electricity must exactly equal its consumption. This balance is maintained across a synchronous machine spanning thousands of miles, held together by the immutable laws of physics and the momentum of spinning turbines. However, the stability of this machine is currently under siege from a convergence of forces that its original architects never anticipated.

The catalyst for this disruption is the explosive proliferation of hyperscale data centers, driven principally by the sudden and voracious energy appetite of Artificial Intelligence (AI) training and inference models. This is not merely a story of rising demand; it is a narrative of structural incompatibility between the digital economy's exponential growth and the linear, capital-intensive timeline of physical infrastructure. The "East Coast," specifically the corridor stretching from Northern Virginia through Maryland and into Pennsylvania, has become the global epicenter of this conflict. Here, the densest concentration of data processing infrastructure in the world is pushing the electrical grid to its thermal and operational limits.

The forecasted consequences are stark. PJM Interconnection, the Regional Transmission Organization (RTO) responsible for coordinating the movement of wholesale electricity for 65 million people, has issued unprecedented warnings regarding resource adequacy. The specter of rolling blackouts—controlled, rotating power outages engineered to prevent total system collapse—has moved from the realm of remote theoretical risk to a plausible near-term reality for the summers of 2026 and beyond. This report provides an exhaustive analysis of this reliability crisis, dissecting the complex interplay of engineering constraints, market failures, regulatory bottlenecks, and the sheer thermodynamics of the AI revolution.

1.1 The scale of the Disruption

To grasp the magnitude of the challenge, one must look beyond standard load growth metrics. The PJM 2025 Long-Term Load Forecast indicates that summer peak usage is projected to climb by approximately 70 gigawatts (GW) to reach 220 GW over the next 15 years.1 For context, the previous record summer peak for the PJM footprint was 165 GW, set in 2006.1 The sheer volume of new demand—30 GW of which is attributed specifically to data centers between 2025 and 2030—is equivalent to adding the entire generating capacity of a medium-sized industrialized nation to the grid in a fraction of the time it typically takes to plan and build such infrastructure.1

This demand shock is occurring simultaneously with a rapid contraction of traditional supply. The grid is losing dispatchable generation capacity—primarily coal and older natural gas plants—faster than it is being replaced by renewables and battery storage. This "crossover" phenomenon, where retirements outpace additions, creates a reliability gap that is widening just as the thermal stress on the system is increasing.1 The result is a grid that is leaner, less resilient, and operating with vastly reduced margins for error.

2. The PJM Interconnection: Anatomy of National Grid Risks

The PJM Interconnection is often described as the "air traffic controller" of the electric grid for thirteen states and the District of Columbia. Its role is to ensure reliability and manage the wholesale electricity market. Historically, PJM has been characterized by a robust reserve margin—a buffer of excess generating capacity available to be called upon during extreme weather events or unexpected plant failures. However, the data from 2024 and 2025 reveals a system where that buffer is eroding at an alarming rate.

2.1 The Statistical Reality of Load Growth

The narrative of load growth in PJM has shifted from one of stagnation to one of aggressive expansion. For much of the 2010s, electricity demand was relatively flat, decoupled from economic growth by significant gains in energy efficiency. LED lighting, more efficient HVAC systems, and better building insulation meant that the economy could grow without a corresponding spike in power consumption. That era is effectively over.

The 2025 Long-Term Load Forecast released by PJM presents a trajectory that is both steep and relentless. The forecast projects that summer peak load will grow by an average of 3.6% per year over the next ten years, a significant upward revision from previous estimates of 3.1%.4 This growth is not evenly distributed across the residential, commercial, and industrial sectors. It is lumpy and concentrated, driven almost entirely by the "large load" category, which PJM uses to classify data centers and other energy-intensive facilities like battery manufacturing plants.

PJM’s evaluation of large load adjustment requests confirmed that data center growth is the primary driver of this trend. The forecast anticipates that the system's summer peak will surge past 183,000 MW by 2030.5 This projection incorporates specific "shovel-ready" projects but also attempts to account for the speculative nature of data center development, where developers often secure power rights for facilities that are years away from completion. The challenge for PJM planners is distinguishing between "phantom" load—requests submitted to hold a place in line—and real load that will materialize and demand electrons on a hot July afternoon.

2.2 The Geographic "Load Pocket"

The crisis is geographically lopsided. While the PJM footprint extends as far west as Chicago, the acute stress is concentrated in the eastern portion of the Dominion Energy zone and the transmission corridors of Northern Virginia. This area, encompassing Loudoun, Prince William, and Fairfax counties, is known as "Data Center Alley." It is estimated that 70% of the world's internet traffic flows through the fibers embedded in this soil.

The physical concentration of these facilities creates what grid operators call a "load pocket." In a load pocket, the demand for electricity within a specific geographic boundary exceeds the local capacity to generate power. To keep the lights on and the servers running, massive amounts of electricity must be imported from outside the region via high-voltage transmission lines. However, transmission lines are not infinite pipes; they have physical limits on how much power they can carry. When these lines reach their capacity, the region becomes "congested."

Congestion prevents cheap power generated by wind farms in the Midwest or nuclear plants in Pennsylvania from reaching the data centers in Northern Virginia. This forces the grid operator to dispatch expensive, often less efficient local generation to meet demand, driving up prices and stressing local infrastructure. PJM has identified immediate reliability violations in the Dulles Airport area due to this localized load density, necessitating billions of dollars in transmission upgrades that will take years to construct.6

2.3 The Capacity Market as a Warning Signal

The clearest economic indicator of this looming reliability crisis appeared in the results of the PJM Capacity Auction for the 2025/2026 delivery year. The capacity market is designed to secure future power supply by paying generators a fee to be available three years in advance. In a balanced market, these prices are moderate.

However, the recent auction results were a shock to the system. Capacity prices hit the administrative price cap of approximately $333 per megawatt-day across much of the footprint, a tenfold increase from previous auctions where prices hovered around $30-$50.7 In the absence of price caps, models suggest the clearing price would have soared to nearly $530 per megawatt-day. This price explosion serves as a frantic market signal: reserves are scarce, and the market is willing to pay a premium for any resource that can guarantee availability.

The auction procured 145,777 MW of capacity, which fell short of the installed reserve margin target by roughly 6,625 MW.7 A shortfall of this magnitude implies that PJM is entering the operating year with a thinner reliability cushion than its own safety standards require. While this does not guarantee blackouts, it significantly increases the probability that emergency procedures will be triggered during extreme weather events.

3. The Physics of Grid Failure: Why "Limits" Matter

To understand why data centers threaten to cause blackouts, one must move beyond economics and delve into the physics of the grid. The electric grid is not merely a marketplace; it is a physical system governed by thermodynamics and electromagnetism. The "limits" being tested are not arbitrary regulatory caps but hard physical boundaries where materials fail and systems collapse.

3.1 Thermal Limits and the Sagging Line

The most immediate physical constraint on the East Coast grid is the thermal limit of transmission lines. As electrical current flows through a conductor (the aluminum and steel cables strung between towers), it encounters resistance. This resistance generates heat, a phenomenon described by Joule’s Law. The heat generated is proportional to the square of the current; doubling the current quadruples the heat.

Transmission lines are designed to operate within a specific temperature range. As they heat up, the metal expands. Since the lines are suspended between fixed points (transmission towers), this expansion manifests as "sag." The line physically droops closer to the ground. If a line sags too low, it violates safety clearances and risks contacting trees, buildings, or even the ground itself. Such a contact causes a massive short circuit, or "fault," which triggers protective relays to instantly de-energize the line to prevent fire or electrocution.8

The data center boom exacerbates this in two ways. First, the sheer volume of current required to power gigawatts of server racks pushes lines closer to their thermal limits 24/7. Second, the peak demand for data centers often coincides with the hottest summer days. On a day when the ambient temperature is 95°F or 100°F, the air provides very little cooling effect for the transmission lines. This "derates" the line—meaning its safe carrying capacity is lower exactly when demand is highest.

PJM’s assessment of the Northern Virginia area has found that under "N-1" conditions—a planning scenario where one major transmission line fails—the remaining lines would immediately overload and sag beyond their thermal limits due to the concentrated data center load.6 To prevent physical damage to the conductors or a public safety incident, operators would have no choice but to shed load—cutting power to customers—to reduce the current flow.

3.2 Reactive Power and Voltage Collapse

While thermal limits are intuitive (wires get hot), a more subtle but equally dangerous threat is voltage instability. The grid delivers two types of power: "active power" (measured in megawatts, MW), which does the actual work of running servers and lights, and "reactive power" (measured in megavars, MVAR), which creates the magnetic fields necessary for motors and transformers to operate.

Data centers are massive consumers of reactive power due to the induction motors in their cooling systems and the characteristics of their power supply units. Reactive power is heavy; it does not travel well over long distances. It must be generated locally. If the local grid in Northern Virginia runs short of reactive power, voltage levels begin to sag.

This creates a dangerous feedback loop known as voltage collapse. As voltage drops, constant-power loads (like data center servers) draw more current to compensate. Drawing more current causes a further voltage drop across the transmission lines. If this cycle continues unchecked, the voltage can crash to zero in seconds, causing a wide-area blackout. Unlike a thermal overload, which happens gradually, voltage collapse can be sudden and catastrophic.9 PJM’s reliance on importing power from distant generation makes the grid in Northern Virginia particularly susceptible to this phenomenon, as reactive power losses increase with transmission distance.

3.3 The Erosion of Inertia

The third physical pillar of reliability is inertia. The North American grid operates at a synchronized frequency of 60 Hertz (Hz). This frequency is the heartbeat of the system. It is maintained by the stored kinetic energy in the massive, spinning rotors of steam and gas turbines. These rotating masses act as shock absorbers for the grid. If a large power plant suddenly trips offline, the inertia of the remaining generators instantly dampens the drop in frequency, buying time for automatic governors to increase power output.10

The energy transition is fundamentally altering this dynamic. As PJM retires heavy, rotating coal and gas plants and replaces them with solar panels and wind turbines, the system loses physical inertia. Solar panels are "Inverter-Based Resources" (IBRs); they have no moving parts and are connected to the grid via digital electronics. Historically, they provide zero inertia.

Data centers add massive load to the system without contributing any inertia. This means the "grid of the future" is becoming lighter and faster. In a low-inertia system, a sudden disturbance—such as a transmission line fault or a large generator trip—can cause the frequency to plummet much faster than in the past. If the frequency drops below a critical threshold (typically around 59.5 Hz), automatic under-frequency load shedding (UFLS) relays trigger, instantly cutting power to neighborhoods to save the machine.12

The "Data Center Alley" creates a unique vulnerability here. A sudden loss of load (e.g., a data center tripping offline) or a sudden spike in load (a massive AI training run ramping up) creates frequency perturbations that a low-inertia grid struggles to absorb. While technologies like synchronous condensers (free-spinning motors) can provide synthetic inertia, their deployment is lagging behind the pace of coal retirements.14

4. The Data Center Load Profile: A New Species of Consumer

The entities driving this crisis are not traditional industrial consumers. The load profile of a modern hyperscale data center, particularly one dedicated to AI, is fundamentally different from the factories and office buildings the grid was designed to serve.

4.1 The Thermodynamics of AI Training

The shift from general-purpose cloud computing to AI training has resulted in a dramatic densification of power consumption. A decade ago, a standard server rack might draw 5 to 10 kilowatts (kW). Today, racks equipped with specialized AI accelerators—such as NVIDIA’s H100 or the upcoming Blackwell architecture—can draw upwards of 100 kW per rack.15

This densification changes the thermal properties of the load. These chips run hot and require aggressive cooling. While traditional data centers used air cooling (CRAC units), AI clusters increasingly require direct-to-chip liquid cooling. This creates a "base load" that is incredibly flat and high. Unlike a factory that shuts down at night, an AI training run may continue at peak intensity for weeks or months without pause. This unrelenting demand gives grid operators no "breathing room" to perform maintenance on transmission lines or recharge grid-scale batteries.16

4.2 Training vs. Inference: The Congestion Driver

It is critical to distinguish between the two modes of AI workloads: training and inference.

  • Training: This is the process of building the model (e.g., teaching GPT-4). It requires massive computational clusters and sustained power. Training is less latency-sensitive; technically, it could be done in rural North Dakota or anywhere with a fat power pipe.

  • Inference: This is the use of the model (e.g., ChatGPT answering a question). Inference is highly latency-sensitive. To provide a seamless user experience, the compute must be located close to the end-users and the major fiber optic backbones.

The crisis in Northern Virginia is driven by the fact that it is the optimal location for both. The fiber infrastructure (dating back to the MAE-East exchange) makes it the inference capital of the world. However, the agglomeration benefits—talent, supply chains, existing permits—have also concentrated massive training clusters there. This creates a scenario where the grid must support the "bursty" nature of training workloads alongside the critical uptime requirements of inference services.16

4.3 The Backup Paradox: Diesel vs. Grid

To ensure "five nines" (99.999%) of reliability, data centers are fortified with massive arrays of backup diesel generators. In Loudoun County alone, the aggregate capacity of these backup generators rivals the output of multiple nuclear power plants.

This creates a paradox. When the grid is stressed to the breaking point, PJM may order a "voltage reduction" or request conservation. If the situation deteriorates to a blackout, the data centers effectively secede from the grid, switching to their diesel islands. While this protects the servers, it shifts the burden of the blackout entirely onto residential and commercial customers. Furthermore, the simultaneous firing of thousands of diesel generators creates a localized air quality crisis, releasing tons of nitrogen oxides (NOx) and particulate matter. This has led to intense regulatory friction with the Virginia Department of Environmental Quality (DEQ) regarding variance permits for generator operations during grid emergencies.18

5. The Supply Crisis: The "Crossover" Trap

If demand is the accelerator, supply constraints are the brakes that have failed. The East Coast grid is caught in a "crossover" trap where dispatchable fossil fuel generation is retiring faster than renewable generation can be connected.

5.1 The Retirement Wave

Environmental regulations, state-level decarbonization mandates like the Virginia Clean Economy Act (VCEA), and the economics of aging machinery are driving the retirement of coal-fired power plants. Key facilities that once provided baseload power and inertia are going dark. For example, the Brandon Shores and Wagner coal plants in Maryland—critical for supporting voltage in the Baltimore-Washington corridor—are slated for deactivation.

PJM has warned repeatedly that these retirements are premature relative to the pace of replacement. The 2025 PJM reliability analysis indicates a potential loss of 40 GW of generation capacity by 2030.1 These "thermal" resources are firm; they can run when the wind isn't blowing and the sun isn't shining. Their departure leaves a hole in the supply stack that intermittent renewables cannot yet fully fill, specifically during the "net peak" hours (winter mornings and summer evenings).20

5.2 The Interconnection Queue Logjam

The theoretical replacement for coal is a massive wave of wind, solar, and battery storage projects. However, these projects are stuck in the PJM interconnection queue—the administrative waiting line for permission to connect to the grid.

The queue is notoriously backlogged. In 2022, facing a deluge of speculative applications, PJM paused the review of new requests to overhaul its process. The reform moved from a "first-come, first-served" model to a "first-ready, first-served" cluster study approach. While this is intended to weed out speculative projects, the transition has created a temporary freeze. Projects entering the queue today might not connect until 2029 or 2030.

Furthermore, many renewable projects fall out of the queue due to upgrade costs. Under PJM rules, if a new solar farm triggers the need for a transmission upgrade (like replacing a transformer), the developer must pay for it. These "network upgrade" costs can run into the tens of millions of dollars, rendering projects financially unviable. The result is a high attrition rate, where only a fraction of proposed renewable gigawatts actually materialize as steel in the ground.21

6. Regulatory Warfare: The Battle for the Grid

The tension between the digital economy's needs and the grid's limitations has sparked a multi-front regulatory war involving hyperscalers, utilities, states, and the federal government.

6.1 The Talen Energy-Amazon Co-Location Case

The most significant battleground in 2024 and 2025 has been the concept of "co-location." Desperate for reliable, carbon-free power, Amazon Web Services (AWS) purchased a data center campus directly adjacent to the Susquehanna nuclear power plant in Pennsylvania, owned by Talen Energy. The plan was to connect the data center directly to the nuclear plant "behind the meter," allowing Amazon to draw up to 960 MW of power without using the PJM transmission grid.23

This proposal ignited a firestorm. Competitor utilities like AEP and Exelon challenged the Interconnection Service Agreement (ISA) at the Federal Energy Regulatory Commission (FERC). Their argument was based on the "free rider" problem: if Amazon diverts 960 MW of nuclear power that was previously serving the grid, other ratepayers must pay to replace that lost capacity and maintain the transmission system that provides Amazon with backup power.

In a landmark decision in late 2024, FERC rejected the amended ISA. The rejection signaled that regulators are wary of allowing hyperscalers to "cannibalize" existing baseload generation at the expense of the broader public. The decision forced data centers back into the general queue, exacerbating the congestion issues but protecting the principle of shared grid costs. The dissent by FERC Chairman Willie Phillips, who argued the rejection threatened national security and AI leadership, highlights the deep fissures within the regulatory body regarding how to prioritize AI versus traditional reliability.23

6.2 The "Emergency Auction" Proposal

In response to the slow pace of market signals, the Trump administration, joined by a coalition of governors from PJM states (Maryland, Virginia, Pennsylvania), proposed a radical intervention in January 2026: an "emergency" capacity auction.

This proposal calls for PJM to hold a special auction to secure long-term (15-year) contracts for new generation, specifically targeting data centers. The idea is to bypass the traditional three-year forward market and provide the long-term certainty needed to finance new natural gas or Small Modular Reactor (SMR) plants. The proposal suggests that data centers would be required to underwrite these contracts, paying for the new capacity whether they use it or not. This marks a shift from a deregulated market philosophy to a more directed, state-interventionist approach to ensure resource adequacy.25

7. The Anatomy of a Blackout: What Summer 2026 Could Look Like

When PJM warns of "rolling blackouts," they are referring to a precise, scripted sequence of emergency procedures. It is important to understand that a rolling blackout is not an accident; it is a deliberate operational decision made to save the grid from a total, uncontrolled collapse.

7.1 The Escalation Ladder

The path to a blackout begins days before the lights go out.

  • Weather Alerts: PJM issues "Hot Weather Alerts," signaling generators to defer maintenance and prepare for maximum output.27

  • Emergency Energy Alerts (EEA): As reserves tighten, PJM moves through NERC-defined alert levels.

  • EEA 1: All available resources are committed.

  • EEA 2: Load management procedures are activated. PJM calls on "Demand Response" resources—factories and businesses paid to shut down voluntarily.28

  • EEA 3: Firm load interruption is imminent. The grid is operating with zero reserves.

7.2 The Manual Load Dump

If the frequency continues to drop or thermal violations on transmission lines become critical, PJM System Operations will issue a "Manual Load Dump" order. This is the technical term for rolling blackouts.

PJM communicates with local transmission owners (like Dominion or Pepco), ordering them to shed a specific megawatt amount (e.g., "Shed 500 MW in Zone B"). The utilities then open circuit breakers at substations, cutting power to specific distribution feeders. These outages are typically rotated every 60 to 90 minutes to share the burden among different neighborhoods. Critical infrastructure (hospitals, police stations) is usually exempt, but residential and commercial areas are dark.29

7.3 The "Double Jeopardy" of Data Centers

A critical point of friction is that during a manual load dump, data centers often remain operational, switching to their diesel backups. This creates a stark visual disparity: residents in Loudoun County may sit in sweltering homes without air conditioning, while adjacent data center campuses remain lit and humming. This dynamic has fueled intense local resentment and political pressure to force data centers to participate more actively in demand response, rather than just relying on diesel.31

8. The Human and Local Impact

The abstract discussions of gigawatts and voltage collapse translate into tangible impacts for the communities hosting this infrastructure.

8.1 The Noise and Land Use Battle

In communities like Great Oak in Prince William County, the data center boom is audible. Residents have filed numerous complaints regarding the low-frequency "hum" of cooling fans and the roar of generator testing. Unlike traffic noise, which fluctuates, data center noise is constant and mechanical. This has led to lawsuits and demands for stricter noise ordinances, which in turn restrict where and how data centers can be built.33

8.2 The "Digital Gateway" Controversy

The proposal to build the "Prince William Digital Gateway," a massive data center corridor near the Manassas National Battlefield, sparked one of the fiercest land-use battles in Virginia's history. Residents and preservationists argued that the development would destroy the rural character of the area and desecrate hallowed ground. The conflict illustrates the growing "NIMBY" (Not In My Backyard) resistance that is slowing down the very infrastructure needed to support the AI boom. These local delays feed back into the macro reliability crisis by delaying the deployment of new load-serving capability.35

9. Conclusion: A Wartime Mobilization for the Grid

The PJM Interconnection is entering a period of extreme vulnerability. The margin for error that once existed has been consumed by the voracious appetite of the digital economy and the friction of the energy transition. The risk of rolling blackouts on the East Coast is no longer a tail risk; it is a central scenario in grid planning exercises.

Addressing this crisis requires a mobilization of resources akin to a wartime effort. It necessitates:

  1. Accelerated Transmission: Cutting the permitting time for new high-voltage lines from years to months.

  2. Strategic Reserves: delaying the retirement of critical fossil fuel plants until replacement capacity is fully operational.

  3. Grid-Enhancing Technologies: Deploying sensors and software to squeeze more capacity out of existing lines (Dynamic Line Ratings).

  4. Demand Flexibility: Forcing or incentivizing hyperscalers to throttle AI training workloads during peak grid stress, turning the problem (load) into part of the solution.

Unless these measures are implemented with urgency, the "East Coast" faces a future where the seamless reliability of electricity—the foundation of modern life—becomes a memory, replaced by the intermittent uncertainty of a grid pushed beyond its limits.

Table 1: The PJM Load Forecast Shift (Summer Peak)


Metric

Previous Trajectory (2010s)

2025 Long-Term Forecast (2025-2039)

Primary Driver

Annual Growth Rate

< 1.0% (Flat)

3.6% - 5.5%

Data Center Densification

Summer Peak (MW)

~150,000 MW

220,000 MW (by 2039)

AI Training Clusters

Record Peak

165,563 MW (2006)

Projecting 183,000 MW by 2030

Large Load Additions

Data Center Load

Stable / Efficient

+30 GW (2025-2030)

Northern Virginia "Alley"

Source

Historical Data

1

PJM Planning Reports

Table 2: PJM Capacity Market Price Shock (2025/2026 Auction)


Zone / Area

Previous Clearing Price ($/MW-day)

2025/2026 Clearing Price ($/MW-day)

Percent Increase

Implication

RTO Average

~$30 - $50

$269.92

~800%

Signal of extreme scarcity across the region.

BGE (Baltimore)

~$70

$466.35

~560%

Critical shortage in Baltimore/DC area.

Dominion (VA)

~$70

$444.26

~530%

Data Center Alley creates massive local premium.

ComEd (Chicago)

~$30

$269.92

~800%

Market coupling draws prices up everywhere.

Source

7

7

--

Consumers face 20-30% bill hikes.

Table 3: The Physics of "The Limit"


Constraint

Mechanism of Failure

Data Center Impact

Consequence

Thermal Limit

Current heats wire -> Wire expands/sags -> Ground contact -> Short circuit.

High continuous load keeps wires hot 24/7; limits ability to cool down at night.

Load Shedding to prevent physical line damage.

Voltage Stability

Lack of reactive power -> Voltage drops -> Motors draw more current -> Voltage drops further -> Collapse.

Massive induction motors (cooling) and servers consume vast reactive power.

Wide-area Blackout (Cascading failure).

Inertia

Loss of heavy spinning mass (Coal/Gas) -> Frequency drops faster during faults.

Adding massive load without adding inertia (Spinning Mass) makes grid brittle.

Under-Frequency Load Shedding (Automatic).

Source

8

9

11

Table 4: Escalation to Blackout (PJM Emergency Procedures)


Step

Procedure

Trigger Condition

Action Taken

Impact

1

Hot Weather Alert

Forecasted Temp > 90°F / High Load

Generators defer maintenance; transmission checked.

None to public.

2

EEA Level 1

Reserves < Target

All generation committed; imports maximized.

None to public.

3

EEA Level 2

Reserves Critical

Demand Response triggered (Factories paid to stop).

Industrial shutdowns.

4

Voltage Reduction

Voltage support failing

Distribution voltage lowered by 2-5% ("Brownout").

Lights dim slightly.

5

Manual Load Dump

Imminent Failure

Rolling Blackouts ordered.

Loss of power to homes/businesses.

Source

27

28

29

30

Works cited

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