Extreme Climate Events and Energy Market Vulnerability: A Systematic Global Review

Abstract

This research study deals with the analysis of climate catastrophes that have occurred worldwide and in what measure they have affected communities, in an economic and social point of view, and energy markets in general over time. A chronological sweep across Europe has been carried out in order to evaluate the different consequences that phenomena such as hurricanes, winter storms, and floods have had, especially on the energy prices. Moreover, the effects of the variability of renewable generation during climate disasters not only in Europe but also in North America, Australia, and Latin America have been discussed. Furthermore, best practices and novel strategies for climate adaptations have been identified in different countries, and the results show how energy planning integrated within a systematic diversification of energy sources and investment in infrastructure and advanced technologies such as distributed generation and digital twins can be crucial to enhance the reliability of energy systems.

1. Introduction

Extreme weather events that occur unusually in various parts of the world end up affecting the stability of energy markets, in addition to having socio-cultural implications in the regions where they occur. Among the main events are hurricanes, floods, droughts, winter storms, and heat waves that are influenced by global climate change and cause physical damage to energy infrastructure, which in turn triggers supply disruptions, sudden increases in demand during climate crises, and volatility in electricity, gas, and water prices. Extreme weather events have demonstrated the ability to affect electrical systems and related infrastructure, causing major interruptions in the generation and production of electrical energy [1].

From here, socio-cultural problems arise since people during these types of catastrophes, particularly in developing countries, face challenges in accessing essential energy services. Extreme weather events on a global scale have led to damage to infrastructure with significant losses and economic impacts. There are existing records of severe damage to energy infrastructure in North America and Central Europe, caused by winter storms, droughts, and floods, and consequently, causing massive interruptions in the electricity supply and producing large economic losses and serious socio-cultural problems [2].

As a matter of fact, multiple researchers have carried out different works in order to find relationships between a specific climatic event and the different implications they have on the population from the economic, social, and structural point of view. As mentioned above, extreme weather events affect energy demand, and the resilience of supply systems can lead to around 16% of losses in the reliability of the electrical system [3]. Such events not only generate supply disruptions and electrical energy price fluctuations, but also imply an increase in the financial risk of energy markets, particularly in the oil and natural gas pricing market [4] Climate catastrophes such as heat waves and droughts, among others, increase the costs of renewable energy production (for example, in the case of hydroelectric plants), immediately affecting the electricity sales prices [5]. Likewise, extreme weather events can lead to a decrease in energy demand in some sectors, although in others the growth of demand is brutal. This is the case of cooling systems, for example in heat waves [6], whose volatility has negative consequences for both consumers and consortia, leading to an increase in operating costs in order to guarantee the supply of electricity in adverse weather periods [7].

Regarding the oil and gas markets, this type of industry is prone to extreme events, such as hurricanes, which directly affect crude oil and gas production and its transportation platforms. As a result of the infrastructure deterioration and consequent interruption in supply, an increase in the price of crude oil in the markets will be detected. Price increases have a knock-on effect on other economic sectors, which adds more money losses than those directly produced by the hurricane [8]. For instance, in the case of Hurricane Katrina, the price of crude oil increased by approximately 20% within a week after the hurricane made landfall. Similarly, extreme events, such as forest fires and snowstorms, have also affected the electricity transmission infrastructure, increasing repair and maintenance costs with negative effects on consumer rates [9].

An analysis carried out by Carty [10] points out that instability in food prices is linked to the effects of adverse climatic phenomena, since energy costs will have repercussions throughout the supply chain, especially in the agricultural sectors. These widespread effects suggest the importance of improving energy planning, as well as climate risk management as a way of mitigating the economic effects of events.

Speaking specifically in Latin America, countries such as Colombia have developed a strong dependence on energy produced by hydroelectric plants. This dependence represents a problem for the country because phenomena such as the so-called “El Niño and La Niña” responsible for extreme droughts and floods caused a strong destabilization in energy prices, in addition to material and social damage of the areas where they occurred. This phenomenon does not just affect Colombia, but it is common to all exceptional weather phenomena, such as hurricanes, floods or heat waves, and other meteorological events able to damage transmission and distribution networks, resulting in interruptions in the supply service and possible disruption of the electrical infrastructure [11].

Despite worldwide policy makers’ efforts, energy markets still remain vulnerable to these catastrophic events.

This review aims to analyze how extreme weather events affect the energy markets. The global patterns of climate catastrophe will be identified in order to propose mitigation strategies to possible damages caused. Furthermore, a chronological review will be carried out by analyzing extreme weather events and countries and the different effects that climatic events had on structures, prices, and supply and demand. The novelty of this research resides in the potential impact it can have on the formulation of energy policies in different countries. The classification of the main climatic events that have occurred around the world and the analysis of their effects will provide valuable information about their influence on energy markets reliability by helping governments and institutions to build up proper mitigation strategies and implement prediction tools. Finally, this research study aims to anticipate the effects of climatic phenomena on the infrastructure of the energy sector, reduce vulnerabilities, and develop adaptive solutions that allow guaranteeing the energy supply and mitigating the socioeconomic effects on exposed communities, as may be the case in regions such as Latin America, where climatic oscillations are an important challenge to overcome.

2. Materials and Methods

A systematic literature review was conducted, consulting major databases such as Scopus and Web of Science, as well as manual searches in other scientific repositories. The references included articles written in English between 2012 and 2024. The search strategy included search terms related to “energy markets and prices” as well as “extreme weather events”, using Boolean operators (Mendeley Reference Manager v2.x, Mendeley, London, UK; and Microsoft Excel (Microsoft 365 version, Microsoft, Redmond, DC, USA) in the title field. Inclusion criteria included original research articles from high-impact-indexed journals addressing the economic impact of extreme weather events on global energy markets in the fields of engineering, environmental sciences, energy, earth sciences, and economics. Mendeley Reference Manager (free version, web and desktop, v2.x) was used to organize, manage, and cite the references, with integration into Microsoft Word for document preparation. The screening and relevance scoring were recorded and analyzed using Microsoft Excel (Microsoft 365 version) Articles were rated on a 5-point Likert-type relevance scale. Articles scoring 4 or 5 were included. Articles with a score of 3 were individually assessed, and their inclusion was decided upon. Two independent authors applied the inclusion and exclusion criteria. Inter-author reliability was ensured through discussion and consensus in cases of discrepancy. After eliminating duplicate studies, 68 articles were finally included in the review. Appendix A includes the exact search strategies, search equations, and the PRISMA flowchart, which was manually created using Microsoft Word (Microsoft 365 version).

3. Classification of the Climatic Environments with Impact on Energy Markets

By conducting an in-depth analysis of the literature, natural events that cause a significant impact on energy systems in different countries around the world were identified and categorized. This choice was made to determine which events were most significant, based on their economic impact, operability, and the consequences they may cause in the energy market. For such purposes, those extreme weather events that have tangible and measurable consequences on the generation, distribution, and consumption of energy around the different countries were considered:

• Hurricanes and tropical storms: These specific types of weather events and disasters pose a significant threat to the electrical infrastructure, as they can cause damage to various system components, as well as to the infrastructure of transmission lines, substations, and other components of the electrical system. The long power outages resulting from storms result in high restoration costs and significant economic losses.
• Magnetic storms: These create geomagnetically induced currents (GIC) that saturate transformers and cause overloads in transmission systems. Such overloads increase operating costs and generate catastrophic failures of the infrastructure. An explicit example is the effect of magnetic storms in Alberta (Canada), where transmission lines have very high induced voltages, which endanger the robustness of energy systems.
• Droughts: These directly affect hydroelectric systems as they reduce generation capacity, which causes an increase in dependence on thermal plants, thus an increase in operating costs and CO₂ emissions. In Colombia, the phenomenon known as “El Niño” can cause reductions in hydroelectric capacity of up to 30%, thus highlighting the vulnerability of the sector to extreme climatic variations.
• Floods: Extreme floods have a serious impact on substations and power transmission systems, causing long power outages and costly repair work, as these floods are usually caused by rivers located near cities and towns.
• Heat waves and extreme cold: Extreme temperatures alter the demand for electricity, with a significant increase in consumption for cooling, specifically in heat waves, in addition to the increase in the use of heating in periods of extreme cold. The conditions mentioned also affect the efficiency of generators and create greater volatility in the energy markets of the region. For example, in the western United States, these heat waves have increased the operating costs of energy companies as a result of the increase in the additional capacity needed to meet demand [12].
• Dust storms: Dust storms contaminate electrical insulators, consequently causing more failures in distribution systems, in addition to making maintenance more expensive. For example, in Iran, dust storms have caused frequent power outages and increased operating costs for local energy companies.

Taking this classification into account, the following section presents the results obtained in the literature review, grouping chronologically the most relevant research in different geographical areas. Throughout the review, a general description of each article is made, as well as summarizing the general objectives, methodology, place of application, and results obtained.

4. Impacts and Adaptation Strategies to Natural Events: A Review of Global Studies

This section presents the different studies classified by regions in the world, organized chronologically, showing the different characteristics of each climatic event, in addition to the effects that these had on the energy structures.

4.1. Global Studies

In this section, phenomena such as floods, hurricanes, droughts, and heat waves have been analyzed, revealing how these events have different repercussions on the planet.

This analysis begins with the study presented in [13], which provides a solid foundation for understanding the interaction between fossil fuel markets and climate change mitigation policies and how these dynamics can be further leveraged to address concerns raised by the analysis of extreme weather events. In this study, REMIND is utilized to assess policy mitigation impacts, energy market scenarios, their effects on global emissions, economic outcomes, and fossil fuel rents associated with stabilizing greenhouse gas (GHG) concentrations, using a version of the REMIND model developed and maintained by the Potsdam Institute for Climate Impact Research (PIK), specifically adapted for global fossil fuel market analysis. One of the key findings is that, under a business-as-usual scenario, fossil fuel consumption could lead to atmospheric GHG concentrations well above the critical threshold of 550 ppm. Instead, mechanisms such as carbon pricing can rapidly decrease carbon consumption and emissions and reduce mitigation threats and shocks to resiliency, while stabilizing the global energy system from shocks resulting from an extreme weather event. The study also discusses how climate policies may impact fossil fuel rents, projected to fall by $9 to $12 trillion, although this can be offset by carbon pricing revenues of $21 to $32 trillion. It identifies the operational and economic potential of strategic pathways and carbon pricing to mitigate the global economy from dependence upon fossil fuels and support price stability. In mitigation scenarios, coal use could be reduced between 55 and 85% as a function of stabilization targets, and the carbon pricing mechanisms proposed could compensate global economic losses, although regional disparities may remain.

At a global level, the types of interactions between carbon, fossil energy, and clean energy markets have been analyzed [14]; the authors investigated types of interactions between carbon, fossil energy and clean energy markets, finding that the main effects depend on time. For example, in the short term, the carbon market absorbs the indirect effects of the risk from the oil and clean energy markets, while in the long term, the risk is transmitted to the oil and gas side. The authors highlight that the effects of these interactions are not always the same, as they respond differently to certain conditions. Regional differences remain large and are more pronounced in economies dependent on oil and gas. Considering what is shown in the articles, it could be concluded that this type of relationship is not a purely static phenomenon, but rather depends on market conditions and the time horizon. Added to this, it can be observed that there are implications for how risks are managed in the energy system, specifically in areas that are dependent on this type of fuel.

Building on this line of analysis, the possible dynamic relationships between the climate change index, green financial assets, renewable energy markets, and geopolitical risks have also been explored [15] To achieve this, different methodologies such as the quantile vector autoregression (QVAR) and wavelet coherence (WC) have been used. Some of the conclusions reached by the authors are that geopolitical risk (GPR) acts as a net transmitter of shocks to the climate change index during the Russian invasion of Ukraine; that special event further influenced global financial and energy markets. Finally, the researchers suggest that policymakers should prioritize investments in green energy and financial assets to reduce greenhouse gas emissions and promote stability in financial markets. Although it is not an in-depth study of climate-related disasters, this research shows how geopolitical shocks can shape financial and environmental market behavior.

Within the broader context of space-related disturbances in energy systems, attention has also been given to the impact of magnetic storms on electric power transmission [16] as these phenomena can cause operational stress and potential infrastructure failures. The authors mention that magnetic storms generate geomagnetically induced currents (GIC) in high voltage systems, which leads to the saturation of the transformer’s magnetic circuits, and with this to large overloads; in addition, thermal stress is also generated that can damage the components. The authors propose a prediction system to mitigate these types of effects when there are magnetic storms; in addition, they offer important information for people in charge of designing transformers, in order for them to incorporate protection measures in the manufacture or maintenance of these machines.

The relationship between natural disasters, climate change, and the dynamics of clean and fossil energy markets has also been explored in the context of climate uncertainty [17]. The researchers analyzed whether these markets function as complements or substitutes under a climate-related perspective when there is climate uncertainty. To do this, the study was conducted from 2015 up to 2022 using data from global energy markets. One of the main conclusions that can be drawn are that clean and fossil energies tend to behave as substitutes in the short term; however, in the long term they show a higher degree of complementarity, synchronizing their market dynamics. Moreover, the authors also agree that every extreme climatic event generates changes in financial markets regardless of the phenomenon studied. In the research, the BEKK–GARCH model was used to analyze and determine the volatility spillover effects across energy markets. The findings suggest that extreme weather events increase volatility in both clean and fossil energy markets, which in turn may lead to greater uncertainty and stronger correlations between them.

From the literature review, relevant information was extracted encompassing various aspects related to events impacting electrical systems. This information includes details about the specific event, the date and location where it occurred, the supply interruptions and grid instabilities that arose, the system responses implemented to mitigate the effects, the proposed policies to prevent future incidents, and the references supporting this observation. The summary of all the studies analyzed can be found in

Table 1. Worldwide extreme weather events occurring from 2012 up to 2024 and classified in terms of their impact on the energy systems and mitigation strategies. Source: own elaboration from [13,14,15,16,17].

Event/Phenomenon	Date	Supply Interruption and Grid Instability	System Response	Proposed Strategies	Reference
Hurricanes, floods, and extreme weather phenomena	2013	Energy supply interruptions and grid instability due to infrastructure damage.	Change in consumption patterns, increased demand, price increase, change in energy mix.	Carbon pricing, promotion of renewable energy, stabilizing the energy market.	[13]
Energy market risks due to climate change (clean and fossil)	2016	Unstable supply due to climate-induced disruptions and fluctuating availability.	Change in energy mix (higher demand for renewables), price increase.	Carbon pricing, promote renewable energy, discourage coal use.	[14]
Geopolitical risks and climate change (Russian invasion of Ukraine)	2012–2022	Interruptions from war, instability in the grid due to sanctions and blockages.	Price increases and search for alternative energy sources (renewables and natural gas).	Investment in renewable energy, energy diversification, energy supply security.	[15]
Magnetic storms and effects on electrical transmission	2015	Instability due to transformer saturation from geomagnetically induced currents (GIC), thermal stress on components.	Improvement in transmission infrastructure. Adaptive design to withstand magnetic storms.	Development of predictive systems, transformer protection.	[16]
Natural disasters and effects on clean and fossil energy markets	2015–2022	Interruptions due to natural disasters affecting generation and transmission of energy. Increased volatility in the grid.	Price increase, change in energy mix towards renewables.	Energy diversification, promotion of clean energy.	[17]

.

In Table 1, it can be observed that all climate events cause supply interruptions and grid instabilities. In addition, the system response includes changes in consumption patterns as well as price volatility. A general trend regarding the proposed strategies includes the following: diversification, carbon pricing, and the promotion of renewable energies. On the other hand, a matrix is presented in

Table 2. Global event impact matrix. Source: own elaboration from [13,14,15,16,17].

Event	Supply Interruption	Grid Instability	Price Volatility	Energy Mix Change	Policy Proposal
Hurricanes, floods, and extreme weather	X	X	X	X	X
Climate risks (clean/fossil markets)	X	X	X	X	X
Geopolitical risks	X	X	X	X	X
Magnetic storms	X	X			X
Natural disasters (2015–2022)	X	X	X	X	X

, where it is clearly observed that all analyzed climate and geopolitical events have an impact on supply interruption, grid instability, price volatility, changes in the composition of the energy mix, and the development of a policy proposal to mitigate these events—except for geomagnetic storms which apparently do not generate price volatility nor induce changes in energy production relative to the traditional energy mix.

4.2. Asia

Asia is a continent with different climatic conditions, as well as a high demand for energy consumption; therefore, it has different challenges when it comes to facing the possible consequences of natural disasters. All kinds of disasters have occurred on this continent, from monsoons and typhoons to extreme heat waves, which is a big problem considering the high population density of many countries on that continent, and of course, affecting the prices of the energy matrix of the countries in question, such as the price of gas, water, and electricity, among others. The following studies provide information on how these challenges are being addressed in various parts of Asia.

In the context of regional analyses, particular attention has been paid to the performance of electrical networks facing geomagnetic storms [18]. In this case, a computational model was developed to evaluate the performance of electrical networks during geomagnetic storms. The study was carried out in the Samara region of Russia, using MATLAB and Simulink to simulate the impact, specifically employing the SimPowerSystems library and custom-built blocks; however, the exact version of the software used was not specified by the authors. The results found in the research indicate that geomagnetic storms with different intensities and geoelectric field vectors can alter the stability of the electrical system, which translates into a sharp rise in magnetizing currents—reaching up to 645 A—and significant harmonic distortions, with total harmonic distortion levels up to 37.3%. Despite this, the study proposes different strategies for monitoring and designing the network, focusing on regions that are prone to these types of electromagnetic events.

In line with efforts to improve forecasting under extreme climatic conditions, the prediction of electricity generation with the greatest possible precision has been analyzed, specifically focusing on how wind speed and high temperature fluctuations can create significant uncertainty in energy supply. The latter is important to know since the energy production of many countries is already depending on renewable energies that are dependent on climatic variables, mainly wind energy. To do this, the authors designed a hybrid prediction model based on an adaptive neuro-fuzzy inference system (ANFIS), optimized by a particle swarm optimization algorithm and complemented with wavelet analysis, which uses historical data and real-time variables, allowing it to learn and adapt to rapidly changing conditions caused by extreme weather events. The model operates in two stages: the first predicts wind speed from meteorological inputs, while the second uses that output to forecast wind-generated electricity from SCADA data. Finally, the authors conclude that the model significantly improves electricity generation predictions, achieving a mean absolute percentage error (MAPE) of 5.78% and outperforming five benchmark models by up to 51% in accuracy [19].

Additionally, the economic implications of climate change on water resources and agriculture were analyzed by projecting conditions for the years 2040 and 2070, using the Zayandehroud River in Iran as the focus of study. The authors use climatic and biophysical models integrated into a hydroeconomic model to simulate the effects of the reduction in water discharge, in addition to the possible increase in its price due to low supply. The study finds that, under climate change and socioeconomic scenarios, agricultural water availability will decrease by up to 9%, and crop yields may decline by up to 32% in the worst-case scenario (without adaptation). However, the authors show that by implementing two no-cost adaptation strategies—optimal cropping patterns and deficit irrigation—economic losses can be reduced to just 2.8% by 2040, compared to the no-adaptation scenario [20]. The implications of dust storms on power distribution networks, particularly in the province of Khuzestan in southwestern Iran, have also been examined, as these extreme storms generally generate contamination of insulators, increasing the risk of insulation system failures and leading to power outages induced by discharges. In addition, dust storms alter the performance of other urban infrastructures, cause financial losses, and generate dissatisfaction in the population [21]. To try to mitigate these events, the researchers propose a cost-based optimization model, aimed at improving the resilience of power distribution networks against dust storms; this algorithm is based on two-stage stochastic mixed-integer programming (SMIP), where the first is responsible for equipping the repair components with insulator washers, supporting the distribution lines with silicone rubber insulators and implementing backup distributed generators. The second stage focuses on network reconfiguration, routing of repair crews, energy dispatch from distributed generation, and load shedding. The model was tested using data from 209 public buses considered as mobile backup generators, and results showed that the optimized strategy reduced expected total costs by up to 26.8% compared to non-optimized scenarios. For a better understanding,

Table 3. Analysis of the extreme weather events that occurred in Asia and classified in terms of their impact on the energy systems and mitigation strategies. Source: own elaboration from [18,19,20,21].

Event	Location/Ref.	Impact	Response/Strategy
Geomagnetic storms	Russia [18]	Grid instability, harmonic distortion.	Network redesign and real-time monitoring.
Wind power under extreme weather	Iran [19]	Forecasting uncertainty due to wind/temp.	ANFIS-PSO model with wavelets, MAPE: 5.78%.
Water stress and agriculture	Iran [20]	−9% water, −32% yield in worst case.	Optimal cropping, deficit irrigation, losses to 2.8%.
Dust storms on distribution systems	Iran [21]	Insulator failure, blackouts.	SMIP model with mobile backup and crew routing.

summarizes the findings from the literature review in Asia, presenting key aspects such as the event, date, country, and reference, as well as details on supply interruption and grid instability, system responses, and suggested strategies.

4.3. Europe

In Europe, there are different energy systems that are characterized by their diversity and efficiency; however, despite the fact that the continent has made great progress in the area of alternative energies, these are largely affected by climate fluctuations such as storms, floods, and cold and heat fluctuations, which affect temperature, wind, water, and, in turn, the generation of renewable energy. These problems often cause prices to increase, it is generally expected that, with less energy production, the price to the final consumer will increase. In this section of the review, different investigations that deal with these problems are studied.

The integration of ice storms into planning systems aimed at the location of wind farms and power lines has also been explored, with the objective of improving the resilience of electrical systems against possible interruptions and problems induced by extreme weather events [22]. The interesting thing about this work is that case studies are proposed for their respective analysis and in these they focus on a cost–benefit simulation by comparing planning alternatives that consider extreme climate risks with those that do not and then indicate as results that the integration of risk assessment in spatial planning significantly reduces the potential damages of extreme climate events. This can be achieved with two approaches: the first is to update engineering standards and the second, avoiding high-risk areas.

Research has also been conducted about the connection between climate change and volatility in electricity markets, specifically considering how the potential for climate change creating uncertainty in revenues from hydroelectric resources is linked to the consequences of disruption of water flows and electricity prices to the economics of the hydro sector. The study reveals that uncertainties evolve differently: while runoff shifts from natural variability to epistemic uncertainty, electricity prices follow the opposite path, becoming increasingly unpredictable in the long term. These findings have major implications for regions highly dependent on hydropower, as managing these risks is crucial to maintaining a reliable electricity supply under changing conditions [23].

Continuing this line of analysis, spatial planning has also been studied as a tool to prevent risks associated with extreme weather events in electric power infrastructure, with two case studies proposed in Slovenia, Europe, where the damage caused by ice storms to networks and heavy rains to hydroelectric plants is examined [24]. The authors propose a risk assessment and risk-informed spatial planning methodology to identify locations for the structure, where exposure to extreme weather conditions can be minimized. When the study evaluates ice storms, the impact on transmission lines is studied, while, for heavy rains, it evaluates erosion and sedimentation risks for hydroelectric plants. In the end, the authors conclude that the methodology has a good performance; however, they point out the importance of incorporating updated engineering standards and avoiding high-risk areas in planning decisions.

The impact of natural disasters on energy policy has also been emphasized, specifically using the example of the Gudrun storm in Sweden in 2005, one of the most destructive storms in the region, causing substantial electricity outages and economic losses estimated at up to 3 billion euros. Among the authors’ most important recommendations is to integrate climate risk analysis into the planning and management of electrical systems; in addition, the researchers point out the need to develop adaptive infrastructure to ensure sufficient continuity during extreme weather events [25].

The influence of different weather events on electricity prices has also been examined using the Italian market as a case study. The researchers developed a model that links energy demand and electricity prices with variables such as GDP, temperature, and other stochastic factors, as well as incorporating IPCC climate projections under different scenarios. The most important conclusions of the study show that electricity prices in Italy are very likely to fluctuate due to seasonal and climatic variations throughout the century. In particular, a decrease in energy demand can be observed during the winter season, while an increase is expected in summer and spring, which results in fluctuations in electricity prices [26].

Expanding on the previous findings, a study explores the delayed effects of geomagnetic storms on Czech power grids. The study focuses on the vulnerability of power lines and transformers to geomagnetically induced currents (GIC). For this, the analysis quantified the anomaly rates in the network infrastructure after periods of increased geomagnetic activity [27]. Once the measurements were made, the authors concluded that the anomaly rates on power lines increase significantly within one day after a geomagnetic storm, ranging between 5 and 10% in disturbances; however, something different happens in transformers; the effects are delayed, and the anomalies reach their peak between 2 and 3 days after the storm. With this, it was possible to say that prolonged storms increase the vulnerability of the systems, which later translates into high prices for consumers.

Further exploration proposes an automatic vector regression (VAR) model. What this algorithm aims to do is to find how climate-related factors, such as temperature, solar radiation, total precipitation, and relative humidity, affect electricity prices in the Portuguese electricity system [28]. They achieved this by including meteorological data to improve the ability to capture the interaction between weather conditions and electricity prices [29]. The researchers reached different conclusions from the study; for example, extreme temperatures increase the demand for energy for heating or cooling, while variations in solar radiation affect the generation of renewable energy from solar and wind sources, which translates into fluctuating final prices. Electricity prices showed a 70% autoregressive behavior, and temperature explained up to 98% of its short-term variance.

Regarding wholesale electricity markets, it was observed that atmospheric pressure is the most influential climatic factor in price variations; this may show that the Portuguese system is vulnerable to extreme changes in extreme weather conditions.

This dynamic is similar elsewhere in Italy, specifically in the Puglia region (southern Italy), where the authors study the effect of climate change (in its various manifestations) on wastewater treatment plants, focusing in particular on understanding how increases in temperature and changes in precipitation patterns influence the operational capacity and economic stability of wastewater treatment plants [30]. The researchers made different projections and analyses of the different consumption patterns of these plants. Some of the results of this research are that high temperatures can increase the energy costs of wastewater treatment, while variations in precipitation alter the consistency of the input, which affects the treatment process and generates greater problems in operations. In one case, energy use increased from 0.36 to 0.51 kWh/m³ due to heavy rainfall. The authors emphasize that it is important to implement advanced technologies that mitigate the effects of climate change.

To facilitate a clearer comprehension,

Table 4. Analysis of the extreme weather events that occurred in Europe and classified in terms of their impact on the energy systems and mitigation strategies. Source: own elaboration from [22,23,24,25,26,27,28,29,30].

Event	Country	Impact	Response/Strategy	Reference
Ice storms affecting infrastructure	Slovenia	Damage risk to wind farms and power lines	Risk-informed spatial planning	[22]
Hydropower revenue uncertainty	Europe (general)	Volatility in water flows and electricity prices	Risk management for supply reliability	[23]
Heavy rains and hydro plants	Slovenia	Erosion and sedimentation risks	Updated engineering standards and location planning	[24]
Gudrun storm (natural disaster)	Sweden	Major outages, economic losses (up to €3 billion)	Integration of climate risk into energy policy	[25]
Seasonal climatic variations and prices	Italy	Electricity price fluctuations (winter vs. summer)	Climate-sensitive electricity market forecasting	[26]
Geomagnetic storms and grid stability	Czech Republic	Power line anomalies (5–10%), transformer delays	Infrastructure monitoring and resilience improvement	[27]
Climate variables and electricity prices	Portugal	Price volatility linked to temperature, pressure, radiation	VAR modeling including meteorological data	[28]
Climate change effects on wastewater plants	Italy (Puglia)	Increased energy costs, operational challenges	Adoption of advanced treatment technologies	[30]

provides a summary of the findings from the literature review in Europe, detailing key aspects such as the event, date, country, and reference, alongside information on supply interruption and grid instability, system responses, and suggested strategies proposed by the authors to address the identified challenges.

4.4. North America

North America faces many challenges from extreme weather events such as hurricanes, floods, and winter storms due to its wide climate zones and expanding energy infrastructure. North American energy systems—ranging from a wide range of renewable energy sources and fossil fuels to hydropower—appear increasingly susceptible to climate-driven disruptions, resulting in widespread outages, economic losses, and changes in energy market behavior. Moreover, individual studies show how North America is both under siege by these major threats and is combating them through innovative strategies and adaptive frameworks. The most important studies on this topic are listed chronologically below.

The resilience of electrical power systems is also examined across regions susceptible to extreme weather events such as hurricanes and storms. The focus of the study is on studying the ability to recover quickly and efficiently after these events. Specifically, a probabilistic modeling framework is designed to quantify resilience by integrating a hurricane and extreme storm hazard model; this study is applied to the Harris region, Texas, USA, using real data from Hurricane Ike in 2008. The research estimates economic losses due to reduced resilience, reporting potential losses of up to $83 million per year; therefore the authors provide a framework to assess the vulnerabilities of electrical systems in addition to implementing mitigation strategies to improve the resilience of these same systems [31].

The risks to wholesale electricity markets in New England (U.S.) are also analyzed, particularly due to changes in wind energy production caused by winter storms in that country, specifically investigating the vulnerability of the English electricity system under these catastrophic events. They do this with different advanced simulations, creating a model of the impact of winter storms on wind generation capacity and the resulting effects on prices and stability of the electricity market. With this, the authors were able to conclude that, during extreme storms, especially those that are very consecutive, wind generation losses can increase the volatility of electricity prices and increase dependence on energy sources based on fossil fuels. In some scenarios, price spikes exceeded 600 USD/MWh, especially during high-demand winter events. This happens because, when prices rise, people look for cheaper and more effective options than electricity. Like other studies, the authors propose implementing mitigation strategies that are capable of avoiding this type of volatility and drastic changes in the supply and demand of the country’s energy basket [32].

The issue of infrastructure vulnerability in the United States is further explored through research that examines how vulnerable the electrical infrastructure is to different hazards related to climate change, such as torrential rains or super storms. For example, the case of Sandy in Long Island, New York, USA, is analyzed using a scenario-based approach to evaluate how changes in temperature, soil, and sea can influence the creation of storms in the future [33]. The authors reached interesting conclusions; among them they were able to demonstrate that simulated increases in temperature of up to +4 °C and sea-level-rise projections could entail risks to the entire electrical infrastructure; for example, simulations show that future storms similar to Sandy could lead to more than twice as many flooded substations compared to 2012 (from 12 flooded substations in 2012 to up to 30 under the 2090 scenario), greater physical damage to transmission lines and substations, and higher recovery costs following the storm.

The projected impact of rising temperatures due to climate change is examined through an analysis that investigates how these variations may affect the United States electricity sector. To do this, they use an Integrated Planning Model (IPM^®), analyzing heating and cooling degree-days, electricity demand, and the efficiency of power generating units. Among the conclusions of the analysis, it can be observed that, without mitigation, annual electricity production costs in 2050 could increase by 14% (approximately $51 billion) due to increased cooling demand, but, on the other hand, with mitigation measures that reduce emissions from the United States electricity sector by 36% below 2005 levels by 2050, the increase in costs to meet elevated demand will be comparable to that of the scenario that does not present any mitigation [34].

On the other hand, a study analyzes the performance of the Florida electrical system against storms and hurricanes, focusing specifically on storm-induced damage to the electrical infrastructure and restoration times. To do this, the researchers develop damage assessment models for various components of the electrical system, in addition to evaluating the duration of interruptions through statistical and stochastic models. The study concludes that their models are very effective in predicting vulnerable areas and estimating hurricane-related outages, achieving overall network error rates between 3% and 9% when validated against Hurricanes Katrina and Wilma. In addition, the researchers found that the main cause of power interruptions are trees and the wind momentum produced by hurricanes [35]. The exploration of the impacts of long-term droughts on hydropower generation is carried over to a discussion of natural gas price fluctuation and how these factors shape the strategies applied to mitigate financial risk.

In the context of regional energy systems, particular attention is given to the western part of the United States, where researchers examine the effects of climate change on the electrical system. This is performed using climate models and energy analysis to try to predict when temperatures will be very high, along with changes in precipitation and streamflow. As expected, the results indicate that climate change significantly influences the generation capacity of the electrical system, including hydroelectric generation. The study shows that average summertime generating capacity could decrease by 1.0–2.7 GW by mid-century (2040–2060) in the Western Electricity Coordinating Council (WECC) region. The changes indicated lead to higher operating costs and the need for additional investments in capacity to meet demand. Therefore, the study emphasizes the vulnerability of the electrical system in this area of the United States, in addition to recommending the implementation of adaptive strategies to mitigate these challenges [36].

Attention is also focused on strengthening and maintaining electric power infrastructure to mitigate the effects of hurricanes, in an area of the United States where the damage that hurricanes cause to electric power systems and the importance of developing management strategies for the assets are highlighted [37]. To achieve this, the authors design a partially observable Markov decision process, modeling the survival function of the components of the electric system under hurricane-induced stress. The final results demonstrate that customized strengthening measures and strategic maintenance planning improve the resilience of electric power systems in the specified area studied, reducing expected lifecycle costs by up to 74% when permanent hardening strategies are implemented compared to corrective-only maintenance approaches.

Building on this focus, a framework is proposed to efficiently assess the resilience of electric power systems affected by hurricanes, with emphasis on computational tools to quantify outages and restoration processes. The present study develops a probabilistic approach with the help of Bayesian networks to model the system response to hurricane-induced failures and models the physical and operational constraints of power flow [38]. The methodology implements the framework in a case study concerning Harris-County Texan resilience to Hurricane Ike in 2008. The proposal assesses the outages to customers within distributed blocks of 1 km² and performs a simulation of restoration on the basis of historical resource mobilization data. The study mined outage and restoration sequences and presented the predictive accuracy of the model as reasonably satisfactory with a mean error of 15.4% at the ZIP code level. The conclusions highlighted the framework for generating insights for reinforcing power system resilience.

Moreover, a complementary approach involves integrating climate change uncertainties into power generation planning using stochastic optimization models. Discretized modeling of climate change scenarios focuses on investigating the uncertainties and variability of temperature, precipitation, and energy demand [39].

From this perspective, strategies must be based on reducing costs while improving the resilience and flexibility of energy systems to the long-term impacts of climate change. Moreover, a stochastic optimization model is used that considers the uncertainties relevant to each climate change scenario. Two optimization strategies are considered: minimizing the total expected cost across all scenarios and minimizing maximum regret, so that, once decisions are made, the company does not find itself in a situation that renders it unviable. The model considers not only costs but, more importantly, the variability of climate impacts to illustrate the trade-off between costs and risk management considerations in planning decision-making. The findings highlight the benefits of using integrated planning frameworks when addressing discrete climate change scenarios [40].

In addition, operational efficiency in power restoration following hurricanes is also addressed, with an analysis based on data from 27 restoration events at 13 utility companies using a data envelopment analysis (DEA). Part of the analysis shows that during Hurricane Sandy, approximately 8.5 million customers experienced power outages, and more than 1 million were left without power for more than a week. In addition, the DEA results reveal consistent performance trends among utility companies. For example, some companies achieved higher efficiency levels due to resource allocation and restoration strategies; however, utility companies had problems due to inadequate resource mobilization. Knowing this, researchers emphasize the importance of systematic performance evaluations, in order to identify best practices and improve restoration processes [41].

Additionally, the impact of geomagnetic storms on power transmission systems is analyzed, with a specific emphasis on how voltages are induced transmission lines under volatile Earth conductivity conditions. The study evaluates how 3D Earth impedance models improve the understanding and quantification of the effects of geomagnetic storms on power grids compared to 1D models. An example of this is what happened during the 1989 storm: 62 transmission lines exceeded 100 volts under 3D modeling, compared to only 16 lines using 1D models. 3D models provide a more accurate assessment of the impacts of geomagnetic storms on power systems [42].

Furthermore, risk mitigation in power transmission systems, analyzed using a probabilistic model, was designed to reduce potential vulnerabilities. The model has the following components: a weighted deterministic hazard analysis model, component vulnerability assessments, system performance modeling, and life-cycle cost analysis to assess the cost-effectiveness in reducing risks. This methodology was applied to different electrical systems in regions of the United States, including Charleston, South Carolina, and New York City, New York. Probabilistically weighted hazard scenarios can better capture the cumulative impacts of seismic and hurricane events, and the vulnerability of the system could be identified, such as the fragility of transmission lines under strong winds and seismic activity [43].

In a related study is the implementation by Nateghi [44], where the researchers present a resilience strategy in electric networks of areas that are specifically vulnerable to hurricanes; for this, the authors used advanced statistical machine learning techniques (artificial intelligence) to quantify the interactions between the system topology, the characteristics of the hazards, and the environmental conditions of the study site; Bayesian networks were also used to model the relationships between the predictors, which include different parameters such as customer density, tree pruning frequency, hurricane intensity, land cover, and soil moisture. The study concludes that factors such as high customer density and inadequate tree maintenance significantly increase the vulnerability of the system to hurricanes and similar climatic hazards.

Similarly, in the same year, Mitsova et al. [45] conducted research analyzing how socioeconomic vulnerability affected power restoration after Hurricane Irma in Florida. The data used were from 9 to 29 September 2017. At the peak of the hurricane, more than 36% of all accounts in Florida experienced power outages. In addition, associations are identified between prolonged power outages and specific socioeconomic factors, such as higher proportions of minority populations, residents with disabilities, and higher unemployment rates.

Subsequently, years later, the research carried out by Zou and Chen [46] developed a two-level stochastic resilience model addressing interconnected failures between traffic and power systems. The study carried out in Galveston, Texas, USA, shows as a result that prioritizing the restoration of traffic signals reduces the average recovery time of energy services by up to 15%, in addition to emphasizing problems such as poorly connected nodes in the network.

Additionally, climate-driven interactions between air temperature and river flows are examined with a focus on how these variables influence electricity market dynamics on the West Coast of the United States. The findings imply that temperature increases create additional electricity demand for summer cooling, while shifting hydroelectric availability to spring and winter [47]. In the Pacific Northwest (PNW), climate risks are mainly linked to variations in river flows, while in California extreme heat waves markedly increase electricity demand with consequent influences on system reliability.

Moreover, scholars have started to focus on resilience to very large-scale weather events (VLSWEs), as exemplified by Winter Storm Uri in 2021, which exposed the vulnerabilities of electric systems during extreme events. For example, during Winter Storm Uri in Texas, nearly 4 million people experienced a loss of power and water for days, with estimates suggesting that 210 people died, and there was nearly $120 billion in economic impacts [48]. The study cited examined the potential capacity of the electric grid in ERCOT to withstand, adapt, and recover from extreme events like Uri. The paper highlights the need to shift the approach towards power grid planning and operation to be more interdisciplinary to effectively respond to the challenges posed by VLSWEs. With more resilience metrics incorporated into system operations and planning, preparedness and response would improve immunity against such extreme events.

Furthermore, other interesting work investigates the coupling of electrical power systems (EPS) and water distribution systems (WDS) during severe drought events, along with the effects on resiliency in the systems. This is achieved by establishing a completely coupled model characterizing the energy uses of the WDS pumping systems alongside the cooling water uses of the thermoelectric systems located within the EPS. Once this is completed, the study concludes that strategies such as adjusting cooling water demands and reconfiguring power generation dispatch must be incorporated to extend operational capacity during events of this type. Therefore, these can extend the dispatch availability of conventional power plants by up to 25% during severe droughts [49].

In addition, geoelectric vulnerability in power transmission systems is also assessed in Canada, where researchers study the effects of geomagnetic storms on power transmission lines in the Alberta region. The authors use magnetotelluric (MT) impedance data, which are measured one by one, to then punctually estimate the geoelectric field generated during a magnetic storm on 8 September 2017, after which they compare the results with one-dimensional (1-D) and three-dimensional (3-D) terrestrial conductivity models [50]. The study found that the geoelectric field is stronger in northeastern Alberta, where the Canadian Shield is located. Resistive causes high voltages to be induced in the transmission lines up to 120 V higher than those estimated by the 1-D models, which means that the results obtained by the 3D models are more representative.

Infrastructure resilience is examined in the context of the impact of climate change on levee-hydraulic systems that support electric power networks. This multidisciplinary perspective integrates climate science, hydrology, and electric power analysis within a common framework to assess system resilience [51]. The study utilizes a resilience index for the power system to assess system performance and compares the probabilities that the power network components will no longer function due to a range of flood events in the baseline, historical flooding, and projected future flooding scenarios. Through this comparison, the framework assesses to what extent resilience loss of the system occurs with time and how climate increasingly introduces more risk to the given system. Findings showed a totally diminished resilience in the system projected during future flooding scenarios riding on an uptake of higher flooding hazards from climate change. The results support a much-needed emphasis on improving power network resilience through the adoption of climate-adaptive infrastructure planning strategies that could involve redesigning levees, setting new engineering standards, and strengthening power grid components in order to withstand greater flood hazards

Continuing this line of research, recent developments evaluate the vulnerability of electrical networks to hurricanes. A digital twin (DT) framework combines physics-based models and real-world data using a dynamic Bayesian network (DBN) to monitor and predict, in near real-time, the failure states and performance of components in the power system. The study focused on Galveston Island, Texas, and was validated using historical data, so that, at the end of the research, the results showed that DBN allows the integration of real-time sensor data, providing detailed estimates of the performance of power grid elements, which is essential to address the increasing frequency and intensity of extreme weather events that are strictly related to climate change [52].

Building on these findings, another important study is the one developed by Soleimani et al. [53]. The researchers investigated the impacts of power outages and other services such as water, in homes during the 2021 Winter Storm Uri phenomenon in Texas, USA. The data used are surveys collected in several Texas communities affected by the storm. Some of the notable findings are that more than 4.5 million customers experienced power outages, and some areas suffered interruptions for more than 96 h. In addition, water outages aggravated the situation, leaving many without basic services. Generally, researchers emphasize that there is a pronounced inequality in adaptive capacity, since low-income communities face greater problems due to limited access to backup systems such as generators. Therefore, the authors propose the creation of policies that can help these types of populations that are vulnerable in this type of event.

Expanding the analysis of social impacts and the social consequences of infrastructure failure are also explored by analyzing the impacts of power outages and other services such as water in homes during the 2021 Winter Storm Uri phenomenon in Texas, USA [54]. To do this, the authors developed an analysis containing two stages. In general, what the researchers did was model the power grid disruptions caused by a cyberattack during an extreme heat wave. In the primary stage, they used a power flow model to simulate operational impacts; with this, they found that the combined scenario can increase the unsupplied electrical load on Long Island from 4% to 13%, which could affect almost 600,000 customers. In the second stage, by combining the results with a computable general equilibrium (CGE) model, they found that activities of state and local governments could decrease by up to 30% in the composite scenario. Therefore, the study emphasizes the need to propose resilience strategies to protect infrastructure and sustain economic activity in regions with a high percentage of urbanization such as New York.

Following this, another important study is the one carried out by Ali et al. [55], where researchers analyzed how promoting distributed generation (DG) could reduce the vulnerability of electrical systems to natural disasters. Using a system-of-systems (SoS) framework integrating agent-based modeling (ABM) and optimal power flow (OPF), they conducted two main analyses: (1) determining the minimum DG required at a specific location to prevent blackouts and (2) applying a genetic algorithm to identify the total allocation of DG in the network, in order to mitigate failures in any transmission line. The researchers found that DG can improve the resilience of electrical networks against natural disasters that could occur.

In addition, electric power sector dynamics under climate change mitigation strategies and economic development are further analyzed, pointing out site-specific factors affecting the system’s evolution [56]. The study examines power generation, CO₂ emissions, water use, and LCOE to show how states manage uncertainties during the energy transition. While population growth does, to a wide extent, dictate the growth in electricity demand, it is not more than industrial dominance across several states; for example, populations in Texas have a far more pronounced story in affecting demand than other states. Variations in regions underscore the need to understand local consumption and electrification patterns for energy response management during extreme events. On the sustainability front, scenarios with lower emissions lead toward a massive drop in water withdrawal for electricity generation thanks to technological improvement and augmented adoption of renewable energy. While water-use habits differ from state to state, in Florida, water withdrawal has gone down, whereas in Texas, it has gone up. A substantial reduction in CO₂ emissions would accompany a remarkable rise in energy prices, especially in the eastern region of the U.S., but together these served as a wake-up call to the economic burden posed by aggressive decarbonization. This study emphasizes trade-offs between emission reduction goals and the hydrological and electrical management of other resources in the face of a climate-induced disaster.

Lastly, the paper written by Zhao et al. [57] analyzes the impact of Hurricane Harvey on the nodal electricity prices (NEP) in the ERCOT market in Texas, USA, treating the hurricane as a natural experiment. The study applies synthetic control methods for causation quantification, showing that the southern Texan price volatility was most affected, primarily in areas with less grid access and closer electrical connection to segments of the damaged network. The analysis illustrates how counties with less favorable socioeconomics and greater hurricane exposure were disproportionately affected by price surges in electricity. The price impact in those nodes multiplied with an extra burden on vulnerable communities. The research provides a critical impetus for the implementation of targeted improvements in infrastructure and the enhancement of disaster preparedness programs to mitigate these differences. Further, this research points to the need for a network-oriented view for better insight into how external shocks, for instance, a natural disaster, propagate through and affect the operations of wholesale electricity markets.

Table 5. Analysis of the extreme weather events that occurred in North America and classified in terms of their impact on the energy systems and mitigation strategies. Source: own elaboration from [31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57].

Climate Event	Effects	Adaptation Strategies	References
Droughts and heat waves	Hydropower loss, blackout risk.	Solar, wind growth, water efficiency.	[36,47,49]
Floods and storms	Grid damage, instability.	Flood defenses, climate planning.	[31,33,35,37,38,41,46,48,51,52]
Wind variability	Wind shortfall, price spikes.	Wind farm diversification.	[32]
Climate change and system stress	Hydropower fall, fossil use, instability.	Renewables, carbon capture, risk planning.	[39,40,42,43,44,50,56]

summarizes the key findings extracted from the reviewed bibliography, highlighting the main themes, their associated impacts, proposed solutions, and supporting references.

4.5. Australia

Australia, with its vast geographical area and unique weather conditions, faces special challenges related to energy stability in extreme weather situations. Frequent storms, heat waves, and the occasional “renewable drought” where sustainable energy generation is very low have marked effects on the region’s electricity systems, not only that, but also the growing dependence on renewable energy sources such as wind and solar, which is initially seen as a good thing, ignoring the various problems that this situation produces. Therefore, in this part of the review, studies address how Australia improves the resilience and efficiency of its energy infrastructure.

Specifically, from the analysis and observations of Lyons et al. [58], wind power fluctuations during storms disrupted balancing generators and carbon emissions within the Australian National Electricity Market (NEM). The study focused on how large fluctuations in output from the wind farm during storms affected the efficiency of fossil-fueled generators used for balancing and the overall net carbon emissions. The researchers used data from storm events of 2012 and 2013 to estimate the output variations of Frequency Control Ancillary Services (FCAS) generators, assessing their efficiency and overall emissions impact. The authors reformulate heat rate curves for each generator such that operating ranges and emissions linked with the compensation of wind power variability are appraised. These findings indicate that, even if the efficiencies of FCAS generators are lower during the times that wind power output arises, displacement amounts to reduced net carbon emissions because wind power substitutes fossil fuel generation. Across all storm events analyzed, wind energy consistently offsets the increased emission intensity from lower FCAS efficiency. The outcomes accentuate the role expected of wind power to play in curtailing carbon emissions even under erratic conditions, such as storms.

Furthermore, in managing disruptions to energy supply caused by extreme weather events, an analysis focused on Australia’s National Electricity Market aimed to identify and mitigate periods of low renewable generation, termed “renewable droughts”, using 15 years of climate and power demand data [59]. The findings indeed show that the months of May through August pose the greatest risk of load loss in the NEM. The mixture of factors behind this is an expectedly high demand in southern Australian states, reduced solar generation, and extended low-wind periods. Proposed renewable energy mixes must account for seasonal low-wind winters, not just isolated events. Energy storage assists in addressing the short-term nighttime demand, and dispatchable thermal generation technologies can provide a more cost-effective solution for such durations of low-wind generation. Including offshore wind could reduce storage needs, although floating turbines remain economically unfeasible. This research sets a foundation for developing resilient electricity systems in the NEM, managing disruptions from extreme weather phenomena while ensuring supply stability from seasonal variations in renewable energy generation.

Table 6. Analysis of the extreme weather events that occurred in Australia and classified in terms of their impact on the energy systems and mitigation strategies. Source: own elaboration from [56,57].

Event	Key Impacts	Proposed Solutions	References
Wind Power Variability During Storms	Fluctuations in wind power output disrupt balancing generators, reducing their efficiency and increasing emissions temporarily.	Promote wind power integration as it offsets high-carbon emissions from fossil-fueled generators despite variability.	[58]
Seasonal Renewable Energy Deficits (“Renewable Droughts”)	Low renewable generation in winter (May–August) risks load loss in the National Electricity Market (NEM), especially in southern Australia.	Develop energy storage systems for short-term demand, integrate offshore wind energy, and maintain dispatchable thermal generation for cost-effective backup.	[59]

summarizes this topic, focusing on the key challenges and impacts related to renewable energy in Australia, such as wind power variability during storms and seasonal renewable energy deficits.

4.6. Latin America

Extreme weather events are changing energy markets in Latin America, generating supply imbalances and rising prices. For example, climate events such as the El Niño phenomenon can cause hydroelectric generation in some countries, such as Argentina, Brazil, Mexico, and Venezuela, to be reduced by up to 50%, resulting in a greater risk of blackouts. Furthermore, they can generate excessive increases in electricity prices [60].

This high volatility in prices can be reflected in industrial production costs, as was the case in Peru and Chile, where energy prices are the main problem for industries and make them less competitive in international markets [61]. For this reason, countries are beginning to diversify their energy matrices by incorporating renewable sources such as solar or wind, which allow for a reduction of up to 0.2 GWh per MW of energy deficit in critical drought months, in addition to giving greater resilience to the electrical infrastructure to guarantee stable access to electricity and combat extreme events [62].

Extreme weather events are significantly transforming Mexico’s energy system, disrupting not only production but also the stability of energy markets. For example, an atmospheric analysis of wind energy has confirmed that wind patterns associated with climate phenomena such as El Niño can increase summer wind speeds in regions such as Chiapas and Oaxaca, while La Niña weeks are affected by lower speeds, significantly impacting wind energy production in southern Mexico [63]. At the same time, in the Yucatán Peninsula, communities have reported a clear shift in the timing of rainfall, but especially an intensification of droughts. This has led to increased energy use linked to irrigation and crop conservation, which has intensified pressure on local grids [64]. At the same time, a recent analysis shows that extreme weather events indirectly affect energy costs, putting pressure on harvests and distribution. Under extreme weather conditions, a 1% positive impact on the country’s gross domestic product (GDP) generates an additional 0.90% increase in the 12-month cumulative inflation [65].

In the face of these risks, Mexico is developing adaptation strategies, such as the geographic diversification of wind farms to avoid simultaneous production losses, the promotion of resilient agricultural systems in rural areas, and the explicit incorporation of climate risks into the design of economic and energy policies.

Building on the global perspective, the focus now shifts to Colombia. A climate change impact analysis on hydropower generation has been conducted through a multi-model approach by Arango-Aramburo et al. [66]. This study applies partial and general equilibrium models (GCAM, TIAM-ECN, Phoenix, and MEG4C) to define adaptation pathways for the energy sector under two scenarios of greenhouse gas concentration, RCP4.5 and RCP8.5. The simulations project changes in water availability and hydropower capacity over the next 30 years, assessing their impact on electricity generation.

The results indicate that the loss of hydropower generation estimated is still a relatively small proportion of growth in Colombia’s electric demand, but these losses necessitate substantial investments in other technologies. In addition, RCP4.5 gives priority to renewable sources such as wind and solar, and the RCP8.5 scenario mostly adopts fossil-based technologies with carbon capture and storage. The trade-offs between the said mitigation strategies include renewable deployment as opposed to relying on traditional energy sources.

Hydroelectric power plants are greatly affected by climate change, which subsequently influences expansion strategies of these systems, according to Restrepo-Trujillo et al. [67]. The need to analyze the influence of climatic phenomena like El Niño upon hydraulic generation planning, especially in the medium to long term, led to this study. The paths of the analyses show that a number of processes linked to El Niño with associated severe droughts tending to reduce river flows and create low levels in reservoirs, thus greatly affecting the generating capacity. For instance, Colombia’s hydroelectric power plants can suffer a 30% reduction in capacity during a drought. Increased dependence on thermal plants results in a rise in generation costs and CO₂ emissions and puts pressure on new strategies. The author recommends diversifying into the non-conventional renewable sources of solar energy and wind and also discusses efficient water resource management measures. All of this aims to counteract the impacts of climate change, ensure energy security, and optimize generation costs.

Additionally, the authors show how energy prices in the stock market responded to episodes of El Niño and La Niña. During periods of very intense El Niño—such as the event between January 2015 and 2016—energy prices rose significantly, reaching nearly $1900. This represents an increase of up to 87.5% over the period, underscoring the substantial impact of extreme climatic conditions on market behavior. Moreover, hydrological vulnerability due to climate change is further addressed by analyzing the effect of climate change on river discharge and flooding extent in the Magdalena River basin in Colombia. An important study applies a hydrological and hydrodynamic model based on general circulation projections [68].

The research analyzes debated scenarios based in the future under different Representative Concentration Pathways (RCPs: RCP4.5 and RCP8.5) to determine changes in hydrology and flood risk assessment. The analysis uses climate time-series data to assesses future river discharge and flood risk areas. The authors reveal that, according to the RCP8.5 scenario, extreme floods could become more frequent and damaging in the basin by the middle of the 21st century. While projections reveal an uptick in the flood extent in important areas of the basin with considerable consequences for agriculture, infrastructure, and urban sectors, that change underscores the increasing vulnerability of the Magdalena River basin to climate-change-induced hydrological alterations. The final statements illustrate how climate adaptation strategies ought to be integrated in water management policies. The authors suggest enhancing flood forecasting systems, improving resilience of infrastructures, and implementing sustainable land-use practices to mitigate damages. These findings provide an important connection between political actions, water resource management, and regional stability in Colombia.

Table 7. Analysis of the extreme weather events that occurred in Latin America. Source: own elaboration from [60,61,62,63,64,65,66,67,68].

Climate Event	Effects	Adaptation Strategies
Drought [60,66,67]	Drop in hydropower output. Increased blackout risks.	Solar and wind expansion. Improved water resource management.
Floods [68]	Infrastructure damage. Grid instability.	Strengthening flood defenses. Climate risk planning integration.
Wind pattern variability [63]	Reduction in wind energy generation.	Geographic diversification of wind farms.
Long-term climate change [62,64,65]	Decline in hydropower capacity. Higher fossil dependency.	Renewables investment. Carbon capture development.

summarizes the key findings related to climate impacts and adaptation strategies.

5. Climate Risks and Energy Market Dynamics

This section will provide a worldwide analytical aggregation regarding the risk associated with extreme climate events on energy markets. Rather than accounting for individual case studies, the aim was to identify generalizable relationships across a range of phenomena—hurricanes, droughts, floods, heat waves, and geomagnetic storms—in terms of their incidence and magnitude of economic and infrastructural consequences.

Using the findings from the systematic literature review, a semi-quantitative risk index was generated to rank events based on their relative impacts on supply stability, price volatility, infrastructure impact, and shifts in demand. This part of the study allows for the development of a conceptual framework to develop thinking about system vulnerabilities to increasing climate pressures and how energy markets respond.

5.1. Risk Assessment Methodology

The systemic risk posed by extreme weather events was assessed based on two important analytical parameters:

• Frequency: This is the occurrence of a specific event impacting the energy system across locations, as identified from the reviewed scientific literature. Events were mapped as incidents based on the frequency with which they were documented across the selected studies.
• Severity: This is the extent of disruption generated by an event based on implications to price volatility, supply interruption, infrastructure damage, and demand shock.

Both frequency and severity were normalized from 0 to 1:

• 0 indicates an absence of a significant occurrence or negligible impact.
• 1 indicates an extremely frequent occurrence or catastrophic severity.

In terms of simplifying the classification of events, a scale of five levels was created. The scale ranges from very low to very high, and the levels were defined according to the patterns identified from the literature review where impacts were described in terms of frequency and severity (

Table 8. Categorization of frequency and severity impacts. Source: own elaboration.

Level	Description	Numerical Value
Very Low	Rare occurrence or negligible impact	0.1–0.2
Low	Occasional occurrence with minor impact	0.3–0.4
Medium	Regular occurrence with moderate impact	0.5–0.6
High	Frequent occurrence or severe impact	0.7–0.8
Very High	Widespread occurrence with catastrophic impact	0.9–1.0

). This method of semi-quantitative categorization allows for the uniform interpretation of various kinds of climate events and allows for a consistent risk assessment process.

To continually analyze the systemic risk for various types of extreme climate events, we calculated a composite risk score (

Table 9. Composite risk scores for major extreme climate events. Source: own elaboration.

Climate Event	Frequency	Severity	Composite Risk
Hurricanes	0.9	0.9	0.81
Droughts	0.9	0.8	0.72
Floods	0.9	0.8	0.72
Wind Pattern Variability	0.7	0.5	0.35
Geomagnetic Storms	0.5	0.8	0.40
Heat waves	0.7	0.6	0.42

).

The score was calculated using the following formula, based on the composite normalized scores for frequency and severity assigned to each of these events:

$$\mathrm{Composite} \mathrm{Risk}=\mathrm{Frequency}\times \mathrm{Severity}$$

(1)

This approach accounts for both the frequency of an event and the amount of disruption it causes, providing an orderly basis for comparing the variety of climate events. The result is a score that identifies those events that pose the most serious threats to energy markets and society with regard to price volatility, supply disruptions, damage to infrastructure, and demand shocks at the event’s tail end.

The composite risk assessment results indicate that hurricanes, droughts, and floods have the highest systemic risk scores among all of the disasters considered, and each has a composite value above 0.7. The literature mentioned these disasters frequently, causing large disruptions in energy supply, severe temporal price fluctuations, and disrupting infrastructure associated with energy supply networks. The composite scoring for hurricanes demonstrated a frequency score of 0.9, which indicates that hurricanes were mentioned throughout many studies across North America and other countries. The disruption to oil, gas, and electricity markets caused by hurricanes has been well documented, and the studies have indicated that the impact of hurricanes is categorically systematic. The severity score of 0.9 indicates the historical cumulative damage to energy infrastructure and cascading economic impacts from hurricanes on the environment.

The assessments of droughts and floods indicated similar frequency scores of 0.9 in studies that documented vulnerabilities to hydroelectric production and grid stability during extreme weather events from climatic events such as El Niño. The degree of severity for these disasters was assigned a severity score of 0.8 to represent the moderate to high levels of disruption to generation capacity and distribution systems. The other weather phenomena like heat waves, wind pattern changes, and geomagnetic storms did not receive high composite scores, ranging between 0.35 and 0.42. These scores seem moderate compared to other events because the frequency or level of impact was not seen as strongly concerning, by the authors, compared to the top three items. Nevertheless, the other extreme events do cause risks that planners have to consider, especially since they occur more often due to changing climate uncertainty and volatility.

5.2. Conceptual Framework Linking Climate Events to Energy Market Disruptions

In addition to the composite risk assessment, a conceptual framework was created to illustrate the connections and linkages within the systems that operate between extreme climate events and energy market disruptions. The framework provides a basic summary of events, starting with the hazard impact first arising from climate events, then moving through the impact path on energy systems, including supply disruptions, infrastructure damage, and increased demand, and finally into the full impact on market systems, including price fluctuations and supply shortages. The framework also serves to emphasize the importance of adaptation and resilience strategies that could serve to mitigate risks. Overall, the figure serves as a representation to summarize the way systems work together to designate how a climatic phenomenon disrupts the stability and functioning of energy markets.

The theoretical framework developed in Figure 1 represents the differentiated pathways whereby extreme climate events influence energy systems and markets. Even though each of the extreme climate events—floods, geomagnetic storms, heat waves, hurricanes, and droughts—creates different patterns of disruption at the level of infrastructure, the market impacts that arise tend to be the same, such as price uncertainty and volatility, supply shortages or lack of availability, and systemic constraints leading to market instability. Likewise, the adaptation and resilience strategies may share certain elements that are used as an approach to assess these risks, although there are some potential vulnerabilities that differ for each risk. This approach simplifies the nature of how various climatic hazards systematically and differently challenge the stability of energy markets while also identifying requirements for integrated and differentiated responses.

6. Discussion

Some of the results regarding catastrophic events that occur in different parts are summarized in Figure 2.

The graphic presented in Figure 2 shows the significant patterns of the analyzed studies on extreme events and their influence on energy systems from a global perspective. Analyzing this matrix, it can be stated that the most represented geographic area of the reviewed articles is that of North America and Europe, which denotes that they are the territories with a higher exposure to hurricanes, droughts, or floods but also a greater capacity to allocate resources to research these impacts. The disproportionate number of studies from other continents, such as Asia and Oceania, shows that there is a significant scientific coverage gap, despite the high vulnerability of these territories to extreme weather events, such as geomagnetic storms or wind variability.

Regarding the type of weather event analyzed, it can be observed that the most documented phenomena are hurricanes and droughts, since they are the most representative due to their immediate effects on energy structures and costs. In contrast, other climatic phenomena such as wind variability or geomagnetic storms are less represented in the articles analyzed, even though they can lead to significant interruptions in the provision of electrical and energy systems. This shows a limitation of the work where events with effects that are difficult to quantify or those with less immediate effects may not have been sufficiently represented; in other words, this type of phenomenon may have been underestimated in terms of its strength and social importance.

The development of the conceptual framework has provided a richer interpretation of how certain extreme climate events resulted in differentiated energy system disruptions and eventual market effects. The regional comparisons showed that although the disruptions differ in nature (e.g., hydroelectric vulnerabilities in Latin America and grid failures due to hurricanes in North America), their systemic impacts (e.g., price volatility and supply instability) generally differ less. The review of the literature also revealed significant gaps, particularly in the availability of systematic quantitative information on price behavior following climatic events, thereby limiting a comprehensive economic impact evaluation. Our findings led to recommendations for incorporating more detailed market analyses into future vulnerability assessments.

In turn, the different types of solutions to the problems addressed by climatic events are concentrated in the technological and infrastructural strategic reinforcement of electrical networks, diversification of energy sources, and use of predictive models.

On the other hand, the associated climate disasters have put immense pressure on electricity infrastructures, causing energy prices to skyrocket and critical systems to be put to the test. As an illustration, outages experienced in the ERCOT market in Texas due to Hurricane Harvey caused prices in South Texas nodes with poor grid connectivity to spike. Systemic failures during Winter Storm Uri left more than 4.5 million Texans without power for many hours, causing severe economic damages exceeding $120 billion. The urgent case for a resilient framework is underscored by applying machine-learning models to reveal necessary vulnerabilities in energy distribution systems and the targeting of strategies, which may include tree trimming and hardening of grid infrastructure in hurricane-prone areas.

Geomagnetic storms represent a unique threat to the power systems of transformers and system stability. It was pointed out that, in the Czech Republic, geomagnetic disturbances raise the anomaly rates of transformers by 5–10 with a day of storm action, with delayed effects stacking up to a maximum three days later. The findings support the consistent monitoring of geomagnetically induced currents and the incorporation of prediction tools into grid design to mitigate potential risks. Efficient modeling tools were also developed in Russia to assess the impacts of the geomagnetic storm on the power grid and identify ways to increase resilience against geoelectric field disturbances.

Flooding along with droughts are some of the added climatic problems to energy systems. In Northern California, mildly protected power grids experience reduced performance due to increased flooding due to a changing climate scenario. This study emphasized modern adaptation strategies, including new infrastructure and updated engineering standards to cope with elevated risk factors. On the other hand, thermal power plants in the southwestern United States find significant derating by drought scenarios and need innovative thinking—that is at times providing reconfigured generation dispatch to keep running. These cases highlight the need for integrated water and energy resource management under extreme climate situations.

The consequences of hurricanes prove to be yet another major challenge, especially concerning areas with high socioeconomic vulnerability. Analysis of the restoration of power following Hurricane Irma in Florida shows that low-income communities report disproportionately longer outages from power services, mostly because of subpar infrastructure that limits resources. Similarly, probabilistic models were created to assess hurricane-induced power interruptions for the county of Harris in Texas, estimating financial losses of $83 million per year. Such studies highlight the crucial nature of investing fairly in the infrastructure and resilience strategies aimed at dealing with the compounding effects of extreme weather on vulnerable groups of people.

The effects of socioeconomic and infrastructural vulnerabilities on the impacts of climate events on energy systems have been extensively explored. An analysis of the behavior of Florida’s power grid during hurricanes revealed that tree injury was the most important cause of power outages, leading Florida to embrace the practice of preventative maintenance. Similarly, the hurricanes in Galveston, Texas, revealed the interdependencies between traffic and power systems, with traffic disruptions causing a 15% increase in power recovery time. All of this corroborates the determination of the need for the channeled management of infrastructure to limit cascading failures of interconnected systems. The dynamics of energy markets in the context of extreme climate events is another critical focus. In Australia, for example, the effect of wind variation due to storms on the balancing generators of the National Electricity Market, when the latter was activated at the start of the balancing generator vehicles, resulted in increased carbon emissions. A similar finding was made in southern Texas when it was shown that electricity price volatility in electricity markets during Hurricane Harvey was increased by structural weaknesses in the grid, especially in those areas where connectivity was limited. These investigations emphasize the considerable consequences for the economy of climate-related energy interruptions, highlighting the importance of having resilient market frameworks.

Flood risks were also a major danger for energy infrastructures on a global scale. In northern California, for example, climate flood risks impair the resilience of electricity networks that are protected by dikes with a negative effect on system performance, and in southern Italy it is shown how wastewater treatment plants face higher energy and operating costs due to variability in rainfall patterns. These examples are evidence of the importance of including climate risk assessments in water and energy infrastructure planning to ensure functionality under extreme conditions.

The interrelationship between energy systems and geomagnetic storms has been widely studied. In the Czech Republic, it was found that geomagnetic storms induce a 5–10% increase in transformer anomalies within a 24 h period, peaking within days due to a delayed effect. In Russia, models simulating the effect of geomagnetically induced currents were built, detecting vulnerabilities in the power grid in the Samara region. The studies carried out demonstrated the importance of predictive modelling and grid reinforcement to protect critical infrastructure from geomagnetic disturbances, while emphasizing the universal nature of climate risks in relation to energy systems.

The vulnerability of hydroelectric systems to climate change has been studied, in particular, in regions where hydropower is dominant in the energy mix, which has led to the study of the influence of climate change on hydroelectric performance at a global level, and in particular in high-emission scenarios, where a reduction in water availability may imply reductions in generation capacity, with similar dynamics taking place in Colombia, where hydroelectricity represents an important portion of the energy matrix. Severe droughts caused by El Niño events have reduced hydroelectric capacity by up to 30%, leading to an increasing dependence on more expensive and polluting thermal power plants. With respect to extreme weather events, wind hazards have come to be considered a critical risk for power transmission lines.

They have been quantified for power lines worldwide along coasts where high wind speeds and aging infrastructure increase the probability of outages. In Colombia, there are also vulnerabilities in this regard, especially in the case of coasts exposed to hurricane-force winds. Transmission lines older than 20 years in these regions have been shown to have a 40% higher risk of failure, implying the need for modernized designs and structural reinforcements.

Energy system stakeholders should take measures to develop adaptive infrastructure, such as strengthening the resilience of the electricity grid, decentralizing energy generation sources, and implementing early warning systems to mitigate climate-related risks in vulnerable developing areas.

Future research should prioritize the acquisition and analysis of detailed quantitative data on the pricing behavior of energy markets following extreme climatic events, with a particular focus on developing countries, where systematic studies are fewer and resilience capacities tend to be more limited.

While the literature consistently reports that extreme climate events drive significant volatility and price increases in energy markets, specific quantitative estimates vary across regions and events, limiting a uniform numerical analysis.

7. Conclusions

Weather catastrophes such as hurricanes, floods, droughts, and geomagnetic storms pose an extraordinary threat to the global energy infrastructure. Such catastrophic events can disrupt electricity generation and transmission, change market prices, and trigger cascading failures in the interconnected systems of water and traffic networks. For example, hurricanes limit electricity supply in various regions that generally face price volatility for electricity, and some transformer failures have been recorded during geomagnetic storms. These challenges underline the compelling case for predictive tools and strengthening infrastructure resilience measures.

A connected energy–water–transport system calling for resilience planning is necessary. When one sector is disrupted, for instance, by flooding, the recovery in another sector is delayed. The studies therefore highlight the importance of cross-sectoral strategies to mitigate cascading climate-related disruption impacts.

Lower-income communities are more prone to potential damage to energy systems in the event of catastrophic events, experiencing longer power outages, higher prices due to weaker infrastructure, and limited resources.

Recent research around the world shows the serious susceptibility of electric networks in combination with the threats posed by climate change and natural disasters, such as floods, hurricanes, and extremely hot waves. There are multidisciplinary studies that link combined future floods and cyberattacks to a significant degradation of resilience, which is an argument that in their own countries, due to a very high electrical demand, there would be some whose needs are unmet, affecting millions of customers, because of the flood. These results depict the urgency of implementing climate adaptation strategies, such as changing the infrastructure and strengthening resilience through leveraging new digital technologies, namely digital twins.

The integration of advanced technologies, such as distributed generation and dynamic Bayesian networks, offers a paradigm shift in mitigating power grid disruptions during extreme events. Agent-based modeling, genetic algorithms, and real-time, adaptive-decision-making frameworks show scalable and efficient methods of reducing the vulnerability of infrastructure. At the same time, sustainability-related analyzes stress the need to balance decarbonization goals and resource management for climate-driven interruptions to avoid economic inequality.

Severe climatic events are highly disruptive to energy infrastructures, and they also reveal underlying vulnerabilities through overlapping and cumulative threat dimensions. As we experience more climate variability, the combined impacts from successive extremes—such as droughts that reduce hydroelectric production immediately followed by storms that damage transmission networks—have a tendency to accelerate system collapse. This increases the demands we face in terms of adaptive policies that emphasize multi-hazardous interactions rather than viewing events in isolation from each other.

Enhancing the resilience of energy markets to climatic extremes involves not only technical development but also institutional strengthening. The vulnerabilities identified in the present case of electricity markets suggest an urgent need for integrated systemic governance processes, with the flexibility to coordinate across sectors, jurisdictions, and stakeholders involved in multiple arrangements under uncertain climatic conditions. Future energy security will depend, in part, on governments and regulatory institutions designing adaptive governance systems capable of anticipating events, reacting quickly, and reorienting infrastructure adaptation to mitigate damages and hazards.