Researchers in Moroco analyzed cybersecurity challenges in smart grids, highlighting AI-driven detection and defense strategies against threats like distributed denial-of-service, false data injection replay, and IoT-based attacks. They recommend multi-layered protections, real-time anomaly detection, secure IoT devices, and staff training to enhance resilience and safeguard power system operations.

Researchers at Morocco's Higher School of Technology, Moulay Ismail University, have conducted a comprehensive analysis of emerging cybersecurity challenges in power systems and detailed recent advances in detection and defense strategies.

Their work emphasizes the growing role of AI in enhancing control, protection, and resilience in modern smart grids. It also classifies cyber threats by origin, impact, and affected system layers to provide a structured understanding and reviews machine learning and optimization-based intrusion detection systems (IDSs) for power systems.

The researchers highlighted that renewable smart grids face diverse cyber threats that can disrupt operations and compromise data. Distributed denial-of-service (DDoS) attacks, for example, flood networks with traffic, blocking legitimate access and delaying control actions, while data integrity attacks manipulate sensor or control data, causing incorrect decisions or blackouts.

Additionally, replay attacks retransmit intercepted data to confuse the system, and false data injection attacks subtly alter real-time data to mimic normal operations while disrupting the grid. Covert attacks inject hidden signals that manipulate system behavior without detection, whereas IoT device-based attacks exploit vulnerabilities in meters or sensors to spread malware, steal data, or launch DoS attacks.

Finally, zero dynamics attacks leverage system models to generate hidden signals that leave output measurements unchanged but affect operations, posing sophisticated stealth threats to smart grid security.

Join us on Apr. 29 for pv magazine Webinar+ | Decoding the first massive cyberattack on Europe’s solar energy infrastructure – The Poland case and lessons learned

The researchers warned that while smart grids have improved energy efficiency and flexibility through advanced communication tools and distributed energy sources, they have also introduced new cyber vulnerabilities. Threats such as phishing, malware, denial-of-service (DoS) attacks, and false data injection (FDI) can disrupt operations, compromise data, and damage infrastructure.

They recommend implementing defense strategies that maintain confidentiality, integrity, and availability, while also incorporating authentication, authorization, privacy, and reliability. Machine learning and data-driven intrusion detection systems can help identify anomalies and detect FDI attacks in real time, particularly in smart grids and industrial control systems such as SCADA, which rely on accurate sensor measurements for state estimation.

The research team also encouraged energy asset owners and grid operators to adopt substation security measures and protocol vulnerability analyses to detect risks at the hardware and network levels. Blockchain, distributed ledgers, and Hilbert-Huang transform methods are highlighted as tools to further strengthen cybersecurity.

IoT devices, including sensors and smart meters, should be secured with strong authentication, safe boot procedures, frequent firmware updates, and standardized security across manufacturers. Sensitive grid data should be protected using techniques such as homomorphic encryption to maintain confidentiality during storage and transmission.

“A multi-tiered security approach that includes firewalls, intrusion detection systems, and network segmentation can enhance grid resilience. Extracting critical elements from vulnerable IoT devices and leveraging redundant control channels ensures operational continuity during attacks,” the researchers stated.

Machine learning and anomaly detection systems should be deployed to enable real-time identification of irregular activities, including FDI and malware propagation. Standardized protocols and rapid incident response measures should also support collaboration among grid operators, IoT manufacturers, and regulators, facilitated by information-sharing platforms.

The researchers emphasize that human-centered attacks, including phishing and social engineering, remain significant threats, but these can be mitigated through regular staff and user training.

The review was presented in “Cybersecurity challenges and defense strategies for next-generation power systems,” published in Cyber-Physical Energy Systems.

An international reserch team developed two deep learning-based IDS models to enhance cybersecurity in SCADA systems. The hybrid approach reportedly improves detection of complex and novel cyber threats with high accuracy, adaptability, and efficiency, outperforming traditional methods across multiple datasets.

A Saudi-British research team has develeped two new deep learning-based intrusion detection systems (IDSs) that can reportedly improve the cybersecurity of SCADA networks.

In large-scale solar power plants, SCADA systems play a vital role by overseeing energy generation, monitoring the performance of solar panels, optimizing output, identifying potential faults, and maintaining smooth overall operations. In essence, they act as the central system that converts raw solar data into practical control decisions, ensuring the plant operates safely, efficiently, and profitably.

The scientists explaind that current cybersecurity frameworks are often inadequate for SCADA systems because they cannot fully cope with the complexity and constantly evolving nature of modern cyber threats. Most existing approaches rely on signature-based detection, which depends on prior knowledge of attack patterns and therefore fails to detect zero-day exploits or novel intrusion techniques.

To address this limitation, the researchers considered deep learning methods, as these techniques allows to process large volumes of data, identify complex patterns, and enable more proactive threat detection.

“Such capability of handling and analyzing big data is particularly useful during scenarios when SCADA systems are generating huge streams of real-time data, including sensor readings, control commands, and other system logs,” they explained. “Furthermore, deep learning methods, especially convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have shown outstanding performances in the detection of complex attack scenarios with sequential or spatial patterns in data.”

The proposed approach integrates two new IDSs, named the Spike Encoding Adaptive Regulation Kernel (SPARK) and the Scented Alpine Descent (SAD) algorithm. By leveraging their complementary strengths, the method reportedly improves spike-threshold accuracy while enhancing adaptability and robustness under dynamic conditions.

The SPARK model introduces adaptive spike encoding by dynamically adjusting thresholds based on input signal characteristics. It uses advanced statistical methods to respond to variations in neural input, improving sensitivity to changes in intensity and frequency. By integrating both temporal and spatial features, SPARK enhances information encoding, especially for complex datasets. Unlike traditional fixed-threshold methods, it provides context-aware thresholding, improving accuracy and reliability.

The SAD algorithm complements SPARK by offering an optimization strategy inspired by olfactory navigation, which is the process by which animals and organisms use odor cues to locate food, mates, or home, and Lévy flight behavior, which is a strategy obeserved in many animal species to randomly search for a target in an unknown environment. This purportedly enables efficient exploration of solution spaces and avoids local minima, ensuring optimal threshold selection.

The hybrid approach can dynamically adjust and optimize spike thresholds simultaneously, surpassing conventional static or isolated approaches, according to scientists, which noted that the SPARK model is well-suited for SCADA and IoT systems due to its scalability, real-time adaptability, and efficient data handling. Additionally, its lightweight design reduces computational overhead and false positives, making it effective for resource-constrained environments.

“SAD is complementary to SPARK in the sense that it focuses on improving the detection accuracy while maintaining computational efficiency,” the researchers emphasized. “SAD's anomaly scoring mechanism can be integrated into this framework to add another layer of detection, which can run parallel with SPARK. In effect, integrating the deep learning models into the scoring mechanism means that SAD would enable a much more fine-grained analysis of attack patterns with little noticeable impact on performance for the SCADA system in question.”

The researchers used multiple benchmark datasets are used to evaluate SCADA intrusion detection performance, including the Secure Water Treatment (SWaT) testbed, Gas Pipeline, WUSTL-IIoT, and Electra. These datasets capture diverse industrial environments, attack types, and operational conditions, enabling comprehensive testing. They also include time-series sensor data, actuator commands, and labeled attack scenarios such as denial-of-service (DoS), distributed denial-of-service (DDoS), malware, and injection attacks.

The diversity of datasets ensured accurate modeling of both normal behavior and complex anomalies in SCADA and IIoT systems, according to the research team. Standardized preprocessing, training, and evaluation procedures also enabled comparison across all tested models. Cross-validation and controlled training conditions, meanwhile, reportedly prevented bias and ensured reliable generalization results. Visualization tools such as histograms, loss curves, and confusion matrices provided insights into model behavior and anomaly detection.

The SPARK model was found to consistently demonstrate “superior” performance, achieving high accuracy, precision, and recall across datasets. It outperformed traditional machine learning and deep learning approaches in detecting diverse intrusion types.

“The findings underline, in summary, that the SPARK and SAD models are basically the final frontier in modern intrusion detection,” the scientists said. “Distinctly designed to provide improved detection capabilities and operational efficiency, the two designs also chart a way into more resilient and intelligent security solutions for modern industrial controlled systems (ICSs) and Internet-of-Things (IoT) networks.”

The novel IDSs have been presented in “SPARK and SAD: Leading-edge deep learning frameworks for robust and effective intrusion detection in SCADA systems,” published in the International Journal of Critical Infrastructure Protection. The research team comprised academics form the Leeds Beckett University in the United Kingdom and King Abdulaziz University in Saudi Arabia. 

54% of respondents cited “energy availability and redundancy” as the single greatest obstacle to successful data center development between now and 2030.

From ESS News

aw firm Foley & Lardner LLP released today its 2026 Data Center Development Report, focusing on the growth and challenges in the data center boom that aims to sustain the growth in AI and LLM usage.

A major focus was on energy, with 54% of respondents citing “energy availability and redundancy” as the single greatest obstacle to successful data center development between now and 2030.

In terms of the right energy mix for data centers, 55% of respondents agreeing that the ideal energy mix to meet the growing power demand of data centers is largely renewables (41%), followed by natural gas (17%), nuclear (16%), and BESS (14%).

Nearly half (48%) of industry participants named advances in energy efficiency (which often includes storage optimization) as the greatest opportunity for development through the end of the decade, and nearly three in four respondents (74%) said advanced energy storage systems like batteries, hybrid solutions, and microgrids are the best way to ensure energy resilience.

Only 14% of developers are actually pursuing modular and small modular nuclear reactors as a viable energy opportunity.

Intriguingly, 63% anticipate a “strategic correction” in the market by 2030, driven by the intense competition for power, with one unnamed banking executive in the report saying, “Once power runs out in 2027 or 2028, that’s where we think deal flow will start to slow down.”

105 U.S.-based respondents were qualified to participate in the survey, including those who had direct experience in data center development, energy procurement, technology delivery, or operations within the past 24 months.

Energy analyst firm Wood Mackenzie identified data centers as one of the five trends to look for in 2026 for global energy storage, and within the past week, a battery storage project decided to give up a grid-connection to a data center and re-tool the batteries, earning revenue without being connected.

What they said:

Daniel Farris, partner and co-lead of Foley’s data center and digital infrastructure team: “There is a Gold Rush mentality right now around securing power. That’s a big part of why people feel there’s a bubble,” said “There’s going to a period in the next two to three years where power at necessary levels is going to be really hard to come by.”

Rachel Conrad, senior counsel and co-lead of Foley’s data center and digital infrastructure team: “Over the next five to 10 years, power providers will need to either grow capacity or increase efficiency to meet the demand fueled by data centers.”

Renewables and storage could reliably power data centers, but success requires active grids, coordinated planning, and the right mix of technologies. Hitachi Energy CTO, Gerhard Salge, tells pv magazine that holistic approaches ensure technical feasibility, economic viability, and energy system resilience.

As data centers grow in size and complexity, supplying them with cheap and reliable power has never been more pressing. Gerhard Salge, chief technology officer (CTO) at Hitachi Energy, a unit of Japanese conglomerate Hitachi, shed light on the relationship between renewable energy and data center operations, noting that while technically feasible, success requires careful planning, the right infrastructure, and a holistic approach.

“When we look at what's happening in the grids, then renewables are an active element on the power generation side, and the data centers are an active element on the demand side,” Salge told pv magazine. “What you need in addition to that is in the dimensions of flexibility, for which we need storage and a grid that can actively act also here in order to bring all these elements together.”

According to Salge, the key is active grids, not passive systems that simply react to conditions. With more renewables, changing demand patterns, new load centers, and storage options like batteries and existing facilities such as pumped hydro, it is crucial to coordinate these resources actively to maintain supply security, power quality, and cost optimization.

“But when you talk about the impact and the correlation between renewables and data centers, you need always to consider this full scope of the flexibility in a power system of all the elements—demand side, generation side, storage side, and the active grid in between,” he said, noting that weak or congested grids would not serve this purpose.

AI data centers

Salge warned that not all data centers are the same. “There are conventional data centers and AI data centers,” he said. “Conventional data centers are essentially high-load systems with some fluctuations on top. They contain many processors handling requests—from search engines or other applications—so the workload is distributed stochastically across them. This creates a baseline load with random ups and downs, which is the typical load pattern of a conventional data center.”

AI workloads, in contrast, rely heavily on GPUs or AI accelerators, which consume significant power continuously. Unlike conventional data centers, AI data centers often run at sustained high load, sometimes close to maximum capacity for long periods.

“AI data centers are specifically good in doing parallel computing,” Salge explained. “So many of them are triggered with the same demand pattern at the same time, which creates these spikes up and down in the demand profile, and they come in parallel all together.”

These fluctuations challenge both the power supply and the voltage and frequency quality of the connected grid. “So, you need to transport active power from an energy storage system or a supercapacitor to the demand of the AI data center. And that then needs to involve really the control of the data center’s active power. What you need is the interaction between the storage unit and then the AI data center to provide active power or to absorb it afterwards when the peak goes down. That can be also done by a supercapacitor.”

Batteries can store much more energy than supercapacitors, but the latter can ramp smaller energies more frequently. “However, if you put a battery that is smaller than the load, and you really need to cycle the battery through its full capacity, the battery will not survive very long with your data center, because the frequency of these bursts is so high, then you are aging the battery very, very quickly, yeah, so supercapacitors can do more cycles,” Salge emphasized.

He also noted that batteries and supercapacitors are both mature technologies, but the optimal setup—whether one, the other, or a combination with traditional capacitors—depends on storage size, number of racks, voltage levels, and overall system design.

Managing AI training bursts

Salge stressed the importance of complying with grid codes across geographies. “You need to become a good citizen to the power system,” he said. “You have to collaborate with local utilities to make sure that you are not infringing the grid codes and you are not disturbing with the data center back into the grid. A good way to do this, when renewables and data centers are co-located, is to manage renewable energy supply already inside the data center territory. Moreover, having a future-fit developed grid is a clear advantage. Because you have much more of these flexibility elements and the active elements to manage storage and renewable integration and to manage the dynamic loads of the data centers.”

If the grid is not future-fit with modern, actively operating equipment, operators will see significantly more stress. “With holistic planning, instead, you can even use some of the data center flexibility as a controllable and demand response kind of feature,” Salge said, adding that data center operators could coordinate AI training bursts to periods when the power system has more available capacity. This makes the data center a predictable, controllable demand, stressing the grid only when it is prepared.

“In conclusion, regarding technical feasibility: yes, it’s possible, but it requires the right configuration,” Salge said.

Economic feasibility

On economics, Salge believes solar and wind remain the cheapest power sources, even when accounting for the grid flexibility needed to integrate them with data centers. Solar is fastest to deploy, wind complements it well, and both can be scaled in parallel.

“Any increase in data center demand requires investment, whether from renewables or conventional power. Economics depend on the market, and market mechanisms, regulations, and technical grid planning are interconnected, influencing energy flow, pricing, and system stability,” he said.

“We recommend developers to work with all stakeholders—utilities, technology providers, and planners—from the start to ensure reliability, affordability, and social acceptance. Holistic planning avoids reactive fixes and leads to better long-term outcomes,” Salge concluded.

Sungrow is introducing its large-scale energy storage system, PowerTitan 3.0, to Europe, featuring grid-forming capability, next-generation battery cells, DC coupling for co-located solar projects, and streamlined commissioning to accelerate deployment.

Sungrow is introducing its large-scale energy storage system, PowerTitan 3.0, to the European market. With the option to connect the battery to a central inverter on the DC side, the company is responding to strong demand for co-located solar-storage projects. The system was first presented at SNEC in Shanghai in June 2025 and has now been showcased to European developers at an event in Madrid.

The storage system is available in standard 10- and 20-foot container formats. The 20-foot version integrates a 1.78 MW power conversion system (PCS) with a 7.14 MWh battery, providing four hours of storage in a single container. A 30-foot version with roughly 12 MWh, also displayed in China, will not be offered in Europe due to logistics and transport costs, which could reduce project profitability. Larger systems in Europe can be achieved by connecting four units to form an AC block with approximately 7.2 MW of power and 28.5 MWh of capacity.

The higher energy density is enabled by new 648 Ah battery cells, with a volumetric energy density exceeding 440 Wh/L. A full liquid-cooling system and updated software maintain all cells within their optimal temperature range, reducing the system’s own energy consumption by around 10%, according to Sungrow. The company guarantees 10,000 cycles at 60% remaining capacity. State of charge is monitored at the rack level and synchronized across the system.

“We are seeing growing demand for stand-alone projects and a significant increase in co-location projects across Europe,” said Moritz Rolf, VP DACH at Sungrow. The DC coupling option is key to meeting this demand.

Paired with a PV system and Sungrow’s “1+X” central inverter, no separate PCS or medium-voltage switchgear is needed. The company estimates hardware and cabling savings for a 150 MWh project at around €1 million.

When connected on the AC side, the system includes an integrated PCS using silicon carbide MOSFETs. Maximum PCS efficiency is 99.5%, with a round-trip efficiency of 92%.

Fast commissioning

The PowerTitan 3.0 is delivered fully assembled and pre-configured. Commissioning is largely autonomous, taking about one hour per unit. A project can be connected to the grid in approximately 12 days, with no on-site parameterization required.

The system can also serve as an AC power source for plant certification tests. If a grid connection is not yet available, the battery can energize medium-voltage switchgear, inverters, and other equipment, simplifying logistics for commissioning and testing.

“Having completed the first stage of the energy transition—the expansion of renewables and their market integration—we are now entering the next phase: electrification, flexibility, and supply security,” said James Li, VP Europe of Sungrow, during a panel discussion.

Grid-forming capabilities were a central theme of the presentation. The system can provide short-circuit current with a ratio of 1.2, deliver instantaneous reserve power within five milliseconds, and contribute to harmonic attenuation, supporting grid strength and stability.

Antonio Arruebo, battery storage analyst at SolarPower Europe, highlighted the growing importance of these functions. Beyond frequency services, markets for instantaneous reserve, short-circuit current, and black-start capability are emerging across Europe. He stressed the need for early development of corresponding markets at EU and national levels, faster approval and certification processes for storage systems, and reduction of duplicate grid fees.

Key challenges

Discussions with event participants highlighted that, while the European battery storage market is developing positively overall, project financing remains a critical bottleneck. Highly leveraged projects are subject to intensive risk assessments by lenders, particularly regarding the valuation of future revenues from arbitrage and frequency markets. The long-term development of these markets is difficult to predict, directly affecting risk premiums and financing terms. Multi-bank financing structures appear to be becoming increasingly common.

From an investor perspective, the stability of revenue streams and technological risks are central. “The crucial factors are the resilience of the revenues and the likelihood of market mechanisms changing over time,” said Paula Renedo, Principal Engineer Director at Nuveen Infrastructure, during a panel discussion.

For battery storage, the balance between exposure to the stock market and contractually secured revenues is evolving. Creditworthiness of customers and technological reliability are gaining greater importance. “We look closely at proven technologies with robust operational experience, particularly regarding availability and degradation over the system’s lifespan,” Renedo added. Nuveen adopts conservative assumptions and engages external technical consultants to assess and mitigate these risks.

On pricing trends in the battery segment, and the Chinese government’s announcement requiring battery cell manufacturers to adopt “sustainable pricing,” Moritz Rolf noted that comparisons with recent photovoltaic module price trends are limited. PV modules have reached a high degree of commodification, whereas integrated large-scale storage systems involve numerous complex integration steps. As a result, prices equivalent to fractions of a cent per kilowatt, as seen in the module market, are not expected. After-sales service and local support remain critical for developers and operators. Sungrow currently employs around 800 people in Europe.

During testing at Estonia’s 100 MW Kiisa battery park, both EstLink 1 and EstLink 2 tripped, triggering the most severe disturbance to the regional power grid since desynchronization from the Russian electricity system. As a result, nearly 1 GW of capacity was lost within seconds. The park’s owner has since publicly pointed to the battery manufacturer.

From ESS News

A disturbance in Estonia’s power system on Jan. 20 forced both EstLink interconnections between Estonia and Finland offline, cutting roughly 1,000 MW of capacity, equivalent to about 20% of the Baltic region’s winter electricity load.

The shortfall was initially covered by support from the continental European grid, as the 500 MW AC connection between Poland and Lithuania operated at double its rated capacity to compensate. Later, reserve capacity within the Baltic states was deployed.

The oscillations were triggered by a 100 MW/200 MWh battery energy storage system in Kiisa, just south of Tallinn, one of the largest battery storage systems in the Baltics. The incident occurred during final grid connection testing, which caused the DC cables to trip.

The €100 million facility, developed by Estonian company Evecon in partnership with French firms Corsica Sole and Mirova, features 54 battery containers supplied by Nidec Conversion.

To continue reading, please visit our ESS News website. 

The Dutch start-up, founded by former Tesla leaders, is taking a novel approach to sodium-ion battery technology, optimizing it for integration with solar power plants. Its technology is set to be deployed for the first time in a Dutch solar-plus-storage project later this year.

From ESS News

Amsterdam-based Moonwatt has developed a new type of battery storage system based on sodium-ion NFPP chemistry, purpose-built for seamless solar hybridization. The system integrates battery enclosures with hybrid string inverters, enabling efficient DC-coupled solar-plus-storage integration.

The company gained attention in March 2025 when it raised $8.3 million in seed funding to accelerate growth. Moonwatt operates as an energy storage system integrator, designing, developing, and supplying string battery enclosures, hybrid string inverters, and battery management and site control systems, while sourcing sodium-ion cells globally.

“Initially, we’re sourcing them from Asia, but we aim to add American and European cell sourcing options as soon as they become available and create value for our customers,” Valentin Rota, co-founder and CCO of Moonwatt, said in an earlier interview with ESS News.

To continue reading, please visit our ESS News website.

A report from McKinsey and Company says the relative ease of building out solar projects means the U.S and Europe are likely to meet their end-of-decade deployment targets, despite current pipeline gaps of around 205 GW and 181 GW.

The US and Europe are likely to meet their 2030 solar targets despite current project pipelines being smaller than their end-of-decade targets, according to a report from global management consulting firm McKinsey and Company.

McKinsey’s “Tracking the energy transition: where are we now?” report analyzes the pathway of solar, wind and battery energy storage system (BESS) technologies towards the 2030 deployment targets set by China, the United States and the EU-27, Norway, Switzerland and the UK in Europe.

It says the US is currently around 254 GW away from its 2030 target while Europe is around 275 GW away. In contrast, China has already more than doubled its 2030 target.

Despite the US and Europe currently lacking enough announced capacity to meet their 2030s targets, by around 205 GW and 181 GW respectively, McKinsey's analysis says they are still likely to find this additional capacity and reach their end-of-decade thresholds thanks to the ease of building out solar.

“While it is easier to track project build-out for other clean energy technologies, data visibility for solar is more limited due to individual household use and ease of build-out,” McKinsey’s report explains. “For example, a consumer can install household solar in two months. This means that the announced capacity may be underestimated in this analysis.”

Diego Hernandez Diaz, a partner at McKinsey, told pv magazine that while core markets will continue their build out, further demand growth will also occur in less saturated core markets such as Poland. “The advantage of some of these elements is that the more nascent markets can have a better economic trade off and can be built in an economically pragmatic way,” he explained.

The report does acknowledge that this growth trajectory is not guaranteed, citing supply chain risks, tariffs, shifting policy focus and growing political uncertainty as factors that can slow down progress. Hernandez Diaz added there will likely be an effect from shifting regulation across the board.

“Perhaps more importantly, however, is that beyond any regulation, what we continue to see is that if the underlying economics work, then deployment accelerates,” he stated. “All major geographies covered in the report have the underlying fundamentals to support accretive deployment of further renewable energy sources.”

The report also notes that the battery energy storage system (BESS) pipeline is growing rapidly across China, the US and Europe, but remains behind what is needed to meet 2030 targets. McKinsey estimates around an additional 123 GW is required in China, 154 GW in the US and 221 GW in Europe.

The analysts says BESS remains the dominant question mark but can be sited, permitted, constructed, and interconnected far faster than technologies such as nuclear or gas with carbon, capture, utilization and storage (CCUS) contributing to its rapid growth in recent years.

The report attributes the rapid acceleration of BESS installation to a positive business case for both large-scale operators and households when paired with solar. “Load balancing is also becoming a popular source of revenue for battery operators,” the report adds. “Planning and integrating BESS with renewable rollout is critical if 2030 net-zero targets are to be met.”