arXiv subjects

Gustavo Valverde

Publications and source records attributed to Gustavo Valverde.

8 recordsLinked to original sources

arXiv2026

Forced Oscillations in Power Systems Induced by Data Centers Hosting AI Workloads

Power swings in large Data Centers (DTCs) running Artificial Intelligence (AI) workloads can excite poorly damped modes in power systems. The resulting forced oscillations can lead to flicker, equipment disconnection, or blackouts. This paper investigates the risks of such load fluctuations for different system strengths and damping conditions. Using an analytical approach based on transfer functions, we identify critical DTC locations in the power grid at which load fluctuations could induce the largest forced oscillations and further characterize the harmonic spectrum of the resulting system response. Depending on the frequency and magnitude of the DTC load fluctuations, forced oscillations can become unbounded. The underlying instabilities are classified into saddle-node bifurcations of the forced periodic response and impasse-surface encounters, using Floquet multipliers and the minimum singular value of the algebraic Jacobian. Furthermore, the impact of different duty cycles and harmonic components beyond the fundamental oscillation frequency in square-wave load profiles is analyzed. Finally, the interaction of two oscillating DTCs is investigated for different locations and forcing frequencies, considering both synchronized and unsynchronized operation. The findings can help system operators to define new regulations on the maximum load fluctuations permitted for DTC facilities at specific grid locations, without negatively affecting the stability and operation of the system.

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arXiv2026

Comparative Assessment of Frequency Scans using EMT and RMS Models

Frequency scans of inverter and grid impedances are crucial for assessing small-signal stability and system strength in inverter-dominated power systems. This paper compares frequency-scan results for several generating units, including a synchronous generator, grid-following, and grid-forming inverters, using fully dq electromagnetic transient and root-mean-square (RMS) models in Simulink. The scans are performed for the same device rating and operating point. Frequency scans and time-domain simulations show that the RMS models are valid only at low frequencies. We find that the current-controlled grid-forming inverter is more difficult to represent in RMS than the voltage-controlled grid-forming inverter. However, including the inner voltage-control loops improves the accuracy of the RMS representation. The paper also investigates the influence of generator and grid impedance on the total system impedance seen from the point of common coupling and relates the oscillatory modes and zeros of the system to peaks and dips in the first and second singular values of the system impedance, respectively.

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arXiv2026

Mitigating Forced Oscillations in Power Systems via Data-Enabled Predictive Control

Sustained forced oscillations in power systems, driven by large cyclic loads such as data centers, pose a challenge to conventional power system stabilizers (PSSs), which rely on fixed tuned parameters and limited adaptability. This paper investigates the use of Data-Enabled Predictive Control (DeePC) as a data-driven alternative for damping such oscillations. DeePC constructs control actions directly from measured trajectories without requiring an explicit system model, enabling adaptation to changing operating conditions. We evaluate the performance of DeePC on a multi-machine two-area system subject to forced oscillations and compare it against a conventional PSS. The study examines the impact of different input-output configurations and the role of representative historical data in the Hankel matrix construction. Results show that DeePC can achieve superior damping. However, its effectiveness depends critically on the quality and representativeness of the underlying dataset. These findings highlight the potential of data-driven predictive control to complement or outperform conventional stabilizers in modern power systems with evolving and uncertain dynamics.

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arXiv2026

Loadability Limits Under Periodic Load Forcing

The static loadability limit, defined as the demand at which the equilibrium equations lose their solution, is the standard basis for interconnection screening of large new loads. This letter shows that when part of the demand varies periodically, as for data-center loads, the steady state is a forced periodic orbit whose loadability limit differs from the static one. The classical optimization argument is extended directly from equilibria to fixed points of the period map. At the limit, the monodromy matrix acquires a Floquet multiplier at +1, so the generic instability is a cyclic fold of the orbit rather than a saddle-node of equilibria. The limit is therefore a function of the forcing frequency, which no static computation can capture. Additionally, with the network Jacobian turning singular along the cycle, singularity-induced instability is extended to orbits. On a four-bus test system, a static margin of 2.5 p.u. shrinks to 0.53 p.u. near the swing frequency, the instability mechanism switches from voltage collapse to a rotor-angle fold, and cold starts fail at amplitudes where the orbit still exists. A static analysis reproduces none of these effects.

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arXiv2026

TSO-DSO Coordination for Flexibility Management Across Voltage Levels

Several sources of flexibility in transmission and, especially, distribution networks are being unlocked by advances in information and communication technologies, aggregators, and new flexibility markets. However, maximizing benefits for both transmission and distribution system operators in a coordinated way requires new algorithms, modeling tools, and modernization of regulatory frameworks. Such approaches must account for uncertainties, the physical and operational constraints of flexibility providers and the grid itself, constraints on information exchange, and scalability, including computational requirements and time constraints. Given the diverse contexts and jurisdictions around the world, there is no single recipe for achieving coordination, but important trends and shared challenges are emerging. This paper surveys the complexities of coordination from technical, market, and technological perspectives, and outlines current practices, proposed approaches, and future research directions to effectively manage, coordinate, model, and leverage flexibility across voltage levels.

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arXiv2026

Revisiting Power System Stabilizers with Increased Inverter-Based Generation: A Case Study

As power systems evolve with increasing production from Inverter-Based Resources (IBRs), their underlying dynamics are undergoing significant changes that can jeopardize system operation, leading to poorly damped oscillations or small-signal rotor angle instability. In this work, we investigate whether Power System Stabilizer (PSS) setting adjustments can effectively restore system stability and provide adequate damping in systems with increased IBR penetration, using the benchmark Kundur Two-Area System as a case study. Specifically, we evaluate the model-based Residues and P-Vref PSS tuning methods to examine their effectiveness under evolving grid conditions. Our findings indicate that the effectiveness of these tuning methods is not guaranteed, particularly when coordination is limited. Consequently, our case study motivates local and adaptive online PSS tuning methods.

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arXiv2026

Residential Peak Load Reduction via Direct Load Control under Limited Information

Thermostatically controlled loads and electric vehicles offer flexibility to reduce power peaks in low-voltage distribution networks. This flexibility can be maximized if the devices are coordinated centrally, given some level of information about the controlled devices. In this paper, we propose novel optimization-based control schemes with prediction capabilities that utilize limited information from heat pumps, electric water heaters, and electric vehicles. The objective is to flatten the total load curve seen by the distribution transformer by restricting the times at which the available flexible loads are allowed to operate, subject to the flexibility constraints of the loads to preserve customers' comfort. The original scheme was tested in a real-world setup, considering both winter and summer days. The pilot results confirmed the technical feasibility but also informed the design of an improved version of the controller. Computer simulations using the adjusted controller show that, compared to the original formulation, the improved scheme achieves greater peak reductions in summer. Additionally, comparisons were made with an ideal controller, which assumes perfect knowledge of the inflexible load profile, the models of the controlled devices, the hot water and space heating demand, and future electric vehicle charging sessions. The proposed scheme with limited information achieves almost half of the potential average daily peak reduction that the ideal controller with perfect knowledge would achieve.

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arXiv2021

Unsupervised Disaggregation of Water Heater Load from Smart Meter Data Processing

In the residential sector, electric water heaters are appliances with a relatively high power consumption and a significant thermal inertia, which is particularly suitable for Demand Response schemes. The success of efficient DR schemes via the control of water heaters presupposes an accurate estimate of their power demand at each instant. Although the load of water heaters is rarely directly measured, a large penetration of Smart Meters (SMs) in distribution grids enables to indirectly infer this information on a large scale via load disaggregation. For that purpose, a considerable number of Non-Intrusive Load Monitoring (NILM) approaches are suggested in the literature. However, they require data streams at a time resolution in the range of one second or higher, which is not realistic for standard SMs. Hence, this paper proposes an unsupervised approach to detect and disaggregate the load profile of water heaters from standard SM data with a time resolution in the minute range. Evaluated on multiple real loads with sub-metering, the proposed approach achieves a Normalized Mean Absolute Error (NMAE) lower than 2% and a precision generally higher than 92% with time resolutions between 5 and 15 minutes.

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