arXiv subjects

Mohammad Panahazari

Publications and source records attributed to Mohammad Panahazari.

5 recordsLinked to original sources

arXiv2026

Evidence-Aligned Local Composition of Discrete Experts for Sequence Restoration

A document modeled as a discrete sequence of tokens can be thought of as being generated from a composition of texts from different domains; a README file, for example, moves between prose, code, and configuration. When such a document is corrupted and only frozen domain experts are available, restoring it requires deciding both what is missing and which expert to trust at each position, at test time and without region labels or a trained router. We introduce evidence-aligned local composition, which infers a soft, position-wise weighting over the experts from the marginal evidence of the corrupted observation under a given corruption model, estimating the evidence from the experts' own denoising losses and smoothing the weights across positions. Because the weighting is soft, it recovers a mixture when the true composition is mixed and concentrates on one expert when that suffices. Across a categorical simulator, byte-level experts, and experts fine-tuned from a $1.3$B discrete flow-matching model, the inferred weights track the true regions at $0.85$ field accuracy on naturally mixed scientific documents, and at $0.98$ on constructed mixtures whose regions are lexically disjoint. Restoration improves over a single global weight when the experts are genuinely distinct and reduces to it when they converge, tracking a measure of expert separation.

cs.AI↗

arXiv2023

A New Market-Based Framework for Increasing Responsive Loads In Distribution Systems

Regarding the pervasive application of information and telecommunication technologies in the power distribution industry, responsive loads (RLs) have been widely employed in the operation of distribution and transmission systems. The utilization of these loads in the competitive environment of the power market has led to a decrease in costs and an increase in the flexibility of the distribution system and, consequently, the power system. This paper presents a framework for the competitive presence of RLs in local markets. The technical cooperation method of the Distribution System Operator (DSO) and Transmission System Operator (TSO), the persuasion mechanism of DSOs, and financial signals for getting and increasing the participation of consumers are represented based on local markets and market clearing mechanisms.

eess.SY↗

arXiv2023

Localized Load Reduction Market Development Considering Network Constraints

With the development of the smart grid concept and the increasing expansion of advanced communication and measurement equipment, consumers can actively participate in the power system operation. The intelligent use of these facilities greatly helps the power system entities to achieve their objectives more efficiently and less expensively. As a beneficial facility, the market mechanism has proven to be a solution to various power system challenges. Furthermore, distributed and localized solutions have shown to be helpful in both reducing operation costs and accelerating the execution of the programs. In a generation shortage condition, to prevent unwanted load curtailment and wholesale market price spikes, utilities can get consumers' help to reduce the load in return for payments. This paper proposes a localized load reduction market model in the distribution system, in which consumers bid for their participation rate at the corresponding prices. Then, a market optimization problem will be solved by considering the technical constraints of the network through the use of Genetic Algorithm (GA). The paper then shows that utilizing the proposed model reduces operation costs.

eess.SY↗

arXiv2023

Improved Dual-Output Step-Down Soft-Switching Current-Fed Push-Pull DC-DC Converter

Multi-port DC-DC converters are gaining more significance in modern power system environments by enabling the connection of multiple renewable energy sources, so the efficient operation of these converters is paramount. Soft switching methods increase efficiency in DC-DC converters and increase the reliability and lifespan of devices by relieving stress on components. This paper proposes a method for soft-switching of a dual-output step-down current-fed full-bridge push-pull DC-DC converter. The converter enables two independent outputs to supply different loads. The topology achieves zero-current switching on the primary side and zero-voltage switching on the secondary side, eliminating the need for active-clamp circuits and passive snubbers to absorb surge voltage. This reduces switching losses and lower voltage and current stresses on power electronic devices. The paper thoroughly investigates the proposed converter's operation principle, control strategy, and characteristics. Equations for the voltage and current of all components are derived, and the conditions for achieving soft switching are calculated. Simulation results in EMTDC/PSCAD software validate the accuracy of the proposed method.

eess.SY↗

arXiv2023

A Hybrid Optimization and Deep Learning Algorithm for Cyber-resilient DER Control

With the proliferation of distributed energy resources (DERs) in the distribution grid, it is a challenge to effectively control a large number of DERs resilient to the communication and security disruptions, as well as to provide the online grid services, such as voltage regulation and virtual power plant (VPP) dispatch. To this end, a hybrid feedback-based optimization algorithm along with deep learning forecasting technique is proposed to specifically address the cyber-related issues. The online decentralized feedback-based DER optimization control requires timely, accurate voltage measurement from the grid. However, in practice such information may not be received by the control center or even be corrupted. Therefore, the long short-term memory (LSTM) deep learning algorithm is employed to forecast delayed/missed/attacked messages with high accuracy. The IEEE 37-node feeder with high penetration of PV systems is used to validate the efficiency of the proposed hybrid algorithm. The results show that 1) the LSTM-forecasted lost voltage can effectively improve the performance of the DER control algorithm in the practical cyber-physical architecture; and 2) the LSTM forecasting strategy outperforms other strategies of using previous message and skipping dual parameter update.

eess.SY↗