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S. Gokul Krishnan

Publications and source records attributed to S. Gokul Krishnan.

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HyMGP: A Customized MILP-Based Tool for Techno-Economic Planning of Islanded Microgrids

This paper presents a customized microgrid planning algorithm and tool, HyMGP, for remote sites in arid regions, which is formulated as a Mixed Integer Linear Programming (MILP) problem. HyMGP is compared with HOMER Pro to evaluate its performance in optimizing the sizing of microgrid components, including photovoltaic panels (PVs), vertical axis wind turbines (VAWTs), and battery energy storage systems (BESS), for remote and off-grid applications. The study focuses on a standalone microgrid in the Saudi Arabia, considering high solar irradiance, limited wind availability, and a constant load profile composed of continuous cathodic protection and daytime cooling. In the simulation environment, comparisons with HOMER solutions demonstrate the advantages of HyMGP, which provides optimal and more flexible solutions by allowing user-defined component specifications and strictly enforcing all constraints. Further analysis shows that incorporating wind turbines reduces the Net Present Cost (NPC) by decreasing the required PV and battery capacities. Increasing battery autonomy leads to a higher NPC in both PV-only and hybrid systems due to the need for larger storage. Finally, lithium iron phosphate (Li-ion LFP) batteries are found to be more cost effective than lead acid, offering lower NPCs due to their longer lifespan, deeper discharge capability, and fewer replacement cycles.

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Impact Assessment of Heterogeneous Grid Support Functions in Smart Inverter Deployments

The decarbonization of the energy sector has led to a significant high penetration of distributed energy resources (DERs), particularly photovoltaic (PV) systems, in low-voltage (LV) distribution networks. To maintain grid stability, recent standards (e.g., IEEE 1547-2018) mandate DERs to provide grid-support functionalities through smart inverters (SIs), which typically operate autonomously based on local measurements. However, as DER penetration increases, uncoordinated control modes of SIs can lead to adverse interactions, compromising system efficiency, voltage regulation, and overall stability. While previous studies have demonstrated the benefits of coordinated inverter control and optimal dispatch strategies, the system-wide impacts of heterogeneous SI groups operating under different control modes remain largely unexamined. This paper addresses this gap by assessing the dynamic interactions among multiple SI groups with varying control strategies, namely: Constant Power Factor (CPF), Volt-VAR, and Volt-Watt modes. Furthermore, the analysis covers both resistive and inductive feeder types. The validation is performed using a real-time setup. The CIRGE low-voltage (LV) distribution network is simulated in the Opal-RT platform as the test network, enabling realistic and high-fidelity evaluation of SI control interactions under practical grid conditions.

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Real-Time Co-Simulation for DC Microgrid Energy Management with Communication Delays

The growing integration of renewable energy sources (RESs) in modern power systems has intensified the need for resilient and efficient microgrid solutions. DC microgrids have gained prominence due to their reduced conversion losses, simplified interfacing with DC-based RESs, and improved reliability. To manage the inherent variability of RESs and ensure stable operation, energy management systems (EMS) have become essential. While various EMS algorithms have been proposed and validated using real-time simulation platforms, most assume ideal communication conditions or rely on simplified network models, overlooking the impact of realistic communication delays on EMS performance. This paper presents a novel real-time cyber-physical system (CPS) testbed for evaluating EMS performance in DC microgrids under realistic communication delays. The proposed testbed integrates a DC microgrid modeled in OPAL-RT with an EMS controller implemented on a Raspberry Pi (RPi). The communication network is emulated using EXataCPS, enabling the exchange of actual power system traffic and the replication of realistic latency conditions. This comprehensive setup captures the interplay between power system dynamics, EMS control, and communication network behavior.

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VAE-GAN Based Price Manipulation in Coordinated Local Energy Markets

This paper introduces a model for coordinating prosumers with heterogeneous distributed energy resources (DERs), participating in the local energy market (LEM) that interacts with the market-clearing entity. The proposed LEM scheme utilizes a data-driven, model-free reinforcement learning approach based on the multi-agent deep deterministic policy gradient (MADDPG) framework, enabling prosumers to make real-time decisions on whether to buy, sell, or refrain from any action while facilitating efficient coordination for optimal energy trading in a dynamic market. In addition, we investigate a price manipulation strategy using a variational auto encoder-generative adversarial network (VAE-GAN) model, which allows utilities to adjust price signals in a way that induces financial losses for the prosumers. Our results show that under adversarial pricing, heterogeneous prosumer groups, particularly those lacking generation capabilities, incur financial losses. The same outcome holds across LEMs of different sizes. As the market size increases, trading stabilizes and fairness improves through emergent cooperation among agents.

cs.LG

A Distributed Local Energy Market Clearing Framework Using a Two-Loop ADMM Method

The diversity of prosumers' resources in energy communities can provide significant technical and economic benefits to both prosumers and the distribution system operator (DSO). To maximize these benefits, a coordination framework is required to address all techno-economic constraints as well as the objectives of all agents. This paper presents a fully distributed market-clearing scheme to coordinate the strategies of agents within a local energy community. In the proposed framework, prosumers, the DSO, and the local market operator (LMO) are the participating agents. The framework addresses the preferences and techno-economic constraints of all actors while preserving their privacy. The proposed model is based on a modified alternating direction method of multipliers (ADMM) method with two outer and inner loops; the outer loop models the interactions between the LMO and prosumers, while the inner loop addresses the interactions between the LMO and the DSO. The model is demonstrated on IEEE-69bus test network, showcasing its effectiveness from various perspectives.

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