US-India CollAborative For Smart DiStribution System WIth STorage

Publications(U.S.)

Papers Published/Accepted in Conference Proceedings

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Abstract:Renewable based isolated DC microgrids(IDCMG) faces reliability issues due to intermittent nature of sources. Hence non-renewable source (diesel generators, gas generators, etc) are generally used to increase the reliability of isolated DC microgrids. Power control and management techniques plays crucial role in achieving optimal utilization of renewable and non-renewable sources. A power control algorithm (PCA) is developed to attain effective energy management between renewable and non-renewable sources by utilizing the hybrid storage systems (battery and supercapacitor). Proposed strategy also covers the extreme scenarios of battery storage and IDCMG. Strategy is simple, reliable and efficient in utilizing the renewable source power. Strategy also improves the life time of battery by diverting high frequency power oscillations to supercapacitor. Simulation of proposed scheme is executed on IDCMG in real time simulator RSCAD/RTDS platform to validate the effectiveness.

Abstract: In an active distribution network with increasing penetration of Distributed generators (DGs), it is critical to model DGs and keep the model updated for analysis. However, the generator parameter provided by the manufacturer changes because of aging and errors. Modeling parameters are typically provided by manufacturers and routinely adjusted with offline field testing. With availability of the high resolution real time measurement data such as μ-PMUs, parameter can be estimated without taking generator offline. Model validation and calibration allows non-intrusive estimation of the parameters in distributed generators. This work aims at estimating the state and transient reactances of a distributed synchronous generator based combined heat and power generation unit connected to a medium voltage distribution network. The state and parameter estimation is performed on-line using phasor data collected by micro-phasor measurement unit (μ-PMU) connected at the terminals of the machine. A constrained least-squares algorithm is used in recursion to track the changes in the state and parameter of the synchronous generator. The parameters are estimated considering different switching and dynamic events like faults, islanding, and load/capacitor switching. Results show the superiority of the proposed approach.

Abstract:—Demand response analysis in smart grid deployment substantiated itself as an important research area in recent few years. Two-way communication between utility and users makes peak load reduction feasible by delaying the operation of deferrable appliances. Flexible appliance rescheduling is preferred to the users compared to traditional load curtailment. Again, if users’ preferences are accounted into appliance transferring process, then customers concede a little discomfort to help the utility in peak reduction. This paper presents a novel Utility-User Cooperative Algorithm (UUCA) to lower total electricity cost and gross peak demand while preserving users’ privacy and preferences. Main driving force in UUCA to motivate the consumers is a new cost function for their flexible appliances. As a result, utility will experience low peak and due to electricity cost decrement, users will get reduced bill. However, to maintain privacy, the behaviors of one customer have not be revealed either to other customers or to the central utility. To justify the effectiveness, UUCA is executed separately on residential, commercial and industrial customers of a distribution grid. Harmony search optimization technique has proved itself superior compared to other heuristic search techniques to prove efficacy of UUCA.

Abstract:This paper investigates the performance assessment of droop controlled converters in a low inertia, low voltage DC microgrid scenario. It employs a generalized DC distribution network consisting of both current-controlled and voltage-controlled voltage source converters and a mix of constant impedance, constant current and constant power loads. Since in large distribution networks, lack of inertia is the cause of instability, virtual impedance based methods and capacitor control techniques have been proposed. A RC-based droop control strategy is employed in this work in order to impart inertia to the system thereby improving the transient performance of the network. The converters considered are both grid-feeding and grid-forming in order to analyze the response in the presence of dissimilar electrical energy sources. The grid-feeding converters, both voltage and current-controlled, are interconnected via communication layer and are governed by the consensus laws for multi-agent systems. The networked control systems aids in achieving proper load current sharing and desired voltage regulation. This is essential for the operation of critical loads. The study presents a comparative assessment of the response of RC-droop and conventional droop in the varied microgrid conditions. The cyber-physical system is modeled in MATLAB/Simulink and tested against various operating situations and cyber adversities to test the efficacy of the control law.

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Abstract:Rural electrification is important to mitigate energy poverty and improve human development in remote unelectrified regions. Optimal planning and designing of the microgrid architectures are required for providing electricity access. DC microgrid architectures with static generation and load demand have some limitations with respect to the planning side. Time-based dynamic load demand and generation gives an insight into a more practical and real-time approach. In this paper, a detailed distribution loss analysis of both centralized and distributed microgrid architectures with dynamic load and generation profiles is presented. The distributed architecture consists of individual household consumers that form independent nanogrids, which can operate in both standalone and integrated manner to make the microgrid scalable. The centralized architecture comprises of distributed load with centralized generation and storage. Both centralized and distributed systems with ring and radial orientations are considered and their performance is evaluated using a modified Newton Raphson method for DC systems. A comparative distribution loss analysis with various conductor sizes and voltage levels shows that the distributed ring architecture is significantly advantageous based on low distribution losses, high efficiency, and low voltage drop. It offers an additional feature of scalability and low capital cost. The microgrid architectures can be tested for any region by using the real-time solar irradiation data, weather conditions, and the dynamic load demand of that community.

Abstract:With enhanced automation and control in active power distribution compared to the legacy system, interaction between transmission and distribution systems has become complex and need to be analyzed. Resiliency refers to ability of the system to continue serving energy to the critic loads even with extreme contingencies, which depends on existing automation, control, energy resources and network topology in the transmission and distribution system. Resiliency analysis for enabling multiple alternatives requires testbed for planning and operational decision. Testbeds having various capabilities have been developed at various institutions, but no single existing testbed can offer full scalability while simultaneously meeting high fidelity requirements for resiliency experimentation. Co-simulating testbed assets can offer a scalable experimentation platform that can be leveraged for verification and validation. As a first step in this direction, two real time simulators, Real Time Digital Simulator (RTDS) and OPAL-RT have been interfaced using VILLAS framework. VILLASnode provides a gateway for processing and forwarding simulated data between real-time simulators. At the core, it acts like a client/server application to connect simulation equipment and software. As an illustrative use case, the resiliency of a transmission-distribution test system is simulated and the results are analyzed. A 179 bus WECC transmission system is developed using OPAL-RT/ HYPERSIM and a modified IEEE 13 node feeder system is built in RTDS/ RSCAD and interfaced for resiliency analysis.

Abstract:High penetration of plug-in electric vehicles (PEVs) can potentially put the utility assets such as transformer under overload stress causing decrease in their lifetime. The decrease in PV and battery energy storage system (BESS) prices has made them viable solutions to mitigate this situation. In this paper, the economic aspect of their optimal coordination is studied to assess transformer hottest spot temperature (HST) and loss of life. Monte Carlo simulation is employed to provide synthetic data of PEVs load in a residential complex and model their stochastic behavior. For load, temperature, energy price and PV generation, real data for City of College Station, Texas, USA in 2018 is acquired and a case study is developed for one year. The results illustrate using BESS and PV is economically effective and mitigates distribution transformer loss of life.

Abstract:Energy storage (ES) is becoming used more and more in power distribution system due to the decrease in the cost. ES can be stationary inside buildings or mobile as a part of plug-in electric vehicles (PEV). The use of ES have merits such as peak shaving, load shifting, and backup power supply in the case of loss of power from the grid. The mobile ES poses challenges to the system since the connection location and time may be random. In this paper, the impacts of the stationary and mobile ES on the distribution transformers loss of life are quantified employing a probabilistic approach. Monte Carlo simulation is utilized to model the stochastic behavior of PEVs. For residential demand, ambient temperature and photovoltaic (PV) generation real data from College Station, Texas is used. Using the historical data of one year in this area, the impacts of different ES penetration level in the presence of PEV and PV are studied. This paper provides a better understanding of the negative effects of PEVs on transformers aging and how ES can be employed to mitigate the loss-of-life risk. 

Abstract:The complexity and vulnerability of the bulk power system are well known. Among all the factors that are important for maintaining the continuity and security of the power system, the importance of the power system operator lies at the top in the hierarchy. It is important to ascertain that the operator has the critical tools, knowledge, access to training, cognitive and technical skills and the experience for extreme contingency condition that may arise. In this paper, decision making ability of power system operators in extreme events with and without advanced power system tools has been analyzed by relating to their measured cognitive flexibility.

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Abstract:High penetration of renewable energy (RE) is highly expected for sustainable green power system. Photovoltaic (PV) is the most suitable form of renewable generation in present distribution system. However, in an existing feeder, the amount of PV accommodation is limited because of utility-established acceptable voltage limit, voltage unbalance, transformer rating, line thermal overloading limit, regulation equipment, protection co-ordination, feeder configuration, load profile and more. It is important for feeder operation and planning to calculate the amount of PV that can be hosted inside an existing feeder subject to satisfy voltage limit, thermal limit, and protection criteria - often referred to as feeder hosting capacity (FHC) or PV hosting capacity. PV has uncertainty due to inherent nature and further, PV ramp rate is much faster than regulator response time. Therefore, it is common practice to consider worst-case scenario. Usually FHC is a complex power system optimization problem using steady state calculations. It is not possible to explore all possible scenarios in a practical timeframe. Therefore, multiple pre-defined scenarios are generated from random Monte Carlo simulation. However, the authors propose a swarm based intelligent scenario (location) selection from local and global search experiences for faster and better solution. Simulation results show effectiveness of the proposed method.

Abstract:This paper studies the problem of \em answering Why-questions for graph pattern queries. Given a query Q, its answers $Q(G)$ in a graph G, and an exemplar $\E$ that describes desired answers, it aims to compute a query rewrite $Q'$, such that $Q'(G)$ incorporates relevant entities and excludes irrelevant ones wrt $\E$ under a closeness measure. (1) We characterize the problem by \em Q-Chase. It rewrites Q by applying a sequence of applicable operators guided by $\E$, and backtracks to derive optimal query rewrite. (2) We develop feasible Q-Chase-based algorithms, from anytime solutions to fixed-parameter approximations to compute query rewrites. These algorithms implement Q-Chase by detecting picky operators at run time, which discriminately enforce $\E$ to retain answers that are closer to exemplars, and effectively prune both operators and irrelevant matches, by consulting a cache of star patterns (called \em star views ). Using real-world graphs, we experimentally verify the efficiency and effectiveness of \qchase techniques and their applications.

Abstract:Internet of Things (IoT) technologies have experienced an unprecedented growth over the last decade due to their wide applicability and low overall costs. These same factors have also allowed IoT deployments to transition into industrial environments which are expected to meet high reliability requirements. These technological-base shifts have raised operational (safety) concerns among researchers, which have been further fueled by high-profile cyber incidents that have exposed vulnerabilities in field devices. Although, multiple IoT cyber security issues are being actively researched, a compelling issue is to identify threats associated with cross-domain devices. A cross-domain vulnerability is any such vulnerability that can cause other non-IT system to experience unintended consequences.

Abstract:In this paper, a review of different frequency control methods for microgrid is presented. Also, the variables considered for choosing an optimal size of energy storage associated with renewable resources are discussed. Conditions of droop control technique used for inverters operating in parallel are analyzed. Simulation investigations using MATLAB/Simulink are conducted to demonstrate the power sharing between inverters and other distributed generators in the microgrids.

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Abstract:In this paper, contingency ranking (CR) method is introduced into the reliability evaluation of line switching operations as a pre-selection method to provide quick and basic guidance on line categorization. Two case studies were conducted on RTS and IEEE 118-bus system to test the efficiency of the method. Both show reasonable accuracy in picking up critical lines and a drastic improvement of calculation speed.

Abstract:This paper presents short term load forecasting using multi-variable linear regression (MLR) for big data. Load forecasting is very important for planning, operation, resource scheduling and so on in power system. Total electric demand dynamically changes in a power system and mainly depends on temperature, humidity, wind speed, human nature, regular activities, events, etc. input variables. For the help of sensors and data science, enough historical and future input data with good accuracy are easily available. On the other hand, linear regression is a proven method, widely used in industries for forecasting. It is deterministic and robust. However, it is slow for big data because it needs large size matrix operations. In this paper, linear regression is formulated for small number of variables with big data and multi-core parallel processing is applied in all matrix operations that allow unlimited historical big data and unlimited scenarios in acceptable execution time limit. Mean absolute percent error is 3.99% of real field recorded data shown in Simulation and Result section.


UI-ASSIST COLLABORATOR-India
UI-ASSIST COLLABORATOR-US