Papers by Bhuvana Ramachandran
Journal of Power and Energy Engineering
Predicting wind speed is a complex task that involves analyzing various meteorological factors su... more Predicting wind speed is a complex task that involves analyzing various meteorological factors such as temperature, humidity, atmospheric pressure, and topography. There are different approaches that can be used to predict wind speed, and a hybrid optimization approach is one of them. In this paper, the hybrid optimization approach combines a multiple linear regression approach with an optimization technique to achieve better results. In the context of wind speed prediction, this hybrid optimization approach can be used to improve the accuracy of existing prediction models. Here, a Grey Wolf Optimizer based Wind Speed Prediction (GWO-WSP) method is proposed. This approach is tested on the 2016, 2017, 2018, and 2019 Raw Data files from the Great Lakes Environmental Research Laboratories and the National Oceanic and Atmospheric Administration's (GLERL-NOAA) Chicago Metadata Archive. The test results show that the implementation is successful and the approach yields accurate and feasible results. The computation time for execution of the algorithm is also superior compared to the existing methods in literature.
Advancement of Women in Engineering: Past, Present and Future
2020 ASEE North Central Section conference, Mar 27, 2020
International Journal of Electronics and Electrical Engineering, 2020
The promotion of energy internet causes external information to directly or indirectly affect pow... more The promotion of energy internet causes external information to directly or indirectly affect power system control decisions through various business approaches. The interaction mechanism between power network and information network becomes increasingly complex. Modern power systems become more prone to cyber-attacks and physical attacks because of the high integration of information layer and physical layer. This paper provides an insight into the impacts of cyber and physical attacks on power systems, where the attacks are modeled in the form of mathematical (optimization) equations representing the attacks. Moreover, the cyber and physical attacks are modeled in the form of Mixed Integer Linear Programming (MILP) problem. The authors have simulated cyber-attack on transmission lines and cyber-physical attack on both transmission lines and loads. The MILP problem is solved by commercial solver, CPLEX. A case study on a modified IEEE 14 bus test system is considered to demonstrate...
The implication of renewables, BES, and EV's in a sustainable power system
A few decades ago, the thought of using solar panels to save money on the power bill was inexiste... more A few decades ago, the thought of using solar panels to save money on the power bill was inexistent. However, as advancements in renewable energy technology continue, adding renewables to one's home or business is becoming more and more beneficial. The prices of renewables such as solar panels and wind turbines has decreased drastically over the past couple decades. This is shifting their use from being not only beneficial to the environment, but to the wallet as well. This research is focused primarily on the monetary perquisites resulting from the use of renewables. That is, how much is the installation cost, how long is the payback period, and how much of a profit may result.
Real-time simulation of demand side management and vehicle to grid power flow in a smart distribution grid
2017 IEEE International Conference on Electro Information Technology (EIT)
The price per kilowatt-hour of energy delivered by the electric power utility varies as the total... more The price per kilowatt-hour of energy delivered by the electric power utility varies as the total power demand supplied to the region it serves throughout the day. To save money and protect power system equipment, it may be necessary to schedule the energy consumed during these periods of high/critical demand and higher pricing. In this project, a number of demand-side management strategies (DSM) are tested and compared on a modified IEEE 37-bus distribution feeder model in real time using an OPAL-RT real time simulator. This study focuses on the use of battery electric vehicles (BEVs) as energy storage components of a smart-grid. A stochastic model is used to predict the location of BEVs and their state of charge (SOC) over a 24-hour period. During the high demand periods or fault conditions, a number of BEV users may connect to the grid and supply power by using vehicle-to-grid (V2G) power flow. This number depends on the level of consumer interest in participating in V2G service as well as the location and SOC of each vehicle. The results show that a power utility will benefit by offering incentives to consumers with BEVs that are available to supply power to the grid.
An Innovative Deep Learning Approach Applied to Transient Stability Assessment of Power Systems
2020 Clemson University Power Systems Conference (PSC)
Secure and reliable operation of a power system is exceedingly important for efficiency in power ... more Secure and reliable operation of a power system is exceedingly important for efficiency in power systems and everyday life. Transient stability is a large obstacle that, if assessed properly, can help maintain this secure and reliable operation. Transient stability studies have created a big data issue and recently data mining and machine learning techniques have been broadly applied to transient stability assessment (TSA). During the operation of a power system disturbances such as, cut-off loads, short-circuit faults, etc., may occur and it is crucial to be able to quickly and accurately determine if the power system is stable after these disturbances. With the growing consumer demand for reliable power, many methods have been proposed for fast and accurate transient stability assessment, but these traditional methods such as, extended area method, direct method, and time domain simulation do not provide the most optimal solutions. The goal of TSA is to fulfill the needs of speed and capacity, calculation accuracy, and easy online calculation. In this paper, an innovative deep learning method is applied for TSA. The approach presented in this paper is tested on a 19-bus system. Simulation results illustrate the effectiveness and practicability of the proposed strategy.
Power management in a microgrid using Teaching Learning Based Optimization Algorithm
SoutheastCon 2017, 2017
As renewable sources are being added to the grid to meet the electricity demand of users everywhe... more As renewable sources are being added to the grid to meet the electricity demand of users everywhere, there is an optimization problem floating in the mix that, without being attended to, could waste not only power, but money as well. This problem, typically involving systems with two or more renewable energy installations, is known as power management and pertains to the appropriate time for power outputs of specified renewable sources. To maximize a power systems efficiency, it is necessary to monitor and regulate the output of each renewable source based off of the demand, and if a surplus occurs, then the power management is based of which renewable is most cost efficient to use first, second, etc. In this paper the problem of power management will be introduced with 6 separate types of energy sources, each with their own set of costs and constraints. The problem will then be analyzed and solved using a new, yet reliable algorithm.
Smart Coordination Approach for Power Management and Loss Minimization in Distribution Networks with PEV Penetration Based on Real Time Pricing
The impact of Plug in Electric Vehicles (PEV) will be most significantly felt by the electric pow... more The impact of Plug in Electric Vehicles (PEV) will be most significantly felt by the electric power distribution networks, and specifically by distribution transformers that exist on each neighborhood block and cul-de-sac as customers charge their PEVs. That impact is unlikely to be positive. Since PEV adoption is initially expected to cluster in neighborhoods where demand for PEVs is strongest, the new load may overload transformers, sap much-needed distribution capacity and also increase distribution network losses. Hence, the national goal of putting one million PEVs on the road by 2015 could easily impose a severe burden on the distribution network. Whether PEVs will help or hinder electricity provision will depend on how frequently and at what times the customers charge their vehicles. This behavior will be driven in part by the rate structures that are offered by utilities, as well as the price responsiveness of PEV owners to those rate structures. In this chapter, we propose ...
Economic Operation of a Microgrid Considering Uncertainties
SoutheastCon 2018, 2018
This research presents economic operation of distributed energy resources in an islanded microgri... more This research presents economic operation of distributed energy resources in an islanded microgrid considering uncertainties associated with forecasting error of load, wind, and solar series. The forecasting is performed using artificial neural networks (ANN). A distribution of the forecasting errors was fitted. A discrete set of probabilities was used to create a set of possible scenarios representing possible deviations from the forecasted outputs of load, wind, and solar. The problem of economical operation of the electric grid was formulated as a stochastic optimization model to minimize expected total cost (ETC). The ETC expression consists of (a) expected operating cost of the generators, which includes linearized fuel cost and startup costs (b) expected operating costs of energy storage system and (c) expected interruption cost. Load demand data from New England area was tested to study the efficacy of this approach. A test system consisting of 10 conventional generators, 100...
Impact of Targeted Cyber Attacks on Electrical Power Systems
This paper formulates targeted and coordinated attacks on an electrical power system infrastructu... more This paper formulates targeted and coordinated attacks on an electrical power system infrastructure as an optimization problem to (a) investigate the impacts of such attacks on the electric power grid and (b) to study the extent of damages to the grid depending on attacker’s resources and level of protection employed in the grid. In this research, we consider the coordinated load redistribution (LR) attack, which is a variant of false data injection attack on electrical power systems. The bi-level formulation is investigated through a problem in which the goal of the hacker is to maximize load curtailment and that of the power system operator is to minimize load curtailment. The resulting nonlinear mixed-integer bilevel programming formulation is converted into an equivalent single-level mixed-integer linear program by solving the inner optimization by KKT optimality conditions. The case studies are conducted based on an IEEE 14-bus system. From the results, it is observed that the ...
Journal of Power and Energy Engineering, 2020
Distribution network state estimation provided complete and reliable information for the distribu... more Distribution network state estimation provided complete and reliable information for the distribution management system (DMS) and was a prerequisite for other advanced management and control applications in the power distribution network. This paper first introduced the basic principles of the state estimation algorithm and sorted out the research status of the distribution network state estimation from least squares, gross error resistance etc. Finally, this paper summarized the key problems faced by the high-dimensional multi-power flow active distribution network state estimation and discussed prospects for future research hotspots and developments.
Improving observability using optimal placement of phasor measurement units
International Journal of Electrical Power & Energy Systems, 2014
State estimator is crucial for on-line power system monitoring, analysis and control. With the in... more State estimator is crucial for on-line power system monitoring, analysis and control. With the increasing use of synchronized phasor measurement units (PMUs) in power grids, utilization of phasor measurements to improve the precision and observability of state estimator becomes imperative. However, for state estimation, the PMUs should be placed appropriately in the network. In this paper, a novel state estimator for minimizing the size of the PMU configuration while allowing full observability of the network is proposed. The proposed approach initially finds the best configuration of PMUs for observability. Then a novel meta-heuristic algorithm called improved fruit fly optimization method is used to determine the minimum number of phasor measurement units that can sustain observability. This methodology is tested on IEEE 14, 24, 30, 57 and 108 bus systems and the results are compared with those found in literature. Results obtained validate the versatility of the approach to deliv...
Dissolved gas analysis to identify faults and improve reliability in transformers using support vector machines
2016 Clemson University Power Systems Conference (PSC), 2016
Dissolved gas analysis (DGA) and its key-gas ratios (C<sub>2</sub>H<sub>2</s... more Dissolved gas analysis (DGA) and its key-gas ratios (C<sub>2</sub>H<sub>2</sub>/C<sub>2</sub>H<sub>4</sub>, CH<sub>4</sub>/H<sub>2</sub>, C<sub>2</sub>H<sub>4</sub>/C<sub>2</sub>H<sub>6</sub>) are the most widely used fault diagnostic tests for transformers. This technique monitors the concentration of various gases in transformer oil and uses it to interpret the type of fault. In this study, support vector machines (SVM) is proposed to classify and predict electrical faults in transformers depending on the key-gas ratios concentrations. A dissolved gas analysis data obtained from published papers are used as a sample for the training and test set with a supervised machine learning from MATLAB software. Results indicate that SVM method can achieve good accuracy under the circumstance of small training data.
Decentralized demand side management and control of PEVs connected to a smart grid
2015 Clemson University Power Systems Conference (PSC), 2015
The recent push for electrified vehicles, including both plug-in hybrid vehicles and pure electri... more The recent push for electrified vehicles, including both plug-in hybrid vehicles and pure electric vehicle may further increase peak electrical load if left unmitigated, resulting in more demand for generation and transmission capacities. Fortunately, PEVs can be treated as controllable loads or even power sources under extraneous situations for demand side management (DSM). Although centralized approach certainly performs an effective demand side management, an important concept regarding the privacy of the information access is not already considered. The objective function for this multi objective problem of demand side power management and decentralized control is the total electricity generation cost and cost associated with implementing the demand side management programs. Thus saving a unit of electricity because of implementing demand side management can be treated like producing a unit of electricity by a power plant. The main constraint related to DSM is that the maximum expected saving that could be achieved by implementing DSM is capped to a realistic maximum limit. The framework is flexible and could incorporate any meta-heuristic for multi-objective optimization. This multi objective approach is applied on a test system comprising of 2516 domestic consumers, 296 small consumption firms, 150 medium consumption firms and 4 large consumption firms. It is observed that PEVs could utilize information transfer with the grid to shape the effect exhibited on the overall load. Also the obtained numerical results show that this approach will improve PEV market penetration, especially relative to centralized strategies that could deter consumers who wish to independently determine their charging strategy.
Electric Vehicles represent an important and futuristic alternative to conventional vehicles. How... more Electric Vehicles represent an important and futuristic alternative to conventional vehicles. However, the effect of charging electric vehicles on electric grids must be taken into account to prevent accidental overloading of the distribution grid due to simultaneous charging/discharging of electric vehicles. As electric vehicles gain more popularity with consumers, power companies and utilities must be prepared for the added load. To assist in this preparation, power companies will need accurate load forecasting algorithms. This paper presents the development of an algorithm that forecasts the load for Battery Electric Vehicles, or BEVs at 15 minute intervals for any day between January 1, 2011 and December 31, 2023. The forecast algorithm uses the projected BEV growth rate, the population of the parking lot or garage of inquiry, and a probability distribution which relates the state of charge (SOC) of the vehicle’s battery to the percent of EV owners that require such charging dai...
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Papers by Bhuvana Ramachandran