U. Bhagyashree

Bio: U. Bhagyashree is an academic researcher from Veermata Jijabai Technological Institute. The author has contributed to research in topics: Grid & Load profile. The author has an hindex of 2, co-authored 7 publications receiving 10 citations.

Power Grid Load Management using Electric Vehicles: A Distributed Resource Allocation Approach

Abstract: Technological advancements in modern age has introduced complex networks and multi-agent systems all around us. The main aim of multi-agent systems is to implement local control laws to achieve a global objective. The Distributed Resource Allocation (DRA) approach has been utilised in this paper for successful incorporation of a large number of Plug-in Electric Vehicles (PEVs) with the power grid. The DRA approach has been used to find an optimal charging strategy for all PEVs such that it satisfies the power grid objective in terms of the smoothening and flattening of grid load profile. The consensus protocol, an application of DRA approach has been implemented to provide a fair scheme of charging strategy to each individual PEV connected to the grid based on their commitment factor.

Electric Vehicle - Power Grid Incorporation Using Distributed Resource Allocation Approach

Abstract: Models of multi-agent systems can be found all around us. One of the objectives of multi-agent systems is to define local control laws in order to achieve a desired global state of the system. This paper utilises the concept of Distributed Resource Allocation (DRA) approach for successful incorporation of a large number of Plug-in Electric Vehicles (PEVs) with the power grid. DRA approach is implemented using the concept of achieving output consensus. A fixed number of PEVs are considered which are connected to the grid for a certain time interval. The PEV batteries can be charged as well discharged during this time interval. Charging and discharging of PEVs from the grid is further divided into time slots and are coined as strategies. The goal of this paper is to obtain a well-inclined charging strategy for each PEV connected to the grid such that it satisfies the power grid objective in terms of the smoothening factor of grid load profile.

Electric Vehicle - Power Grid Incorporation Using Distributed Resource Allocation Approach

Abstract: Models of multi-agent systems can be found all around us. One of the objectives of multi-agent systems is to define local control laws in order to achieve a desired global state of the system. This paper utilises the concept of Distributed Resource Allocation (DRA) approach for successful incorporation of a large number of Plug-in Electric Vehicles (PEVs) with the power grid. DRA approach is implemented using the concept of achieving output consensus. A fixed number of PEVs are considered which are connected to the grid for a certain time interval. The PEV batteries can be charged as well discharged during this time interval. Charging and discharging of PEVs from the grid is further divided into time slots and are coined as strategies. The goal of this paper is to obtain a well-inclined charging strategy for each PEV connected to the grid such that it satisfies the power grid objective in terms of the smoothening factor of grid load profile.

Distributed Optimization of Standalone PV Components in Microgrid

Abstract: Renewable energy sources particularly solar energy have a great potential in fulfilling the energy demand in far-off rural areas where providing electricity is difficult from the existing transmission line network of the main grid. Photovoltaic (PV) sources possess stochastic nature either operating standalone or connected to the main power grid. The standalone systems have various issues like voltage fluctuations and power quality which also have an adverse effect on equipment utilizing the power generated from PV sources. Standalone PV systems consist of PV panels, a storage system, and a charge control unit (CCU). To fully utilize the energy generated from PV panels all these components as well as loads must be optimized to provide an efficient operating scenario in microgrids. Required operating condition is achieved by a distributed optimization method with the lower and upper bound constraints in terms of population dynamics of microgrid components. To implement this, a microgrid is considered with 10 Standalone PV systems with residential loads. The analysis shows how power converges to a reference value and provides a stable voltage profile for the standalone microgrid systems in rural areas.

Bifurcation Point Tracking in Generator Outage Scenario using Nested Holomorphic Embedding Power Flow Method

Abstract: The power system is operated to an increasing extent bordering its limits. Violation of these limits leads the system towards its bifurcation point (BP), resulting in voltage collapse. Therefore, tracking of BP for generator outage condition is essential, which gives a stability margin to the system operator for preventive control. Hence, a power flow solution, independent of convergence issue is of a great deal. This paper proposes a nested holomorphic embedding power flow method (HEPM) for obtaining power flow solution if one exists along with the bifurcation point and unambiguously notifies its nonexistence under sequential generator outage. It is devoid of the issues faced by iterative methods implemented during major blackouts, cascade failure, and voltage collapse situations. The complexity of the nested HEPM for calculation of the bifurcation point in terms of the number of power flow equations to be solved is extremely lower compared with other iterative methods. The proposed methodology is validated with a modified IEEE 14 bus system using MATLAB in the worst-case scenario where all generators fail except the slack bus.

Online Voltage Stability Assessment for Load Areas Based on the Holomorphic Embedding Method

Abstract: This paper proposes an online steady-state voltage stability assessment scheme to evaluate the proximity to voltage collapse at each bus of a load area. Using a non-iterative holomorphic embedding method (HEM) with a proposed physical germ solution, an accurate loading limit at each load bus can be calculated based on online state estimation on the entire load area and a measurement-based equivalent for the external system. The HEM employs a power series to calculate an accurate Power-Voltage (P-V) curve at each load bus and accordingly evaluates the voltage stability margin considering load variations in the next period. An adaptive two-stage Pade approximants method is proposed to improve the convergence of the power series for accurate determination of the nose point on the P-V curve with moderate computational burden. The proposed method is illustrated in detail on a 4-bus test system and then demonstrated on a load area of the Northeast Power Coordinating Council (NPCC) 48-geneartor, 140-bus power system.

Packetized plug-in electric vehicle charge management

Abstract: Plug-in electric vehicle (PEV) charging could cause significant strain on residential distribution systems, unless technologies and incentives are created to mitigate charging during times of peak residential consumption. This paper describes and evaluates a decentralized and ‘packetized’ approach to PEV charge management, in which PEV charging is requested and approved for time-limited periods. This method, which is adapted from approaches for bandwidth sharing in communication networks, simultaneously ensures that constraints in the distribution network are satisfied, that communication bandwidth requirements are relatively small, and that each vehicle has fair access to the available power capacity. This paper compares the performance of the packetized approach to an optimization method and a first-come, first-served (FCFS) charging scheme in a test case with a constrained 500 kVA distribution feeder and time-of-use residential electricity pricing. The results show substantial advantages for the packetized approach. The algorithm provides all vehicles with equal access to constrained resources and attains near optimal travel cost performance, with low complexity and communication requirements. The proposed method does not require that vehicles report or record driving patterns, and thus provides benefits over optimization approaches by preserving privacy and reducing computation and bandwidth requirements.

Vehicle-to-Grid Integration for Enhancement of Grid: A Distributed Resource Allocation Approach

Abstract: In the future grids, to reduce greenhouse gas emissions Electric Vehicles (EVs) seems to be an important means of transportation. One of the major disadvantages of the future grid is the demand-supply mismatch which can be mitigated by incorporating the EVs into the grid. The paper introduces the concept of the Distributed Resource Allocation (DRA) approach for incorporating a large number of Plug-in EV (PEVs) with the power grid utilizing the concept of achieving output consensus. The charging/discharging time of all the participating PEVs are separated with respect to time slots and are considered as strategies. The major aim of the paper is to obtain a favorable charging strategy for each grid-connected PEVs in such a way that it satisfies both grid objectives in terms of load profile smoothening and minimizing of load shifting as well as economic and social interests of vehicle owners i.e. a fair share of the rate of charging for all connected PEVs. The three-fold contribution of the paper in smoothening of load profile, load shifting minimization, and fair charging rate is validated using a representative case study. The results confirm improvement in load profile and also highlight a fair deal in the charging rate for each PEV.

Fish and Chips: Converting Fishing Boats for Electric Mobility to Serve as Minigrid Anchor Loads

Abstract: Though electricity access remains out of reach for roughly one billion primarily rural and low-income people, crucial strides have been made in developing new pathways for connecting households and businesses to electricity supplies Among these, decentralized minigrids - typically comprised of generation, storage, and a medium- and low-voltage distribution network - have considerable technical promise for balancing recent advances in decentralized generation as well as grid sensing and communication systems with the overwhelming economies-of-scale enjoyed by electricity grids However, low revenues and, in response, high tariffs necessary for cost recovery stifle the widespread development of this promising pathway for electrification In this paper, we study techniques for addressing the principal challenge for sustainable minigrids: demand stimulation among rural customers Specifically, we evaluate the potential for conversion of diesel-based fishing boats in Lake Victoria to electric motor and battery-based systems that can provide a crucial anchor load for a nascent 650 kWp hybrid solar-battery-diesel minigrid We conduct a survey among fishing boat operators (n = 69) to characterize the target population and deploy a custom tracking system to measure fishing boat movement patterns Using these primary data along with secondary data on customer consumption, we select a candidate electric mobility system, create synthetic loads of residential and business customers, and construct technical and financial models of the complete minigrid system We then use these models to evaluate the excess capacity on the minigrid for electric boats, evaluate the tradeoffs among electric mobility and manufacturing on the minigrid, and assess the impacts of demand response capabilities for charging the boats We find that electric boat charging contributes to at least 17% more consumption per day resulting in substantial technical as well as financial value to the minigrid system, though perhaps at the cost of additional use of the system's backup diesel generator We find that adding shifting capabilities to electric boat charging can save up to 6% of diesel expenditures at little to no impact on the system Net Present Value We combine these minigrid-scale evaluations with design considerations for a future boat tracking system, providing guidance for minigrid designers and operators to incorporate the potentially attractive load class of electric mobility systems

Forecasting and Enhancing the Performance of the Electric Grid: A Dynamic Mode Decomposition approach

Abstract: The recent development in the field of smart meters has resulted in a large amount of electricity consumption profile which can be forecasted and analyzed for better planning of grid such as load scheduling, demand-side management, etc. In this paper, a Dynamic Mode Decomposition (DMD) for forecasting of grid profile for a specified time period is proposed. The key feature of the DMD technique is that it utilizes the past data for the prediction of future data without the need for the system model. Once the load profile is forecasted using DMD, the peak loads and base load time period are segregated. With the help of a system operator, various energy sources can be arranged for supplying peak loads. Electric vehicles (EVs) having the advantage of mobility and smart building acting as the virtual battery is considered for providing support to the grid as compared to other renewable energy sources which generally have limitations due to environmental factors. The DMD technique for forecasting the load profile of the smart grid is tested under various test scenarios. Finally, from the results, it has been proved that EVs and the smart building seem to be the most promising solution for supporting the grid during the peak load period.