Sailaja Kumari M - Academia.edu (original) (raw)

Papers by Sailaja Kumari M

Demand for electricity is gradually increasing in India and use of more thermal power generation ... more Demand for electricity is gradually increasing in India and use of more thermal power generation is leading to increased emissions. The effect of emission of thermal power plant is adverse to the environment; we cannot largely depend on thermal power plant for power generation. So, this work considered the integration of thermal units with the renewable sources like solar and wind, while accounting for ancillary service management and renewable energy uncertainties. Unit Commitment (UC) and Economic load dispatch (ELD) have significant research applications in power systems and optimize the total production cost for the forecasted load demand of particular hour. UC decides the turn ON/ turn OFF decision of particular unit/units according to the forecasted load of particular hour optimally while satisfying all constraints of the unit like minimum up and down time, startup and shut down cost constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the forecasted load demands of customers in particular hour. UC and ELD are performed to reduce the total production cost to as minimum as possible, so that customer will get electricity at minimum cost. This paper presents a Genetic algorithm and priority list approach for wind and solar integrated system having thermal generators, for solving UC problem. The dynamic programming approach is used for the UC and ELD and production cost of each hour is calculated for comparison purpose.

Journal of Electrical Engineering & Technology, Dec 1, 2009

Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit c... more Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit commitment, economic load dispatch planning, turbine active control and optimal planning for wind farms maintenance. In this paper wind speed has been forecasted for 30 hour ahead by using Artificial Neural Network (ANN) and Auto Regressive Integrated Moving Average (ARIMA) models based on Empirical Mode Decomposition (EMD) method. Wind speed data is decomposed into Intrinsic Mode Functions (IMF) and Residue by EMD method. High frequency IMFs are forecasted using ANN model and low frequency IMFs and a residue are forecasted using ARIMA model. The result obtained by proposed method has given less mean absolute percentage error (MAPE) and improved statistical parameters. Wind speed data of the site 7263 in the Midwest ISO region is used for this study and it has been taken from National Renewable Energy Laboratory (NREL) website for the year 2014.

Electric Power Components and Systems, Oct 21, 2021

Electric Power Components and Systems

2016 International Conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH), 2016

Demand for electricity is gradually increasing in India and use of more thermal power generation ... more Demand for electricity is gradually increasing in India and use of more thermal power generation is leading to increased emissions. The effect of emission of thermal power plant is adverse to the environment; we cannot largely depend on thermal power plant for power generation. So, this work considered the integration of thermal units with the renewable sources like solar and wind, while accounting for ancillary service management and renewable energy uncertainties. Unit Commitment (UC) and Economic load dispatch (ELD) have significant research applications in power systems and optimize the total production cost for the forecasted load demand of particular hour. UC decides the turn ON/ turn OFF decision of particular unit/units according to the forecasted load of particular hour optimally while satisfying all constraints of the unit like minimum up and down time, startup and shut down cost constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the forecasted load demands of customers in particular hour. UC and ELD are performed to reduce the total production cost to as minimum as possible, so that customer will get electricity at minimum cost. This paper presents a Genetic algorithm and priority list approach for wind and solar integrated system having thermal generators, for solving UC problem. The dynamic programming approach is used for the UC and ELD and production cost of each hour is calculated for comparison purpose.

2013 International Conference on Power, Energy and Control (ICPEC), 2013

ABSTRACT There are several forecasting methods available to estimate the uncertainty of the wind.... more ABSTRACT There are several forecasting methods available to estimate the uncertainty of the wind. Wind behavior is chaotic in nature. These forecasting methods are used to predict wind power generation capacity for the grid. With the introduction of smart grid has created enough space for integrating renewable (wind power) in to the grid. Several methods have been proposed by researchers to estimate the wind speed. In present days there is a lot of research is going on to estimate the wind speed by using mathematical, biologically inspired computing methods to minimize the prediction error. This paper presents a review of several forecasting techniques which are using presently. This paper will be helpful for the new researchers who are going to work in this area. This paper will also be helpful to the wind farm operators to know about the present wind estimation model capabilities and will give an idea to estimate the wind speed at their particular wind farms.

2017 14th IEEE India Council International Conference (INDICON), 2017

Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit c... more Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit commitment, economic load dispatch planning, turbine active control and optimal planning for wind farms maintenance. In this paper wind speed has been forecasted for 30 hour ahead by using Artificial Neural Network (ANN) and Auto Regressive Integrated Moving Average (ARIMA) models based on Empirical Mode Decomposition (EMD) method. Wind speed data is decomposed into Intrinsic Mode Functions (IMF) and Residue by EMD method. High frequency IMFs are forecasted using ANN model and low frequency IMFs and a residue are forecasted using ARIMA model. The result obtained by proposed method has given less mean absolute percentage error (MAPE) and improved statistical parameters. Wind speed data of the site 7263 in the Midwest ISO region is used for this study and it has been taken from National Renewable Energy Laboratory (NREL) website for the year 2014.

International Journal of Emerging Electric Power Systems, Apr 26, 2023

The Proton Exchange Membrane Fuel Cell (PEMFC) has found widespread use for regulated output volt... more The Proton Exchange Membrane Fuel Cell (PEMFC) has found widespread use for regulated output voltage applications because of its quick response time and mobility. A different form of hydrogen is employed in fuel cell-based electric vehicles for smart transportation for the reduction of global warming and the development of smart cities. To properly manage the operation of Fuel Cells (FCs), there is a need for accurate modeling. One of the most common challenges is finding the exact values of unknown parameters in the PEMFC. In the current study, a new method called Dandelion Optimizer (DO) is used for parameter identification. DO is used to estimate the parameters of the PEMFC based on Current-Voltage (I-V) characteristics. The Ballard Mark V and BCS 500-W PEMFC stacks use the DO method to identify unknown parameters. The performance of the DO algorithm is compared to that of other optimization techniques and the Sum of Squared Errors (SSE) is used to represent the objective function of the current optimization problem. In contrast to traditional and other efficient techniques, the simulation results proposed by the DO algorithm have excellent accuracy in extracting the PEMFC optimal parameters.

Journal of institution of engineers (India) series B, Jan 18, 2021

This paper presents a novel topology-based optimal PMU placement strategy. The proposed strategy ... more This paper presents a novel topology-based optimal PMU placement strategy. The proposed strategy provides the entire feasible solution space which gives the observability of the power system by working on binary connectivity matrix of the system. From the feasible solution space, multiple optimal solutions are obtained. Providing multiple optimal solutions gives flexibility to the system operator to choose one optimal solution which best fits subordinate objectives rather than providing single optimal solution which gives no choice to the operator. This novel strategy has been tested on IEEE 14-bus and IEEE 30-bus system. Multiple optimal solutions are obtained while maintaining observability and maximizing redundancy. For demonstrating the advantage of multiple optimal solutions, minor objectives, such as direct monitoring of generator and weak buses are illustrated. One of the multiple solution which best fits to the minor objectives is chosen as a final optimal solution. The proposed method ensures global optimal solution for various objectives under consideration. In addition, normalized Bus observability index and normalized System observability redundancy index are presented to overcome the drawback of SORI and BOI.

Energy and power, Aug 31, 2012

This paper presents an approach for optimal placement and size of the DGs considering system tech... more This paper presents an approach for optimal placement and size of the DGs considering system technical issues such as active and reactive power losses, the voltage profile and the line loading of the system. The solar and wind systems are modelled as constant power factor model and variable reactive power model respectively. The renewable energy DGs placement is limited to a number of busses with the consideration of environmental constrains. In this work, only the solar and wind available busses are considered for optimization for placing the Renewable DGs. The impact indices of the total system are compared with and without considering the DGs limiting busses. This work is tested on 38-bus Distribution Systems. The simulation technique based on Genetic Algorithm is studied.

International Journal of Electrical Power & Energy Systems, Jul 1, 2016

Abstract In this paper a new and efficient hybrid multi-objective optimization algorithm is propo... more Abstract In this paper a new and efficient hybrid multi-objective optimization algorithm is proposed for optimal placement and sizing of the Distributed generations (DGs) in radial distribution systems. A Multi-objective Shuffled Bat algorithm is proposed to evaluate the impact of DG placement and sizing for an optimal improvement of the distribution system with different load models. In this study, the ideal sizes and locations of DG units are found by considering the power losses, cost and voltage deviation as objective functions to minimize. Furthermore, the study is verified with voltage dependent load models like industrial, residential, commercial and mixed load models. The feasibility of the proposed technique is verified with the 33 bus distribution network and also the qualitative comparisons against a well-known technique, known as Non-dominated Sorting Genetic Algorithm II (NSGA-II) is done and results are presented.

In this paper a new and efficient hybrid optimization algorithm is proposed for optimal placement... more In this paper a new and efficient hybrid optimization algorithm is proposed for optimal placement and sizing of the Distributed Generations (DGs). Bus voltage profile improvement, line flow capacity, active and reactive power loss minimization are considered as multi-objectives to optimize under various distribution load conditions. Renewable energy resources such as wind, solar, fuel cell and micro turbines are considered in power system modeling for finding the optimal placement and sizing. Current injection based distribution load flow is considered in DGs modeling in power systems. To optimize the objective function, a new optimization technique called Shuffled Bat algorithm (ShBAT) is proposed. The proposed methodology is tested on 84-bus Taiwan power company distribution systems with 90%, 100% and 120% of base load conditions to demonstrate its performance and effectiveness. Results show that the planned methodology is superior to existing strategies in terms of multi-objectives considered.

International Journal of Renewable Energy Research, 2017

In a restructured power system, Ancillary services (AS) are required to balance load generation m... more In a restructured power system, Ancillary services (AS) are required to balance load generation mismatches and to meet unforeseen contingencies. Operating Reserve is a major part of AS which is highly uncertain to forecast, mainly due to the unpredictability of customer needs, over or under production of Energy and unpredictability in the integration of renewable energy sources. In this work, wind integration is considered as a factor to forecast operating reserve. The increase of wind integration into power system needs larger quantities of operating reserve. This demands an increase in the cost of generation and emissions. Forecasting the Operating Reserve Ancillary Service helps the system operators (SO) to plan scheduling of generators in advance and also in better bidding environment. Forecasting tools like feed-forward networks, Time series models were used to forecast load and Electricity price in the past. In this paper a hybrid method consisting of Support Vector Machines (SVM) and Fuzzy Interface System (FIS) is used to forecast Operating Reserve in Day-ahead market. Case studies using CAISO and ERCOT ISOs are presented. The SVM-FIS method is found to be better forecasting tool to predict the operating reserve Ancillary Service.

Energy Procedia, 2012

There has been a great interest in integration of distributed generation (DG) units at distributi... more There has been a great interest in integration of distributed generation (DG) units at distribution level in the recent years. DGs can provide cost-effective, environmental friendly, higher power quality and more reliable energy solutions than conventional generation. For maximum power loss reduction, proper sizing and position of distributed generators are ardently necessary. This paper presents a simple method for optimizing cost and optimal placement of generators. A simple vector based load flow technique is implemented on 38 bus distribution systems. This paper presents a new methodology using a new population based meta heuristic approach namely Shuffled frog leaping algorithm for the placement of Distributed Generators (DG) in the radial distribution systems to reduce the real power losses and cost of the DG. The paper also focuses on optimization of weighting factor, which balances the cost and the loss factors and helps to build up desired objectives with maximum potential benefit. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.

Congestion management is one of the technical challenges in power system deregulation. This paper... more Congestion management is one of the technical challenges in power system deregulation. This paper presents single objective and multi-objective optimization approaches for optimal choice, location and size of Static Var Compensators (SVC) and Thyristor Controlled Series Capacitors (TCSC) in deregulated power system to improve branch loading (minimize congestion), improve voltage stability and reduce line losses. Though FACTS controllers offer many

International Transactions on Electrical Energy Systems, Apr 1, 2015

Summary In this paper, a new and efficient hybrid optimization algorithm is proposed for optimal ... more Summary In this paper, a new and efficient hybrid optimization algorithm is proposed for optimal placement and sizing of the distributed generations (DGs). Bus voltage profile improvement, line flow capacity, and active and reactive power loss minimization are considered as multi-objectives to optimize under-distribution load enhancement. The addition of multi-DGs to the distribution system, which is already having DGs, is studied under increased load demand. Renewable energy resources such as wind, solar, fuel cell, and micro turbines are considered in power system modeling for finding the optimal placement and sizing. Current injection-based distribution load is considered in DGs modeling in power systems. Active and reactive losses and voltage profiles are studied for all combinations of DGs. To optimize the objective function, a new optimization technique called shuffled bat algorithm is proposed. The proposed methodology is tested on 38-bus and 69-bus radial distribution systems with 100% and 120% of base load conditions to demonstrate its performance and effectiveness. Results show that the planned methodology is superior to existing strategies in terms of multi-objectives considered. Copyright © 2015 John Wiley & Sons, Ltd.

International Journal of Renewable Energy Research, 2017

This paper proposes a solution to generator bidding strategy using a novel hybrid Evolutionary Ga... more This paper proposes a solution to generator bidding strategy using a novel hybrid Evolutionary Game Theory (EGT) and Differential Evolution (DE) method. In restructured power system, the generating companies (GENCOs) have an opportunity to compete in energy and ancillary services markets and earn profits. This competition creates a complicated situation to System Operator (SO) in the market clearing process. This paper attempts to maximize GENCOs profit with incomplete information by adopting optimal bidding strategies in energy and ancillary service markets while considering unit commitment constraints. Supply Function Equilibrium (SFE) model is employed to compute GENCOs profit. Nash Equilibrium points were calculated in the first stage by using Evolutionary Game Theory and then optimal bidding strategies were found with the help of Differential Evolution method. Evolutionary Game Theory is best suited for GENCOs bidding strategies but leads to slow convergence due to a large number of variables. So, a novel hybrid method involving Evolutionary Game Theory with Differential Evolution is proposed in this paper. The proposed method to solve bidding strategies is employed on WSCC 9 and New England 39 bus test systems to demonstrate its merits.

Lecture notes in electrical engineering, 2022

Journal of The Institution of Engineers (India): Series B

Demand for electricity is gradually increasing in India and use of more thermal power generation ... more Demand for electricity is gradually increasing in India and use of more thermal power generation is leading to increased emissions. The effect of emission of thermal power plant is adverse to the environment; we cannot largely depend on thermal power plant for power generation. So, this work considered the integration of thermal units with the renewable sources like solar and wind, while accounting for ancillary service management and renewable energy uncertainties. Unit Commitment (UC) and Economic load dispatch (ELD) have significant research applications in power systems and optimize the total production cost for the forecasted load demand of particular hour. UC decides the turn ON/ turn OFF decision of particular unit/units according to the forecasted load of particular hour optimally while satisfying all constraints of the unit like minimum up and down time, startup and shut down cost constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the forecasted load demands of customers in particular hour. UC and ELD are performed to reduce the total production cost to as minimum as possible, so that customer will get electricity at minimum cost. This paper presents a Genetic algorithm and priority list approach for wind and solar integrated system having thermal generators, for solving UC problem. The dynamic programming approach is used for the UC and ELD and production cost of each hour is calculated for comparison purpose.

Journal of Electrical Engineering & Technology, Dec 1, 2009

Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit c... more Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit commitment, economic load dispatch planning, turbine active control and optimal planning for wind farms maintenance. In this paper wind speed has been forecasted for 30 hour ahead by using Artificial Neural Network (ANN) and Auto Regressive Integrated Moving Average (ARIMA) models based on Empirical Mode Decomposition (EMD) method. Wind speed data is decomposed into Intrinsic Mode Functions (IMF) and Residue by EMD method. High frequency IMFs are forecasted using ANN model and low frequency IMFs and a residue are forecasted using ARIMA model. The result obtained by proposed method has given less mean absolute percentage error (MAPE) and improved statistical parameters. Wind speed data of the site 7263 in the Midwest ISO region is used for this study and it has been taken from National Renewable Energy Laboratory (NREL) website for the year 2014.

Electric Power Components and Systems, Oct 21, 2021

Electric Power Components and Systems

2016 International Conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH), 2016

Demand for electricity is gradually increasing in India and use of more thermal power generation ... more Demand for electricity is gradually increasing in India and use of more thermal power generation is leading to increased emissions. The effect of emission of thermal power plant is adverse to the environment; we cannot largely depend on thermal power plant for power generation. So, this work considered the integration of thermal units with the renewable sources like solar and wind, while accounting for ancillary service management and renewable energy uncertainties. Unit Commitment (UC) and Economic load dispatch (ELD) have significant research applications in power systems and optimize the total production cost for the forecasted load demand of particular hour. UC decides the turn ON/ turn OFF decision of particular unit/units according to the forecasted load of particular hour optimally while satisfying all constraints of the unit like minimum up and down time, startup and shut down cost constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the forecasted load demands of customers in particular hour. UC and ELD are performed to reduce the total production cost to as minimum as possible, so that customer will get electricity at minimum cost. This paper presents a Genetic algorithm and priority list approach for wind and solar integrated system having thermal generators, for solving UC problem. The dynamic programming approach is used for the UC and ELD and production cost of each hour is calculated for comparison purpose.

2013 International Conference on Power, Energy and Control (ICPEC), 2013

ABSTRACT There are several forecasting methods available to estimate the uncertainty of the wind.... more ABSTRACT There are several forecasting methods available to estimate the uncertainty of the wind. Wind behavior is chaotic in nature. These forecasting methods are used to predict wind power generation capacity for the grid. With the introduction of smart grid has created enough space for integrating renewable (wind power) in to the grid. Several methods have been proposed by researchers to estimate the wind speed. In present days there is a lot of research is going on to estimate the wind speed by using mathematical, biologically inspired computing methods to minimize the prediction error. This paper presents a review of several forecasting techniques which are using presently. This paper will be helpful for the new researchers who are going to work in this area. This paper will also be helpful to the wind farm operators to know about the present wind estimation model capabilities and will give an idea to estimate the wind speed at their particular wind farms.

2017 14th IEEE India Council International Conference (INDICON), 2017

Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit c... more Wind power output mainly depends on wind speed. Forecasting of wind speed is important for unit commitment, economic load dispatch planning, turbine active control and optimal planning for wind farms maintenance. In this paper wind speed has been forecasted for 30 hour ahead by using Artificial Neural Network (ANN) and Auto Regressive Integrated Moving Average (ARIMA) models based on Empirical Mode Decomposition (EMD) method. Wind speed data is decomposed into Intrinsic Mode Functions (IMF) and Residue by EMD method. High frequency IMFs are forecasted using ANN model and low frequency IMFs and a residue are forecasted using ARIMA model. The result obtained by proposed method has given less mean absolute percentage error (MAPE) and improved statistical parameters. Wind speed data of the site 7263 in the Midwest ISO region is used for this study and it has been taken from National Renewable Energy Laboratory (NREL) website for the year 2014.

International Journal of Emerging Electric Power Systems, Apr 26, 2023

The Proton Exchange Membrane Fuel Cell (PEMFC) has found widespread use for regulated output volt... more The Proton Exchange Membrane Fuel Cell (PEMFC) has found widespread use for regulated output voltage applications because of its quick response time and mobility. A different form of hydrogen is employed in fuel cell-based electric vehicles for smart transportation for the reduction of global warming and the development of smart cities. To properly manage the operation of Fuel Cells (FCs), there is a need for accurate modeling. One of the most common challenges is finding the exact values of unknown parameters in the PEMFC. In the current study, a new method called Dandelion Optimizer (DO) is used for parameter identification. DO is used to estimate the parameters of the PEMFC based on Current-Voltage (I-V) characteristics. The Ballard Mark V and BCS 500-W PEMFC stacks use the DO method to identify unknown parameters. The performance of the DO algorithm is compared to that of other optimization techniques and the Sum of Squared Errors (SSE) is used to represent the objective function of the current optimization problem. In contrast to traditional and other efficient techniques, the simulation results proposed by the DO algorithm have excellent accuracy in extracting the PEMFC optimal parameters.

Journal of institution of engineers (India) series B, Jan 18, 2021

This paper presents a novel topology-based optimal PMU placement strategy. The proposed strategy ... more This paper presents a novel topology-based optimal PMU placement strategy. The proposed strategy provides the entire feasible solution space which gives the observability of the power system by working on binary connectivity matrix of the system. From the feasible solution space, multiple optimal solutions are obtained. Providing multiple optimal solutions gives flexibility to the system operator to choose one optimal solution which best fits subordinate objectives rather than providing single optimal solution which gives no choice to the operator. This novel strategy has been tested on IEEE 14-bus and IEEE 30-bus system. Multiple optimal solutions are obtained while maintaining observability and maximizing redundancy. For demonstrating the advantage of multiple optimal solutions, minor objectives, such as direct monitoring of generator and weak buses are illustrated. One of the multiple solution which best fits to the minor objectives is chosen as a final optimal solution. The proposed method ensures global optimal solution for various objectives under consideration. In addition, normalized Bus observability index and normalized System observability redundancy index are presented to overcome the drawback of SORI and BOI.

Energy and power, Aug 31, 2012

This paper presents an approach for optimal placement and size of the DGs considering system tech... more This paper presents an approach for optimal placement and size of the DGs considering system technical issues such as active and reactive power losses, the voltage profile and the line loading of the system. The solar and wind systems are modelled as constant power factor model and variable reactive power model respectively. The renewable energy DGs placement is limited to a number of busses with the consideration of environmental constrains. In this work, only the solar and wind available busses are considered for optimization for placing the Renewable DGs. The impact indices of the total system are compared with and without considering the DGs limiting busses. This work is tested on 38-bus Distribution Systems. The simulation technique based on Genetic Algorithm is studied.

International Journal of Electrical Power & Energy Systems, Jul 1, 2016

Abstract In this paper a new and efficient hybrid multi-objective optimization algorithm is propo... more Abstract In this paper a new and efficient hybrid multi-objective optimization algorithm is proposed for optimal placement and sizing of the Distributed generations (DGs) in radial distribution systems. A Multi-objective Shuffled Bat algorithm is proposed to evaluate the impact of DG placement and sizing for an optimal improvement of the distribution system with different load models. In this study, the ideal sizes and locations of DG units are found by considering the power losses, cost and voltage deviation as objective functions to minimize. Furthermore, the study is verified with voltage dependent load models like industrial, residential, commercial and mixed load models. The feasibility of the proposed technique is verified with the 33 bus distribution network and also the qualitative comparisons against a well-known technique, known as Non-dominated Sorting Genetic Algorithm II (NSGA-II) is done and results are presented.

In this paper a new and efficient hybrid optimization algorithm is proposed for optimal placement... more In this paper a new and efficient hybrid optimization algorithm is proposed for optimal placement and sizing of the Distributed Generations (DGs). Bus voltage profile improvement, line flow capacity, active and reactive power loss minimization are considered as multi-objectives to optimize under various distribution load conditions. Renewable energy resources such as wind, solar, fuel cell and micro turbines are considered in power system modeling for finding the optimal placement and sizing. Current injection based distribution load flow is considered in DGs modeling in power systems. To optimize the objective function, a new optimization technique called Shuffled Bat algorithm (ShBAT) is proposed. The proposed methodology is tested on 84-bus Taiwan power company distribution systems with 90%, 100% and 120% of base load conditions to demonstrate its performance and effectiveness. Results show that the planned methodology is superior to existing strategies in terms of multi-objectives considered.

International Journal of Renewable Energy Research, 2017

In a restructured power system, Ancillary services (AS) are required to balance load generation m... more In a restructured power system, Ancillary services (AS) are required to balance load generation mismatches and to meet unforeseen contingencies. Operating Reserve is a major part of AS which is highly uncertain to forecast, mainly due to the unpredictability of customer needs, over or under production of Energy and unpredictability in the integration of renewable energy sources. In this work, wind integration is considered as a factor to forecast operating reserve. The increase of wind integration into power system needs larger quantities of operating reserve. This demands an increase in the cost of generation and emissions. Forecasting the Operating Reserve Ancillary Service helps the system operators (SO) to plan scheduling of generators in advance and also in better bidding environment. Forecasting tools like feed-forward networks, Time series models were used to forecast load and Electricity price in the past. In this paper a hybrid method consisting of Support Vector Machines (SVM) and Fuzzy Interface System (FIS) is used to forecast Operating Reserve in Day-ahead market. Case studies using CAISO and ERCOT ISOs are presented. The SVM-FIS method is found to be better forecasting tool to predict the operating reserve Ancillary Service.

Energy Procedia, 2012

There has been a great interest in integration of distributed generation (DG) units at distributi... more There has been a great interest in integration of distributed generation (DG) units at distribution level in the recent years. DGs can provide cost-effective, environmental friendly, higher power quality and more reliable energy solutions than conventional generation. For maximum power loss reduction, proper sizing and position of distributed generators are ardently necessary. This paper presents a simple method for optimizing cost and optimal placement of generators. A simple vector based load flow technique is implemented on 38 bus distribution systems. This paper presents a new methodology using a new population based meta heuristic approach namely Shuffled frog leaping algorithm for the placement of Distributed Generators (DG) in the radial distribution systems to reduce the real power losses and cost of the DG. The paper also focuses on optimization of weighting factor, which balances the cost and the loss factors and helps to build up desired objectives with maximum potential benefit. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.

Congestion management is one of the technical challenges in power system deregulation. This paper... more Congestion management is one of the technical challenges in power system deregulation. This paper presents single objective and multi-objective optimization approaches for optimal choice, location and size of Static Var Compensators (SVC) and Thyristor Controlled Series Capacitors (TCSC) in deregulated power system to improve branch loading (minimize congestion), improve voltage stability and reduce line losses. Though FACTS controllers offer many

International Transactions on Electrical Energy Systems, Apr 1, 2015

Summary In this paper, a new and efficient hybrid optimization algorithm is proposed for optimal ... more Summary In this paper, a new and efficient hybrid optimization algorithm is proposed for optimal placement and sizing of the distributed generations (DGs). Bus voltage profile improvement, line flow capacity, and active and reactive power loss minimization are considered as multi-objectives to optimize under-distribution load enhancement. The addition of multi-DGs to the distribution system, which is already having DGs, is studied under increased load demand. Renewable energy resources such as wind, solar, fuel cell, and micro turbines are considered in power system modeling for finding the optimal placement and sizing. Current injection-based distribution load is considered in DGs modeling in power systems. Active and reactive losses and voltage profiles are studied for all combinations of DGs. To optimize the objective function, a new optimization technique called shuffled bat algorithm is proposed. The proposed methodology is tested on 38-bus and 69-bus radial distribution systems with 100% and 120% of base load conditions to demonstrate its performance and effectiveness. Results show that the planned methodology is superior to existing strategies in terms of multi-objectives considered. Copyright © 2015 John Wiley & Sons, Ltd.

International Journal of Renewable Energy Research, 2017

This paper proposes a solution to generator bidding strategy using a novel hybrid Evolutionary Ga... more This paper proposes a solution to generator bidding strategy using a novel hybrid Evolutionary Game Theory (EGT) and Differential Evolution (DE) method. In restructured power system, the generating companies (GENCOs) have an opportunity to compete in energy and ancillary services markets and earn profits. This competition creates a complicated situation to System Operator (SO) in the market clearing process. This paper attempts to maximize GENCOs profit with incomplete information by adopting optimal bidding strategies in energy and ancillary service markets while considering unit commitment constraints. Supply Function Equilibrium (SFE) model is employed to compute GENCOs profit. Nash Equilibrium points were calculated in the first stage by using Evolutionary Game Theory and then optimal bidding strategies were found with the help of Differential Evolution method. Evolutionary Game Theory is best suited for GENCOs bidding strategies but leads to slow convergence due to a large number of variables. So, a novel hybrid method involving Evolutionary Game Theory with Differential Evolution is proposed in this paper. The proposed method to solve bidding strategies is employed on WSCC 9 and New England 39 bus test systems to demonstrate its merits.

Lecture notes in electrical engineering, 2022

Journal of The Institution of Engineers (India): Series B