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Dr. Satyendra Singh
Bhartiya Skill Development University Jaipur

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Research Keywords & Expertise

0 Wind Power
0 Power System optimization
0 Power System Optimization techniques
0 Power system economics and electricity markets
0 Uncertainty and decision making

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Journal article
Published: 16 July 2021 in IEEE Access
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A new algorithm for biometric templates using a 6D-chaotic system, and 2D fractional discrete cosine transform (FrDCT) is proposed in this paper. In this technique, the $k$ biometric templates are represented into three groups. After representation, these three groups are converted into row vectors and scrambled by using keys generated by the 6D-chaotic system and after that, these row vectors are combined into three matrices. The three matrices are then mixed horizontally and divided into two halves, with the left half serving as the real part and the right half serving as the imaginary part of a complex-valued matrix (CVM). This CVM is further subjected to 2D FrDCT. The output of 2D FrDCT is separated into three parts. The robustness of the technique is further enhanced by substitution operation using keys generated by the 6D-chaotic system. Thus, the final encrypted template is obtained. The analysis like security, statistical, and attacks are given to authenticate the reliability of the proposed technique. The experimental values also show that the proposed technique is resistant to brute force attacks.

ACS Style

Dhanesh Kumar; Anand B. Joshi; Sonali Singh; Vishnu Narayan Mishra; Hamurabi Gamboa Rosales; Liang Zhou; Arvind Dhaka; Amita Nandal; Hasmat Malik; Satyendra Singh. 6D-Chaotic System and 2D Fractional Discrete Cosine Transform Based Encryption of Biometric Templates. IEEE Access 2021, 9, 103056 -103074.

AMA Style

Dhanesh Kumar, Anand B. Joshi, Sonali Singh, Vishnu Narayan Mishra, Hamurabi Gamboa Rosales, Liang Zhou, Arvind Dhaka, Amita Nandal, Hasmat Malik, Satyendra Singh. 6D-Chaotic System and 2D Fractional Discrete Cosine Transform Based Encryption of Biometric Templates. IEEE Access. 2021; 9 ():103056-103074.

Chicago/Turabian Style

Dhanesh Kumar; Anand B. Joshi; Sonali Singh; Vishnu Narayan Mishra; Hamurabi Gamboa Rosales; Liang Zhou; Arvind Dhaka; Amita Nandal; Hasmat Malik; Satyendra Singh. 2021. "6D-Chaotic System and 2D Fractional Discrete Cosine Transform Based Encryption of Biometric Templates." IEEE Access 9, no. : 103056-103074.

Journal article
Published: 13 May 2021 in Applied Sciences
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It is expected that large-scale producers of wind energy will become dominant players in the future electricity market. However, wind power output is irregular in nature and it is subjected to numerous fluctuations. Due to the effect on the production of wind power, producing a detailed bidding strategy is becoming more complicated in the industry. Therefore, in view of these uncertainties, a competitive bidding approach in a pool-based day-ahead energy marketplace is formulated in this paper for traditional generation with wind power utilities. The profit of the generating utility is optimized by the modified gravitational search algorithm, and the Weibull distribution function is employed to represent the stochastic properties of wind speed profile. The method proposed is being investigated and simplified for the IEEE-30 and IEEE-57 frameworks. The results were compared with the results obtained with other optimization methods to validate the approach.

ACS Style

Satyendra Singh; Manoj Fozdar; Hasmat Malik; Maria Fernández Moreno; Fausto García Márquez. Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm. Applied Sciences 2021, 11, 4438 .

AMA Style

Satyendra Singh, Manoj Fozdar, Hasmat Malik, Maria Fernández Moreno, Fausto García Márquez. Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm. Applied Sciences. 2021; 11 (10):4438.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar; Hasmat Malik; Maria Fernández Moreno; Fausto García Márquez. 2021. "Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm." Applied Sciences 11, no. 10: 4438.

Journal article
Published: 07 May 2021 in IEEE Access
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The fast globalization of renewable energy-based technologies has enabled its wide speared utilization as well. This has shaped a new prospect of operation in the modern electricity system. But, its dependency on environmental factors leads to an uncertain scenario in the day-ahead electricity market. During this period, compromises are made in the genuine process of expenditure and resources of the producers to offset the capacity that decreases the profits for the producers. In general, a significant variety of scenarios need to be taken into account when describing uncertainty, thereby necessitating the need for techniques of scenario reduction. Therefore, to manage the intractable effects of solar radiation and wind speed instability, the function of the Beta and Weibull distribution of probability is implemented, respectively, and scenarios are minimized using forward-reduction algorithms. Besides, an underestimation and overestimation of the cost function are used to calculate the deviation of renewable influence. Thus, this paper is suggesting a valuable bidding strategy to maximize the remuneration of electricity producers in the presence of rival competitors and the instability of solar and wind energy. This problem has been prepared by taking the benchmark IEEE 30-bus network with and without renewable energy sources, and this problem has been solved by using the Gravitational Search Algorithm. The observations of the outcome demonstrate the appropriateness of the projected bid strategy in the presence of volatility of renewable energy.

ACS Style

Satyendra Singh; Manoj Fozdar; Abdulaziz Almutairi; Saeed Alyami; Hasmat Malik. Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers. IEEE Access 2021, 9, 70221 -70232.

AMA Style

Satyendra Singh, Manoj Fozdar, Abdulaziz Almutairi, Saeed Alyami, Hasmat Malik. Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers. IEEE Access. 2021; 9 ():70221-70232.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar; Abdulaziz Almutairi; Saeed Alyami; Hasmat Malik. 2021. "Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers." IEEE Access 9, no. : 70221-70232.

Conference paper
Published: 26 July 2020 in Algorithms for Intelligent Systems
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The rapid globalization of solar-based technologies has enabled widespread utilization of solar energy. This has created a new prospect of operation in modern power system due to their dependency on environmental factors, which cause uncertain landscape in day-ahead power market. In real-time operations, compromises have been made in cost and power to balance the power which reduces suppliers’ benefits. Therefore, beta probability distribution function is used to handle the adverse impact of solar irradiation uncertainty and scenarios are reduced using forward-reduction algorithm. Moreover, to measure the deviation of solar power, underestimation and overestimation cost function are used. The paper proposes a suitable bidding strategy to maximize the suppliers’ benefit to handle uncertain rivals’ behavior and uncertainty of solar power. The formulated problem is solved by gravitational search algorithm and simulation results are obtained in absence and presence of solar power on IEEE standard 30-bus test system. The obtained result proves the suitability of the proposed bidding strategy in the presence of uncertainty of solar power.

ACS Style

Satyendra Singh; Manoj Fozdar. Supplier’s Strategic Bidding for Profit Maximization with Solar Power in a Day-Ahead Market. Algorithms for Intelligent Systems 2020, 775 -784.

AMA Style

Satyendra Singh, Manoj Fozdar. Supplier’s Strategic Bidding for Profit Maximization with Solar Power in a Day-Ahead Market. Algorithms for Intelligent Systems. 2020; ():775-784.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar. 2020. "Supplier’s Strategic Bidding for Profit Maximization with Solar Power in a Day-Ahead Market." Algorithms for Intelligent Systems , no. : 775-784.

Research article
Published: 10 February 2020 in IET Generation, Transmission & Distribution
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The deployment of renewable energy sources has been rapidly increasing due to environmental constraints but renewable electricity suppliers face an inevitable problem of uncertainty which is caused by the intermittent nature of renewable sources. In real-time operation, compromises have been made in cost and power to balance the power which reduces supplier benefits. Therefore, the functions of Weibull and Beta distribution of probability are used to handle the adverse impact of wind speed uncertainty and solar irradiation, respectively, and scenarios are reduced using the forward-reduction algorithm. Moreover, to measure the deviation of renewable power, underestimation and overestimation cost functions are utilised. This study proposes a suitable double-sided strategic bidding problem as a multi-objective optimisation problem to maximise the profits of suppliers and buyers to minimise uncertainty of rivals and renewable power. The formulated problem is solved by Technique for Order of Preference by Similarity to Ideal Solution along with Gravitational Search Algorithm, and simulation results are obtained in absence and presence of both solar and wind power on IEEE standard 30-bus and 57-bus test systems. The obtained results prove the suitability of the proposed bidding strategy in the presence of uncertainty of solar and wind power.

ACS Style

Satyendra Singh; Manoj Fozdar. Double‐sided bidding strategy for power suppliers and large buyers with amalgamation of wind and solar based generation in a modern energy market. IET Generation, Transmission & Distribution 2020, 14, 1031 -1041.

AMA Style

Satyendra Singh, Manoj Fozdar. Double‐sided bidding strategy for power suppliers and large buyers with amalgamation of wind and solar based generation in a modern energy market. IET Generation, Transmission & Distribution. 2020; 14 (6):1031-1041.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar. 2020. "Double‐sided bidding strategy for power suppliers and large buyers with amalgamation of wind and solar based generation in a modern energy market." IET Generation, Transmission & Distribution 14, no. 6: 1031-1041.

Conference paper
Published: 17 December 2019 in Lecture Notes in Electrical Engineering
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In the assessment of the features of strategic bidding choice issues, this paper proposes a novel procedure that optimizes strategic bidding using Intelligent Gravitational Search Algorithm (IGSA) for profit maximization of power suppliers in an emerging power market. In this paper, two approaches are suggested. One suggests using the inverse agents in the assessment procedure of GSA. It empowers improved investigation of the exploration space and avoids trapping of the solution in a local optimum result. Another is a new gravity constant control procedure to avoid repetitive calculation and enhance the speed of convergence. The suggested procedure has been tested on the IEEE 30-bus system. The experimental solutions of both result qualities in terms of profit and calculation efficiency demonstrate the efficacy and strength of IGSA to other approaches such as Shuffled Frog Leaping Algorithm (SFLA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Monte Carlo (MC).

ACS Style

Satyendra Singh; Manoj Fozdar; Ajeet Kumar Singh. Optimal Strategic Bidding Using Intelligent Gravitational Search Algorithm for Profit Maximization of Power Suppliers in an Emerging Power Market. Lecture Notes in Electrical Engineering 2019, 963 -971.

AMA Style

Satyendra Singh, Manoj Fozdar, Ajeet Kumar Singh. Optimal Strategic Bidding Using Intelligent Gravitational Search Algorithm for Profit Maximization of Power Suppliers in an Emerging Power Market. Lecture Notes in Electrical Engineering. 2019; ():963-971.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar; Ajeet Kumar Singh. 2019. "Optimal Strategic Bidding Using Intelligent Gravitational Search Algorithm for Profit Maximization of Power Suppliers in an Emerging Power Market." Lecture Notes in Electrical Engineering , no. : 963-971.

Conference paper
Published: 17 December 2019 in Green Intelligent Transportation Systems
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The increase in electricity demand has given the Distributed Generation (DG) technology a boost in the power system. DG units are increasing expeditiously and majority of them are connected with distribution network in order to feed power in the local load and network as well. However, in order to do the maximum utilization of DGs few issues have to be discussed. Islanding condition is a standout amongst the most vital issue in this context. This paper discusses the various anti-islanding protection methods followed by a comparison between one of the active method with its improved variant on the basis of certain parameter.

ACS Style

Vikram Singh; Manoj Fozdar; Ajeet Kumar Singh; Satyendra Singh. Analysis of Anti-Islanding Protection Methods Integrated in Distributed Generation. Green Intelligent Transportation Systems 2019, 663 -671.

AMA Style

Vikram Singh, Manoj Fozdar, Ajeet Kumar Singh, Satyendra Singh. Analysis of Anti-Islanding Protection Methods Integrated in Distributed Generation. Green Intelligent Transportation Systems. 2019; ():663-671.

Chicago/Turabian Style

Vikram Singh; Manoj Fozdar; Ajeet Kumar Singh; Satyendra Singh. 2019. "Analysis of Anti-Islanding Protection Methods Integrated in Distributed Generation." Green Intelligent Transportation Systems , no. : 663-671.

Conference paper
Published: 01 December 2019 in 2019 8th International Conference on Power Systems (ICPS)
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A double-sided strategic bidding problem is projected in the developing electricity market as a multi-objective difficulty. The most important aim of this paper is to identify optimal values of bidding coefficients for sellers and buyers of electrical energy to optimize their remuneration in terms of overall profit. When both sellers and buyers of electrical energy are involved in a double-sided bid procedure to maximize their profits, the issue becomes a multi-goal in which two goals are simultaneously optimized. Therefore, in this work, problem of profit maximization of both entities is included as a complex multi-objective problem and solved by a new hybrid solution, it relies on a correspondence to the form of ideal solution (TOPSIS) coupled with a algorithm for gravitational exploration (GSA). The TOPSIS method uses Euclidean geometry to provide a standardized outcome distribution for multi-objective optimization issues and can be used in combination with any recent form of heuristic optimization to choose the best compromising result. The proposed methodology is productively implemented on the system having six electrical energy sellers and two large buyers participating in a single hour trading period. Results obtained using TGSA provide a superior result in terms of higher profits / benefits than other methods like Monte Carlo. The comparison suggests that the TGSA approach is effective and may be a useful tool in multi-objective bidding procedure in day-ahead market for maximizing social welfare.

ACS Style

Satyendra Singh; Manoj Fozdar. Double Sided Bidding Strategy in a Day-Ahead Electricity Market. 2019 8th International Conference on Power Systems (ICPS) 2019, 1 -6.

AMA Style

Satyendra Singh, Manoj Fozdar. Double Sided Bidding Strategy in a Day-Ahead Electricity Market. 2019 8th International Conference on Power Systems (ICPS). 2019; ():1-6.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar. 2019. "Double Sided Bidding Strategy in a Day-Ahead Electricity Market." 2019 8th International Conference on Power Systems (ICPS) , no. : 1-6.

Journal article
Published: 18 September 2019 in TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES
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ACS Style

Satyendra Singh; Manoj Fozdar. Bidding strategy for generators considering ramp rates in a day-ahead electricity market. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 2019, 27, 3868 -3882.

AMA Style

Satyendra Singh, Manoj Fozdar. Bidding strategy for generators considering ramp rates in a day-ahead electricity market. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 2019; 27 (5):3868-3882.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar. 2019. "Bidding strategy for generators considering ramp rates in a day-ahead electricity market." TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 27, no. 5: 3868-3882.

Research article
Published: 25 April 2019 in IET Generation, Transmission & Distribution
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In polistic electricity market structure, each power producers can maximise its profit through bidding strategy. Also, with the advent of renewable generation mostly wind has shaped a new prospect in the bidding process. Although, the wind power output uncertainty, wind power suppliers facing an inevitable uncertainty problem in an emerging power market. To alleviate the adverse impact of this uncertainty on wind power bidding, Weibull distribution is used to model wind power scenarios and the forward-reduction algorithm is utilised to reduce scenarios. Furthermore, an overestimation and underestimation cost function is modelled to measure the deviation of wind power output. The bidding strategy with the inclusion of wind power is proposed in this study to maximise profit. However, the uncertainty of rival's behaviour affects the bidding process, which minimised by utilising the normal probability distribution function. The proposed problem is tested on the IEEE standard 30-bus and 57-bus systems and solved by the gravitational search algorithm (GSA). The results are obtained without and with wind power and shows that the effects of wind power on market clearing price and bidding strategy. Moreover, GSA gives higher market clearing price and net profit as compared with particle swarm optimisation and genetic algorithm.

ACS Style

Satyendra Singh; Manoj Fozdar. Optimal bidding strategy with the inclusion of wind power supplier in an emerging power market. IET Generation, Transmission & Distribution 2019, 13, 1914 -1922.

AMA Style

Satyendra Singh, Manoj Fozdar. Optimal bidding strategy with the inclusion of wind power supplier in an emerging power market. IET Generation, Transmission & Distribution. 2019; 13 (10):1914-1922.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar. 2019. "Optimal bidding strategy with the inclusion of wind power supplier in an emerging power market." IET Generation, Transmission & Distribution 13, no. 10: 1914-1922.

Conference paper
Published: 01 December 2018 in 2018 8th IEEE India International Conference on Power Electronics (IICPE)
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Modern electricity market operates as an oligopolis-tic entity. The power producers earn by supplying power to a local geographical area and providing the ancillary services to the Independent System Operator (ISO). The market imperfection enables the power producer to maximize its profit by unified strategic bidding of both power and ancillary services. Therefore, a suitable bidding strategy is indispensible for power suppliers in the energy and reserve services market. In this paper, the coordinated bidding strategy for competitive power suppliers in an energy and reserve market has been solved using Extended Gravitational Search Algorithm (EGSA). EGSA is based on the notion of oppositional learning where an equal number but opposite agents are generated in the initial search space. The size of search space reduces to half in every iteration based the proximity of solution to an agent or its opposite agent. The proposed method is tested on a test system with six suppliers and results are compared with Gravitational Search Algorithm (GSA) and Refined Genetic Algorithm (RGA) previously reported in the literature.

ACS Style

Satyendra Singh; Manoj Fozdar; Ajeet Kumar Singh. Coordinating Bidding Strategy of Profit Maximization for Competitive Power Suppliers in Energy and Reserve Markets. 2018 8th IEEE India International Conference on Power Electronics (IICPE) 2018, 1 -6.

AMA Style

Satyendra Singh, Manoj Fozdar, Ajeet Kumar Singh. Coordinating Bidding Strategy of Profit Maximization for Competitive Power Suppliers in Energy and Reserve Markets. 2018 8th IEEE India International Conference on Power Electronics (IICPE). 2018; ():1-6.

Chicago/Turabian Style

Satyendra Singh; Manoj Fozdar; Ajeet Kumar Singh. 2018. "Coordinating Bidding Strategy of Profit Maximization for Competitive Power Suppliers in Energy and Reserve Markets." 2018 8th IEEE India International Conference on Power Electronics (IICPE) , no. : 1-6.