Sanjoy Debbarma

Bio: Sanjoy Debbarma is an academic researcher from National Institute of Technology, Meghalaya. The author has contributed to research in topics: Automatic Generation Control & Electric power system. The author has an hindex of 10, co-authored 36 publications receiving 689 citations. Previous affiliations of Sanjoy Debbarma include National Institute of Technology, Silchar.

Utilizing Electric Vehicles for LFC in Restructured Power Systems Using Fractional Order Controller

Abstract: Introduction of vehicle-to-grid technology offer electric vehicles (EVs) to participate in different ancillary services under competitive electric market. EVs provide an opportunity to grow new products and services for grid management. Particularly, EVs, which is a new form of distributed energy storage, can be used to compensate the uncontracted power in the local area if the contracts between the market players are violated. This paper presents the participation of EVs for load frequency control (LFC) under deregulated environment along with other conventional sources such as hydro, thermal, and gas turbine units. An aggregate model of EV fleets and improved version of fractional order (FO) controller is provided in all the areas for robust LFC considering bilateral transactions. Flower pollination algorithm, which is one of the new proven nature inspired algorithm employed to choose the optimal parameters of the FO controllers under several scenarios. Numerous simulations are conducted to validate the superiority of the proposed control strategy.

Solution to automatic generation control problem using firefly algorithm optimized IλDµ controller

Abstract: Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as IλDµ controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of IλDµ controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized IλDµ controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed IλDµ controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized IλDµ controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed IλDµ controller is also tested against system parameter variations.

Frequency Regulation in Deregulated Market Using Vehicle-to-Grid Services in Residential Distribution Network

Abstract: Progress in vehicle-to-grid technology opens market for electric vehicle (EV) users to participate in the emergency reliability services, such as frequency regulation (FR). EVs can be considered as a mobile energy storage, which has the potential to compensate the uncontracted power if the contracts between the market players are breached. As all the EVs will be penetrated to the distribution network, distribution power loss along with the power limit of transformer and lines must be incorporated in the EV model. In this paper, the accuracy of conventional EV model is improved by introducing distributed network characteristics to participate in FR under deregulated environment in the presence of diverse transmission links such as ac/dc links. Fractional order plus proportional plus integral plus derivative (FOPID) controller also abbreviated as PI λ D μ controller is used for coordinated control of conventional units and EVs. Flower pollination algorithm is employed to choose the controller parameters under different scenarios. Extensive simulations have been performed to validate the superiority of the proposed control strategy. Obtained results strongly suggest that FOPID controller is far superior to conventional PID controller.

A literature survey on load–frequency control for conventional and distribution generation power systems

Abstract: In this paper an extensive literature review on load–frequency control (LFC) problem in power system has been highlighted. The various configuration of power system models and control techniques/strategies that concerns to LFC issues have been addressed in conventional as well as distribution generation-based power systems. Further, investigations on LFC challenges incorporating storage devices BESS/SMES, FACTS devices, wind–diesel and PV systems etc have been discussed too.

Load frequency control of interconnected power system using grey wolf optimization

Abstract: In this article an attempt has been made to solve load frequency control (LFC) problem in an interconnected power system network equipped with classical PI/PID controller using grey wolf optimization (GWO) technique. Initially, proposed algorithm is used for two-area interconnected non-reheat thermal-thermal power system and then the study is extended to three other realistic power systems, viz. (i) two-area multi-units hydro-thermal, (ii) two-area multi-sources power system having thermal, hydro and gas power plants and (iii) three-unequal-area all thermal power system for better validation of the effectiveness of proposed algorithm. The generation rate constraint (GRC) of the steam turbine is included in the system modeling and dynamic stability of aforesaid systems is investigated in the presence of GRC. The controller gains are optimized by using GWO algorithm employing integral time multiplied absolute error (ITAE) based fitness function. Performance of the proposed GWO algorithm has been compared with comprehensive learning particle swarm optimization (CLPSO), ensemble of mutation and crossover strategies and parameters in differential evolution (EPSDE) and other similar meta-heuristic optimization techniques available in literature for similar test system. Moreover, to demonstrate the robustness of proposed GWO algorithm, sensitivity analysis is performed by varying the operating loading conditions and system parameters in the range of ± 50 % . Simulation results show that GWO has better tuning capability than CLPSO, EPSDE and other similar population-based optimization techniques.

Challenges and Opportunities of Load Frequency Control in Conventional, Modern and Future Smart Power Systems: A Comprehensive Review

Abstract: Power systems are the most complex systems that have been created by men in history To operate such systems in a stable mode, several control loops are needed Voltage frequency plays a vital role in power systems which need to be properly controlled To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance Likewise, the power exchanges between different control areas are controlled by LFC approaches In recent decades, many control approaches have been suggested for LFC in power systems This paper presents a comprehensive literature survey on the topic of LFC In this survey, the used LFC models for diverse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC