Dulal Chandra Das

Bio: Dulal Chandra Das is an academic researcher from National Institute of Technology, Silchar. The author has contributed to research in topics: Microgrid & PID controller. The author has an hindex of 14, co-authored 51 publications receiving 576 citations.

Expeditious frequency control of solar photovoltaic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm

Abstract: This work endeavours to propose an approximate mathematical model of a community based renewable microgrid with solar photovoltaic, biogas and biodiesel generators including battery storage for load frequency studies. It becomes a great challenge to coordinate between generation and load demand of the microgrid as the renewable sources are highly unpredictable and nature dependent. To overcome this issue, the responses of the system are studied under different real-world scenarios of renewable source availabilities and load variations with a maiden approach towards optimising the controller gains using a recent grasshopper optimisation algorithm (GOA) for efficient frequency control. The frequency responses of proposed microgrid are compared with different conventional controllers and some popular optimisation algorithms using MATLAB/Simulink. Finally, proportional-integral-derivative controller with GOA is preferred for the case studies under four cases of source variations with step load perturbation and one case of simultaneous source and load variations. The results of all these five scenarios are found satisfactory in terms of frequency responses and reported in the work.

Proficient load-frequency regulation of demand response supported bio-renewable cogeneration based hybrid microgrids with quasi-oppositional selfish-herd optimisation

Abstract: This is an earliest attempt to study the effective regulation of load-frequency oscillations due to the penetration of renewable generations in bio-renewable cogeneration based hybrid microgrids with demand response (DR) support considering optimal utilisation of resources. The work is a maiden attempt to derive the linearised model of a medium-sized linear-Fresnel-reflector type solar-thermal power unit for load-frequency study in the proposed wind/micro-hydro/biogas/biodiesel generator-based hybrid microgrids, modelling suitable DR strategies for both isolated and interconnected modes. The proposed systems are simulated using MATLAB/Simulink for coordinated source/demand-side management, proposing a novel quasi-oppositional selfish-herd optimisation algorithm in both the modes, incorporating real-time recorded solar/wind data and realistic random loads. Firstly, the oscillations due to renewable-penetrations are reduced efficiently in the isolated microgrid incorporating biodiesel generator and DR supports. Then the study is further extended for interconnected two-unequal hybrid microgrids considering resource availabilities. The system responses are compared in four extreme scenarios of source variations, as well as three variations of DRs without retuning the controllers to study the adaptability of the proposed system. Finally, the system frequency oscillations are regulated satisfactorily by DR support for both the modes.

Comparative performance evaluation of WCA‐optimised non‐integer controller employed with WPG–DSPG–PHEV based isolated two‐area interconnected microgrid system

Abstract: This study endeavours an effective frequency control of renewable-based isolated two-area interconnected microgrid (ICμG) without battery, incorporating wind power generation in area-1, dish-Stirling solar power generation system in area-2 and other common distributed generation systems such as diesel engine driven generator, plug-in hybrid electric vehicle, heat pump and freezer in both the areas. A recently developed heuristic optimisation technique called water cycle algorithm (WCA) is applied to optimally tune the parameters of the non-integer fractional-order proportional-integral-derivative (FOPID) controllers employed with ICμG. Application of WCA-based FOPID controllers in frequency control two-area ICμG without battery is a novel work. The comparative performance analysis of proportional-integral-derivative (PID), PID with filter and non-integer order-based FOPID controller with their gains tuned by particle swarm optimisation (PSO), improved PSO, firefly algorithm and WCA algorithms indicates the superiority of WCA-based FOPID controller's under different case studies (considering different load disturbances, wind speed variation with real data, and solar irradiance) in terms of frequency deviation, tie-line power, and objective function. Furthermore, the sensitivity analysis contemplates that WCA-optimised FOPID controller can withstand ±25% change in synchronising coefficient, +20% change in loading condition and ±25% change in frequency bias constant without resetting the gain values.

Salp swarm algorithm: a comprehensive survey

Abstract: This paper completely introduces an exhaustive and a comprehensive review of the so-called salp swarm algorithm (SSA) and discussions its main characteristics. SSA is one of the efficient recent meta-heuristic optimization algorithms, where it has been successfully utilized in a wide range of optimization problems in different fields, such as machine learning, engineering design, wireless networking, image processing, and power energy. This review shows the available literature on SSA, including its variants, like binary, modifications and multi-objective. Followed by its applications, assessment and evaluation, and finally the conclusions, which focus on the current works on SSA, suggest possible future research directions.

A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications

Abstract: The grasshopper optimization algorithm is one of the dominant modern meta-heuristic optimization algorithms. It has been successfully applied to various optimization problems in several fields, including engineering design, wireless networking, machine learning, image processing, control of power systems, and others. We survey the available literature on the grasshopper optimization algorithm, including its modifications, hybridizations, and generalization to the binary, chaotic, and multi-objective cases. We review its applications, evaluate the algorithms, and provide conclusions.

Expeditious frequency control of solar photovoltaic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm

Abstract: This work endeavours to propose an approximate mathematical model of a community based renewable microgrid with solar photovoltaic, biogas and biodiesel generators including battery storage for load frequency studies. It becomes a great challenge to coordinate between generation and load demand of the microgrid as the renewable sources are highly unpredictable and nature dependent. To overcome this issue, the responses of the system are studied under different real-world scenarios of renewable source availabilities and load variations with a maiden approach towards optimising the controller gains using a recent grasshopper optimisation algorithm (GOA) for efficient frequency control. The frequency responses of proposed microgrid are compared with different conventional controllers and some popular optimisation algorithms using MATLAB/Simulink. Finally, proportional-integral-derivative controller with GOA is preferred for the case studies under four cases of source variations with step load perturbation and one case of simultaneous source and load variations. The results of all these five scenarios are found satisfactory in terms of frequency responses and reported in the work.

Fuzzy-logic based frequency controller for wind farms augmented with energy storage systems

Abstract: Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.