Showing papers by "Dulal Chandra Das published in 2018"

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.

Active power management of isolated renewable microgrid generating power from Rooftop solar arrays, sewage waters and solid urban wastes of a smart city using Salp swarm algorithm

Abstract: This work is a maiden attempt to manage the active power of an isolated renewable microgrid with Rooftop solar arrays, Micro-hydro generator, Biomass fired combined heat and power, Aqua-electrolyzer, and Fuel cells, by optimized load frequency control using a recent Salp Swarm Algorithm. The effort has put on to propose the mathematical model of a renewable microgrid generating power from solar irradiances, urban solid wastes, and sewage waters of a smart city like Bhubaneswar, for a dual objective of power and waste management. The importance of choosing the above combination of resources for microgrid is the effective co-compensation with climatic changes between solar PV and micro-hydro units naturally. Since sufficient solar energy is available during summer, but the water potential reduced subsequently for micro-hydro power generation. In other hands, during monsoon, water potential is highly available as rainwater adds to the sewage, but there are insufficient sunrays for PV units. The Biomass-based CHP is considered to give support to microgrid during non-availability of solar energy. It becomes a great challenge to coordinate between generation and load demand efficiently with the considered sources of renewable energy due to their inherent dependency towards climatic variations. To overcome this issue, the responses of the system are studied for different scenarios of renewable sources availability and load changes for optimal frequency control. The proposed microgrid is simulated with MATLAB-Simulink for four different scenarios and the optimized responses are reported to be competent in maintaining power frequency within the acceptable limit.

Plug in hybrid vehicle-wind-diesel autonomous hybrid power system: frequency control using FA and CSA optimized controller

Abstract: Large integration of renewable energy in hybrid power system in isolated mode of operation make frequency control a challenging task. This paper investigates the performance of Cuckoo Search Algorithm (CSA) and Firefly Algorithm (FA) based frequency control strategy of such a hybrid power system, which is a unique work. The generating units of the system are plug in hybrid vehicle (PHEV), wind turbine generators, a diesel engine generator (DEG) and battery energy storage system (BESS). The proportional plus integral (PI)/proportional integral derivative (PID) controllers are employed with PHEV, DEG and BESS to adjust the total active power generation in accordance to the load demand. Addition of PHEV reduces the reliance on the DEG or BESS as a result of variability and uncertainty of wind power. Different disturbance conditions such as step perturbations, random variations of load as well as wind output power, have been considered in the case studies under Matlab simulation to assess the performance of CSA and FA based control strategy. Analysis indicates that CSA based PID controller provides better response compare to GA, PSO and FA based PI/PID controller and CSA based PI controller. Sensitivity analysis has been carried out to check the robustness of FA and CSA optimized PI/PID controller gains.

Parabolic trough solar–thermal–wind–diesel isolated hybrid power system: active power/frequency control analysis

Abstract: This study investigates the frequency control of an isolated hybrid power system (HPS) in the presence of parabolic-trough solar thermal power system (STPS), wind generator, diesel engine generator and battery energy storage system to ensure the system reliability. Dynamic performance of the HPS has been analysed considering the degree of penetration of solar thermal power. The inclusion of parabolic-trough-based STPS in such study is a maiden work. For coordinated control of the whole system and to damp out the oscillations occurring due to the disturbances, proportional-integral (PI) and PI-derivative controllers are incorporated whose gain parameters are simultaneously optimised by genetic algorithm, particle swarm optimisation, and mine blast algorithm (MBA). MBA-based control strategy in such a hybrid system has been reported for the first time. The dynamic response analysis with different algorithms figured out that the parameters of controllers tuned by MBA provide a significant improvement in the performance of HPS.

LFC for Autonomous Hybrid Micro Grid System of 3 Unequal Renewable Areas using Mine Blast Algorithm

Abstract: This paper ensures the feasibility of the proposed 3-area hybrid micro grid system (3A-HµGS) comprising of highly intermittent energy sources like wind turbine generator (WTG), parabolic trough collector (PTC), and PV arrays. Renewable energy sources (RES) inherently set in power and frequency oscillations as these sources (RES) are extremely influenced by climatic behavior that’s why the erection of 3A-HµGS as a controlled dispatch able unit is in fact very difficult to be realized but this proposed system has considered diesel engine generator (DEG) as a back-up source and the energy storage system (ESS) like battery, ultra-capacitor and fuel cell as the dynamic devices to make it controllable and reliable. Unwanted frequency deviation has been restricted to a satisfactory limit through GA, PSO and MBA based proportional integral derivative (PID), proportional integral derivative with filter (PIDN) and 2 degree of freedom PID (2DOF-PID) controllers. MBA based 2DOF-PID controllers provide the best coordination among RES, ESS, and DEG to maintain the power quality of 3A-HµGS. A qualitative and quantitative analysis of the dynamic responses under all the controlling actions clearly exhibits the efficacy of the proposed system. Moreover, the system remains stable even after incorporation of natural disturbances like change in wind velocity and solar irradiances which ensure the feasibility and practicality of the proposed 3A-HµGS.

Integrated Demand Side Management and Generation Control for Frequency Control of a Microgrid Using PSO and FA based Controller

Abstract: This paper applies demand side management (DSM) method as a new control strategy for frequency control in a microgrid powered by the diesel driven generator (DDG), wind and solar photovoltaic (PV) power sources. In order to level the frequency fluctuation due to intermittent power generation, the power consumption of the non-critical loads (i.e., heat pump, freezer) and power charging-discharging of plug-in hybrid vehicles (PHEV) are controlled through the controllers (PI/PID). The parameters of the controllers are optimized using Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). Different disturbance conditions such as step perturbation and random variations of load, solar PV and wind output power has been considered to investigate the performance of the microgrid. Simulation studies confirmed that the performance of the FA optimized PID controller is better than the PSO optimized PI/PID controllers and FA optimized PI controller in terms of frequency deviation and setting time.

Optimal Load-frequency Regulation of BioRenewable Cogeneration based Interconnected Hybrid Microgrids with Demand Response Support

Abstract: This work is an earliest attempt to study the load-frequency regulation of Wind, Solar-thermal, Microhydro, Biogas, and Biodiesel generating unit based interconnected hybrid microgrids with Demand response support. The linearized models of each renewable units are established for the proposed interconnected two-unequal hybrid microgrid system along with demand response strategies. The load-frequency responses of the proposed system are studied using Particle swarm optimization tuned classical PID controllers for different scenarios of source and load variations. Initially, the responses of system with microhydro and biogas units, are studied, subsequently connecting Wind and Solar-thermal units, which witness the increment in oscillations with penetration of renewable units. Then, the oscillations are reduced optimally by the inclusion of biodiesel generator and demand response supports. Finally, the responses are studied for simultaneous variations in renewable-sources and load-demands, reporting satisfactory regulation of load frequency with demand response contributions.

Performance Analysis of CSA Optimized PIDF Controller for Containing Frequency Fluctuation of Micro-Grid

Abstract: Integration of renewable power generation in the modern power system requires intelligent and flexible control to ensure the balance between the generation and load demand. This paper addresses a frequency control model of an isolated micro-grid with plug-in hybrid electric vehicle (EV) and heat pump (HP) supplied by diesel engine generator (DEG) and renewable solar thermal power generation (STPG). Due to the interconnection of intermittent energy source like STPG and load variation, the micro-grid frequency fluctuate with different adverse effect on the power system. The PID and PID with filter (PIDF) are employed with EV, DEG and HP to control their power generation to maintain the desired frequency level under different contingencies. The parameters of PID and PIDF controllers are controllably tuned by Cuckoo search algorithm (CSA) for containing frequency fluctuation and their performances are compared thereafter. Different disturbed conditions have been realized in the form of step perturbations and random variations on the load and generation side. Investigation of the responses shows that Cuckoo search algorithm (CSA) based PIDF controller gives better response compare to the Cuckoo search algorithm (CSA) based PID controller.