This work endeavours to propose an approximate mathematical model of a community based renewablemicrogrid with solar photovoltaic, biogas and biodiesel generators includingbattery storage for load frequency studies. It becomes a great challenge tocoordinate between generation and load demand of the microgrid as the renewablesources are highly unpredictable and nature dependent. To overcome this issue,the responses of the system are studied under different real‐world scenarios ofrenewable source availabilities and load variations with a maiden approachtowards optimising the controller gains using a recent grasshopper optimisationalgorithm (GOA) for efficient frequency control. The frequency responses ofproposed microgrid are compared with different conventional controllers and somepopular optimisation algorithms using MATLAB/Simulink. Finally,proportional–integral–derivative controller with GOA is preferred for the casestudies under four cases of source variations with step load perturbation andone case of simultaneous source and load variations. The results of all thesefive scenarios are found satisfactory in terms of frequency responses andreported in the work.

The world energy requirement has skyrocketed radically in the past two decades raising concern over energy security and adequacy. Energy resource planning plays a substantial role in the global economy and geopolitics of clean energy to achieve global commitment towards sustainable development. It includes strategic management, control and storage of energy supply. Microgrids contribute another layer to the apparent advantages of renewables by boosting system performance and mitigating energy losses. The prospects of energy resource management with the benefits of a hybrid microgrid are discussed here with a brief review of past research works on challenges encountered in voltage and frequency regulations with low-inertia issues, demand response, renewable system integration with transition conditions, and tuning controllers with metaheuristic optimisation techniques.

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.

This work presents a maiden approach of coordinated frequency control of novel solar tower (ST)‐Archimedes wave energy conversion (AWEC)‐geothermal energy conversion (GEC)‐biodiesel driven generator (BDDG)‐energy storage (ES) units and direct current (DC) links based independent three‐area interconnected microgrid system (ImGS). A recent metaheuristic technique, named butterfly optimisation algorithm (BOA) is applied to obtain the optimal gains of the controllers employed with the ImGS and system participation factors. The dynamic performance of proportional–integral derivative (PID), PID with filter (PIDN), proportional–fractional‐order integral derivative (PFOID) controllers with their gains tuned by different algorithms such as particle swarm optimisation (PSO), firefly algorithm (FA), whale optimisation algorithm (WOA), and BOA have been compared. Further, the effect of ES units and DC links in all the areas is analysed first time in ImGS. The results have established the superiority of the BOA‐based PFOID controllers under different real‐world scenarios in terms of frequency deviation, tie‐line power, and objective functions. Finally, rigorous sensitivity analysis has been conducted to evaluate the superiority of BOA‐optimised PFOID controller towards preserving system stability of ImGS with ±25% change in synchronising tie‐line coefficients and bias values, and +20% change in loading condition without resetting the nominal condition gain values.

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.

This study proposes an earliest approach toward coordinated frequency stabilisation of wind turbine driven generator‐tidal power generation‐biodiesel driven generator‐micro‐turbine generator‐based islanded two‐area interconnected microgrid system with demand response support (DRS) mechanism. A recent bio‐inspired optimisation technique, named yellow saddle goatfish algorithm (YSGA) is employed to optimally tune the controller gains. The comparative dynamic performance of conventional proportional–integral–derivative (CPID), fractional order (FO) PID, dual‐stage PIFOD‐one plus PI [PIFOD‐(1 + PI)] controllers’ parameters optimised by several algorithmic tools such as particle swarm optimisation, firefly algorithmic tool, salp swarm technique and YSGA clearly designates the superiority of YSGA‐PIFOD‐(1 + PI) controller under different scenarios (considering the real‐time recorded wind and load data) in terms of change in frequency, tie‐line power fluctuation and objective function. Furthermore, the impact of the DRS mechanism in both areas is analysed first time under real‐time wind and load disturbances. Finally, the rigorous sensitivity analysis of YSGA‐optimised PIFOD‐(1 + PI) controller has been conducted with the variation of wind turbine driven generator gain, ±30% change in synchronising tie‐line factor, frequency bias value, microgrid system time constant and + 30% change in loading magnitude without retuning the optimal base condition values.