• Energy Research

Abstract Photovoltaic (PV) system are the cleanest form of electricity generation and it is the only form with no effect on the environment at all. However, some environmental challenges persist, which must be overcome before solar energy may be used to represent a source of truly clean energy. This paper aims to study the stability and dynamic behavior of a grid-connected environmentally-friendly photovoltaic energy system using the bifurcation theory. This theory introduces a systematic method for stability analysis of dynamic systems, under changes in the system parameters. To produce bifurcation diagrams based on the bifurcation theory, a parameter is constantly changed in each step, using MATLAB and AUTO, and eigenvalues are monitored simultaneously. Considering how the eigenvalues approach the system’s imaginary axis in accordance with the changes in the targeted parameter, the occurred saddle-node and Hopf bifurcations of the grid-connected PV system are extracted. Using the obtained bifurcations, the system’s dynamic stability limits against changes in controlled (controller coefficients) and systematic parameters (such as Thevenin impedance network) are found

In this chapter, turbulent flow of water-based optimization (TFWO) inspired based on whirlpools created in turbulent flow of water is used to solve the maximum power point tracking (MPPT) of photovoltaic systems in partial shading conditions. The TFWO is used to determine the optimal duty cycle of the DC/DC converter with the objective of maximizing the extracted power of the photovoltaic system. The capability of proposed method is evaluated in different patterns of partial shading to achieve global optimal power. The simulation results showed that TFWO is able to track the global maximum power point (GMPP), successfully in PSC and also fast climate changing. The TFWO has a better tracking capability with faster tracking speed and accuracy than particle swarm optimization (PSO) in obtaining the GMPP. Moreover, the results indicate that the use of buck–boost converter led to faster and more accurate access to the global optimal point than the system equipped with boost converter. The results showed that photovoltaic system with boost converter cannot obtain global maximum power in climate changing condition and limited the efficiency of the MPPT algorithm, while the photovoltaic system with buck–boost converter could be tracked GMPP due to its wider operating area.

Abstract This paper examines the optimal design of a hybrid photovoltaic-wind generator system with battery storage (PV-wind-battery) with off-grid and on-grid operation modes. The objective of the study is to supply annual load demand considering environmental emissions and energy generation cost, as well as the cost of load losses. The decision variables include the optimal size of photovoltaic and wind resources, transfer of the power of the inverter to the load, battery storage bank size, and photovoltaic panel angle. The angle is determined optimally using a meta-heuristic algorithm, i.e., the spotted hyena optimisation (SHO), considering minimisation of the objective function and satisfying the constraints. The objective function is defined as the sum of net present cost (NPC) of the system components and load losses and also cost of emissions (TNPC). The constraints are a maximum and minimum size of the system components and also reliability constraint as load interruption probability (LIP). In this study, first, an off-grid PV-wind-battery system was designed without considering emissions; then, an on-grid PV-wind-battery system was designed considering emissions. It was then optimized using SHO. The simulation results indicated that the PV-wind-battery and wind-battery combinations are the best and worst system combinations, respectively, in terms of TNPC and reliability indices. Additionally, the performance of the SHO algorithm was compared with that of the particle swarm optimisation (PSO), and the results proved the superiority of SHO in system design with a lower cost and better reliability indices. Moreover, the results cleared that the TNPC and LIP achieved 1.286 M$ and 0.13%, respectively, which were lower in the on-grid mode of the hybrid PV-wind-battery system designing compared to the results of the off-grid mode with 1.295 M$ and 0.19%. The obtained results showed that reliability can be improved by purchasing power from the network and considering minimisation of emissions in the on-grid operation mode. The impact of increasing the maximum available power of the network (MAPnet) was examined on the hybrid PV-wind-battery system designing. The results confirmed that the system reliability was improved and TNPC decreased by increasing the MAPnet, and vice versa.