A SSA-based CFFOPID drop deloaded tidal turbine controller using HVDC-link.

In contemporary scenario, electric power companies have observed upsurge in penetration level of tidal power plants (TPPs) in the traditional electric power system framework. However, the tidal turbines offer less frequency assistance due to their lesser rotor mass. Hence, TPPs may be collaborated with conventional units like diesel engine generator (DEG) to confirm system frequency stability in multi-area micro-grid system. The DEG comprises of primary and proportional integral derivative (PID) secondary frequency controls. However, in TPPs, to advance the system frequency regulation, deloading control approach is suggested and a cascade fuzzy fractional order PID-ID with derivative filter (CFFOPID-IDF) droop controller is suggested in place of the conventional non-cascade controller droop in the deloaded region. The suggested controller gains are fetched exploiting Salps swarm algorithm. For further enhancement of the dynamic responses, a precise high voltage direct current (AHVDC) link with the inertia emulation-based control (INEC) scheme is adopted, which allows the utilization of the gathered energy from the capacitance of the HVDC interface for frequency regulation. It provides better results compared to conventional AC tie line interface having less undershoot (34 %/20.63 %/43.75 %) and settling time (20.45 %/59.09 %/16.83 %) for variation in area-1 frequency/area-2 frequency/tie line power, respectively. The recommended control scheme is evidenced superior over numerous existing control techniques and provides least cost function in contrast to other control techniques. Additionally, it offers a highly stable performance under variable load conditions.

Metal-free adsorption and photodegradation methods for methylene blue dye removal using different reduction grades of graphene oxide.

The release of organic pollutants and dyes into the environment by industries has had profound and harmful effects on both humans and ecosystems. Graphene oxide (GO) and its reduced form have been investigated for their effectiveness in removing pollutant dyes. GO nano-powder was synthesized using an improved version of Hummer's method and subsequently thermally reduced at various temperatures, including 125, 150, 175, and 200 °C, under vacuum conditions. In the X-ray diffraction spectra, an intense (001) diffraction peak was initially observed at 9.136° (2θ) for pristine GO. This peak gradually shifted towards higher angles as the reduction process took place and eventually disappeared when the GO was reduced at 200 °C. The intensity ratio of the D and G bands (ID/IG ratio) for GO nano-powder in the Raman spectra decreased from 0.94 to 0.76 due to the reduction process. The FTIR spectra of GO and reduced graphene oxide (rGO) also illustrated the reduction process. The bandgap of pristine GO significantly decreased from 2.31 to 0.73 eV, as determined by ultraviolet-visible (UV-Vis) diffuse reflectance spectrophotometry during the reduction process. The surface area and pore volume of both pristine GO and rGO-150 were determined using the BET (Brunauer-Emmett-Teller) and BJH (Barrett-Joyner-Halenda) methods. The results indicated an increase in the BET surface area from 6.61 to 7.86 m2/g and a corresponding enhancement in pore volume from 0.118 to 0.128 cc/g after reduction. The adsorption and photocatalytic degradation behavior of pristine GO and reduced graphene oxides (rGOs) were examined using methylene blue dye. The pristine GO demonstrated impressive adsorption capability, effectively removing the dye by 85.78 % within just 15 min and achieving nearly 97 % removal after 4 h. In contrast, the highest photocatalytic degradation of methylene blue, about 47.58 %, was attained for the rGO sample reduced at 150 °C under the illumination of visible light.

Optimal planning and designing of microgrid systems with hybrid renewable energy technologies for sustainable environment in cities.

Although hybrid wind-biomass-battery-solar energy systems have enormous potential to power future cities sustainably, there are still difficulties involved in their optimal planning and designing that prevent their widespread adoption. This article aims to develop an optimal sizing of microgrids by incorporating renewable energy (RE) technologies for improving cost efficiency and sustainability in urban areas. Diverse RE technologies such as photovoltaic (PV) systems, biomass, batteries, wind turbines, and converters are considered for system configuration to obtain this goal. Net present cost (NPC) is this study's objective function for optimal sizing microgrid configuration. For demonstration, we assess the technical, economic factors, and atmospheric emissions of optimal hybrid renewable energy systems for Putrajaya City in Malaysia. The required solar radiation data, temperature, and wind speeds are collected from the NASA surface metrological database. From the quantitative analysis of simulations, the biomass-battery-based system has optimal economic outcomes compared to other systems with an NPC of around 1.07 M$, while the cost of energy (COE) is 0.118 $/kWh. Moreover, environmentally safe nitrogen oxide emissions, carbon monoxide, and carbon dioxide concentrations exist. The grid-tied RE technology boasts cost-effectiveness, with an NPC of 348,318 $ and a COE of 0.0112 $/kWh. This study aids decision-makers in formulating policies for integrating hybrid RE systems in urban areas, promoting sustainable energy generation.

Tidal turbine support in microgrid frequency regulation through novel cascade Fuzzy-FOPID droop in de-loaded region.

The goal of this study is to introduce an effective load frequency control scheme with the integration of tidal turbines in a standalone microgrid (µG) system. As standalone µG experiences lower inertia and lacks primary frequency control, the use of variable tidal turbines in the de-loaded region may be accepted as one of the feasible solutions for managing frequency regulation issues. In this condition, the de-load region alludes to an area where tidal turbines liberate their accumulated kinetic energy in rotational parts pursuing frequency fluctuations. An effectual cascade fractional order fuzzy PID-integral double derivative (CFOFPID-IDD) controller suggested for efficient utilization of tidal turbines, whose design variables are tuned through a recently appeared Jaya algorithm. An investigation is made between the acquired outcomes of the studied CFOFPID-IDD droop controller with fractional order fuzzy PID droop control to analyze the proposed strategy performance in various load conditions, with different physical constraints like time delay, dead zone, and generation rate constraints. Moreover, the sensitivity test reveals that the Jaya-optimized CFOFPID-IDD controller can undergo ± (10-25) % variation in various coefficients without retuning the design variable values. The simulation outcomes validate the effectiveness and adequacy of the proposed regulator.

A novel CFFOPI-FOPID controller for AGC performance enhancement of single and multi-area electric power systems.

The modern power system (PS) is an intricate manmade control system. Automatic generation control (AGC) executes an imperative contribution in PS operation to preserve its frequency and tieline power flow within a tolerable range following continuously varying load demands. Hence, a wholesome and expert controller for AGC is obligatory to deliver superior power to the end users. The objective of this article is to design a cascaded fuzzy fractional order (FO) PI-FOPID (CFFOPI-FOPID) controller as a novel control strategy for AGC problem solution in electric PS. The controller parameters are determined employing a recent stochastic imperialist competitive algorithm. The controller assures the convergence of deviation in area frequency and tieline power under load disturbances to zero in minimum definite time. Single and interconnected multi-area thermal PS models are utilized as test systems to authorize the efficacy of the method. Results analysis reveals the advantage of CFFOPI-FOPID​ controller over various prevalent controllers. The models are also explored with appropriate generation rate constraint. Robustness test validates controller's robustness at large changes in system parameters, random change in power demand and additional imperative nonlinearities.

Improvement in automatic generation control of two-area electric power systems via a new fuzzy aided optimal PIDN-FOI controller.

Automatic generation control (AGC) executes a vital role to supply quality power in an interconnected power system. To cultivate good quality of power supply via preserving area frequency and tie-line power oscillations following consumer's load demand disturbances, the controller designed for AGC of power system should display excellent disturbance rejection expertise. Hence, in this paper, a maiden attempt is made to propose a fuzzy aided integer order proportional integral derivative with filter-fractional order integral (FPIDN-FOI) controller for AGC of multi-area power systems. A more recent intelligent optimization technique termed as imperialist competitive algorithm (ICA) is fruitfully employed for concurrent tuning of various parameters of the proposed controller. It is observed from the simulation results that the proposed FPIDN-FOI controller outperforms the various existing control strategies and PID/PIDN/FPIDN controller designed in the study for five different power system models. Effect of variation in fractional order value of integral on the system performance is analyzed. A sensitivity analysis is conducted to test the robustness of the designed controller under variations in the system parameters, load demands and existence of the system nonlinearities. It is perceived that the proposed controller is robust and executes adequately under variations in system parameters, random load disturbance patterns and nonlinearities.