Artificial intelligence based solar/diesel hybrid water pumping system

Solar energy powered systems are increasingly being implemented in different areas due to the advances in solar energy technologies. Some of the major areas for solar energy applications include solar water heating, solar electric power generation, and solar water pumping. Solar water pumping has become the most adopted solar energy technology in the last decade. It has been considered as an attractive way to provide water in remote areas. A major advantage of using solar water pumps is that they are naturally matched with solar irradiation since usually water demand is high in summer when solar irradiation has its maximum values. However, solar energy powered systems are weather dependent. In most cases, a solar energy source has to be combined with another energy source to form a hybrid system to overcome the demerits of using solar alone. This thesis provides the detailed design, modelling and analysis of an Artificial Intelligence (AI) based solar/diesel hybrid water pumping system. This research aims to develop an optimization model that uses AI techniques to maximize the solar energy output and manage the energy flow within the solar/diesel hybrid water pumping. Thus, the proposed system is composed of solar photovoltaic modules, battery bank, Variable Speed Diesel Generator (VSDG), Adaptive Neuro-Fuzzy Inference System (ANFIS) based Maximum Power Point Tracking (MPPT) controllers and an Energy Management Controller (EMC). The EMC, which is based on Fuzzy Logic (FL), is responsible for managing the flow of energy throughout the hybrid system to ensure an undisturbed power supply to the water pump. The PV array, battery bank, VSDG are all sized to power a 5Hp DC water pump and the ANFIS based MPPT controllers are proposed for improving the efficiency of PV modules. The modelling of the system components is performed in the MATLAB/Simulink environment. For evaluation of the proposed system, several case scenarios were considered and simulated in the MATLAB/Simulink environment. The simulation results revealed the effectiveness of the proposed ANFIS based MPPT controllers since the controllers were able to extract maximum available power from PV modules for both steady-state and varying weather conditions. The proposed EMC demonstrated the successful management and control of the energy flow within the hybrid system with less dependency on the VSDG. The EMC was also able to regulate the charging and discharging of the battery bank.

Performance Analysis of a Stand-Alone PV/WT/Biomass/Bat System in Alrashda Village in Egypt

This paper presents an analysis and optimization of an isolated hybrid renewable power system to operate in the Alrashda village in the Dakhla Oasis, which is situated in the New Valley Governorate in Egypt. The proposed hybrid system is designed to integrate a biomass system with a photovoltaic (PV), wind turbine (WT) and battery storage system (Bat). Four different cases are proposed and compared for analyzing and optimizing. The first case is a configuration of PV and WT with a biomass system and battery bank. The second case is the integration of PV with a biomass system and battery bank. The third case is WT integrated with biomass and a battery bank, and the fourth case is a conventional PV, WT, and battery bank as the main storage unit. The optimization is designed to reduce component oversizing and ensure the dependable control of power supplies with the objective function of reducing the levelized cost of energy and loss of power supply probability. Four optimization algorithms, namely Heap-based optimizer (HBO), Franklin’s and Coulomb’s algorithm (CFA), the Sooty Tern Optimization Algorithm (STOA), and Grey Wolf Optimizer (GWO) are utilized and compared with each other to ensure that all load demand is met at the lowest energy cost (COE) for the proposed hybrid system. The obtained results revealed that the HBO has achieved the best optimal solution for the suggested hybrid system for case one and two, with the minimum COE 0.121171 and 0.1311804 $/kWh, respectively, and with net present cost () of $3,559,143 and $3,853,160, respectively. Conversely, STOA has achieved the best optimal solution for case three and four, with a COE of 0.105673 and 0.332497 $/kWh, and an NPC of $3,103,938 and $9,766,441, respectively.

An Optimal Tilt Integral Derivative Applied to the Regulation of DC Link Voltage in a Stand-Alone Hybrid Energy System

This paper presents an application of fractional control scheme named Tilt Integral Derivative (TID) to control a stand-alone hybrid energy system composed of a solar photovoltaic (PV) system and a battery bank (BB). A three-level NPC inverter is inserted in order to increase the efficiency of the energy injected into the AC load. Variation in solar radiation or AC load may cause power imbalance, which leads to variation in DC link voltage. As a solution, a buck-boost converter is connected between the DC link and the battery bank to ensures the transfer of energy in both directions. The parameters of TID controller were tuned using a powerful optimization technique known a Genetic Algorithm (GA) by minimizing the Mean Square Error (MSE) used as a performance index. The effectiveness of the proposed TID controller is demonstrated through a comparison with a conventional Proportional-Integral-Derivative (PID) controller, whose parameters are computed by the pidtool function of the Matlab/Simulink tool where the DC link voltage behavior is previously modeled by a capacitor transfer function. The obtained results show that the proposed TID controller provides a stable DC bus with low chattering, regardless of the rapid irradiation and load changes, when compared to a conventional PID controller.

Control of a battery charger for electric vehicles with unity power factor

A nonlinear controller for an electric vehicle battery charger is proposed in this work. The controller allows charging the battery bank with constant current and constant voltage charging profile, while ensuring unity power factor and low distortion in the grid current. A single model is made for the complete system and the controller is designed using interconnection and damping assignment. The proposed controller ensures the closed-loop stability and allows decoupling the system avoiding disturbances in the electric grid and battery bank. The proposal is validated with simulation results.

Enhancing Farm Produce in Punjab through Solar Simulation Model - A Step towards Clean Energy and Green Economy

In Indian context, the state government is providing subsidized electricity to the farmers to lessen their financial burden and to mitigate the challenge arising due to uncertain weather pattern. But the electricity supply has a limitation of timing and in near future the cost of electricity will certainly increase . On the other hand Indian government has launched many schemes to electrify the rural areas using renewable sources. PM KUSUM yojana being the one which aims to provide the solar panel to the farmers in subsidized cost. In this backdrop the proposed scheme is introduced to provide continuous power supply during day time to do the pumping activity and can able to serve light load during night time. The power generated from the solar PV is utilized to supply the load in sunny hour and the excess power is stored in the battery bank for use in later stage when the solar PV alone cannot meet the load demand. The application of battery bank will remove the dependency upon the grid and can be operated in standalone mode. Thus the present work aims to introduce the Solar PV system with battery bank and investigates the Standalone PV option for reliable, continuous and cost-competitive power supply.

New Developed Wind Pumping System

In this paper a new wind pumping system is developed. This system is hybrid between mechanical and electrical wind pumping systems. It combines the advantages of these two systems. The developed wind pumping system consists of wind turbine, special gearbox, DC machine, battery bank, and water pump. Three wind pumping systems have been modeled and then simulated by using MATLAB/SIMULINK. The simulation results show that the developed wind pumping system has the best performance. Thus, the extracted water volume of the developed system is 984.1 m3, where mechanical and electrical systems extract 737.2 and 642.9 m3 respectively.

Hybrid Power System Modelling and Simulation

When two systems are hybridized with the addition of a storage device, the system's reliability increases dramatically. Even in this instance, enough battery bank capacity is necessary to supply electricity to the load on lengthy cloudy and non- days. As a result, in particular geographical places where the environment is acceptable, the appropriate sizing of system components is an important feature of hybrid power system hybrid models of renewable power generation. The planned research will determine whether such non-use is justifiable or whether using hybrid models in particular regions with acceptable conditions would be useful.

Modified Fuzzy Logic MPPT for PV System under Severe Climatic Profiles

Photovoltaic energy is considered highly favorable due to the environment's pleasant nature. After analyzing different maximum power point tracking (MPPT) algorithms, an effective control scheme is proposed to obtain stabilized maximum output power throughout the PV system. Therefore, this article presents an efficient control algorithm for the extraction of maximum power through a PV system under severe climatic drifts. The modified fuzzy logic controller sustains the maximum output power of the system by defining fuzzy rules to control the duty cycle appropriately. A DC-DC boost converter is also modeled to stabilize and maintain output power under variant climatic uncertainties. Furthermore, charging management control is also implemented on lead-acid battery bank to store PV energy for backup usage. It defines charging-discharging time and state of charge for keeping the battery bank healthier.