Control of the photovoltaic emulator using fuzzy logic based resistance feedback and binary search

Photovoltaic (PV) emulator is a power supply that produces similar currentvoltage (I-V) characteristics as the PV module. This device simplifies the testing phase of PV systems under various conditions. The essential part of the PV emulator (PVE) is the control strategy. Its main function is to determine the operating point based on the load of the PVE. The direct referencing method (DRM) is the widely used control strategy due to its simplicity. However, the main drawback of DRM is that the output voltage and current oscillate due to the inconsistent operating point under fixed load. This thesis proposes an improved and robust control strategy named resistance feedback method (RFM) that yields consistent operating point under fixed load, irradiance and temperature. The RFM uses the measured voltage and current to determine the load of the PVE in order to identify the accurate operating point instantaneously. The conventional PV models include the I-V and voltage-current PV model. These PV models are widely used in various control strategies of PVE. Nonetheless, the RFM requires a modified PV model, the current-resistance (I-R) PV model, where the mathematical equation is not available. The implementation of the I-R PV model using the look-up table (LUT) is feasible, but it requires a lot of memory to store the data. A mathematical equation based I-R PV model computed using the binary search method is proposed to overcome the drawback of the LUT. The RFM consists of the I-R PV model and the closed-loop buck converter. In this work, the RFM is investigated with two different controllers, namely the proportional-integral (PI) and fuzzy logic controllers. The RFM using the PI controller (RFMPI) and the RFM using the fuzzy logic controller (RFMF) are tested with resistive load and maximum power point tracking (MPPT) boost converter. The perturb and observe algorithm is selected for the MPPT boost converter. In order to properly design the boost converter for the MPPT application, the sizing of the passive components is proposed, derived and confirmed through simulation. This derivation allows adjustment on the output voltage and current ripple of the PVE when connected to the MPPT boost converter. The simulation results of the proposed control strategies are benchmarked with the conventional DRM. To validate the simulation results, all controllers are implemented using dSPACE ds1104 rapid prototyping hardware platform. The RFM computes an operating point of the PVE at 20% faster than the DRM. The generated output PVE voltage and current using RFMPI and the RFMF are up to 90% more accurate compared to the DRM. The efficiency of the PVE is beyond 90% when tested under locus of maximum power point. In transient analysis, the settling time of RFMF is faster than the RFMPI. In short, the proposed RFMF is robust, accurate, quick respond and compatible with the MPPT boost converter

Sizing of energy storage based on loss of load probability of standalone photovoltaic systems

If the standalone PV system is optimally design, it can be cost effective and reliable. This process is called optimal sizing, which focused on finding the lowest cost for the PV system at the acceptable reliability. The project is focused on finding the optimum configuration for PV system at FKE Building, UTM, Johor. The configuration consists of two components; number of PV arrays and number of battery. By manipulating these two components, the reliability of the PV system can be controlled. For this project, the reliability is measured using Lost of Load Probability (LOLP) concept for one year duration. The LOLP of the system is calculated for every configuration starting from one PV array and one battery until 100 PV arrays and 100 batteries. The project used 0.1 LOLP as the reliability level, which means only 10% of the total energy demand could not be satisfied by the PV system. Out of the configurations that meet the 0.1 LOLP, the most cost effective configuration needs to be determined. For this project, two methods are used for the optimal sizing; Graphical Construction Method (GCM) and Life Cycle Cost (LCC) analysis. GCM is focus on finding the optimal size of the system depending on the initial cost of the PV arrays and batteries, while LCC analysis considered all the cost throughout the entire project

Computation of current-resistance photovoltaic model using reverse triangular number for photovoltaic emulator application

PV emulator (PVE) is a power supply that produces similar current‑voltage (I‑V) characteristic as the PV module. It simplifies the testing of the PV system during the development phase. Since the output voltage and current of the PVE change based on various factors (load, irradiance and temperature), the computation of the operating point for the PVE is crucial. The resistance feedback control strategy is a robust and fast approach to find the operating point for the PVE. Nonetheless, it uses an uncommon current‑resistance PV model, which cannot be computed using the conventional approach. This work introduces the reverse triangular number to compute the PV model and obtained the operating point of the PVE. The reverse triangular number is based on the variable step sizes that allow fast computation of the PV model. The operating point is then used by the PI controller and the buck converter to produce the output voltage and current similar to the PV module. The results show that the reverse triangular number is able to compute the PV model accurately. In addition, the proposed PVE not only works well with resistive load but adapts accurately under the integration with maximum power point tracking converter

Minimizing power loss considering bulk uncoordinated charging station operation

The widespread usage of electric vehicles (EV) carries a negative impact on the distribution network. Higher penetration of uncoordinated charging station (CS) that used to charge the EV may boost the capacity of demand, especially during off-peak. Next, an increase in power loss may occur since the bulk operation of CS causes a higher power flow at existing networks. Furthermore, the CS varying demand usually challenging to handle, uniquely for the load that has various behaviour. From repetitious researchers, the CS operation often installs at the residency, parking lot and specific station. Then, the charging power requirement is different between EV's, which depend on battery size and characteristic. This research focuses on power loss parameters at the distribution network for uncoordinated CS operation. The analysis will be based on the 48-bus radial distribution system with two residential blocks using MATLAB environment. Then, suitable sizing and placement of multiple passive filters used to minimize power loss with assistance metaheuristic technique and multi-objective approach. From the result, propose method able to improve up to 8.03% compared to existing power loss after implement optimal sizing and placement of passive filter. The proposed method is useful to assist utility owner in reducing power loss issues at a distribution system that cause by extensive uncoordinated CS operation

Switching modulation strategies for multilevel inverter

There is always a need to create efficient and optimized converters to deliver the best possible results to achieve a better THD profile in the waveform output. One way is by controlling the switching of the power switches of the converters using appropriate modulation schemes. While numerous works have been done in proposing new switching modulation strategies for multilevel inverters, this work will compare multicarrier PWM and near-to-level control (NLC) modulation schemes. In this paper, multicarrier PWM variants, namely, PD-PWM, POD-PWM, and APOD-PWM, are designed and simulated. Their voltage THD and spectrum performance are discussed when applied to single-phase 7, 9, and 11-level cascaded multilevel inverters. Then NLC modulation will be designed and applied to similar multilevel inverter circuits. It will be shown that the NLC exhibits some superior performances compared to PWM-based but with several drawbacks that can be optimized

A review of the smart grid communication technologies in contactless charging with vehicle to grid integration technology

Power needs to be transferred from the source to the load (electric vehicle). Transmitting electricity through the air gap for charging using electromagnetic waves as one of the smart grid technologies called Wireless Power Transfer (WPT), or Inductive Power Transfer. This paper presents the fulfilment of future gird that addresses the issues of Greenhouse Gas emission, and transportation and industries emissions known as the smart grid with a complex system. The complexity of the smart grid communication system is the motivation to be an open area of research issue. The main contribution of this paper is to close the gap between this research and other researches by delivering a comprehensive review and update the recent state-of-the-art of smart grid communication technologies with the integration of vehicle-to-grid (V2G) technology using the contactless charging method. Smart grid communication technologies with their pros and cons, topologies of wireless communication, challenges of the V2G, WPT challenges, and standards are discussed. Therefore, this study is expected to be a significant guide to engineers and researchers studying in the field of smart grid communication technologies and contactless charging for electric vehicles

Energy management strategy and capacity planning of an autonomous microgrid: Performance comparison of metaheuristic optimization searching techniques

Electricity generation using renewable energy-based microgrid (REM) is a prerequisite to achieve one of the objectives of sustainable development goal (SDG 7- Affordable and Clean Energy). Nonetheless, the optimum design of the REM is challenging due to fluctuating demand and intermittent nature of the renewable energy sources. The optimum sizing of the REM is also associated with several non-convexities and nonlinearities, thereby precluding the application of deterministic optimization searching techniques for the sizing problem. This paper, therefore, proposes a rule-based algorithm and metaheuristic optimization searching technique (MOST) for the energy management (EM) and sizing of an autonomous microgrid, respectively. The purpose of the energy management scheme (EMS) is to provide power delivery sequence for the different components that compose the microgrid. Afterward, the EMS is optimized using MOST. For benchmarking, the paper compares the success of six different MOSTs. The simulation is performed for the climatic conditions of Maiduguri, Nigeria. The comparative results indicate that grasshopper optimization algorithm yields a better result relative to other studied MOSTs. Remarkably, it outperforms the grey wolf optimizer, the ant lion optimizer, and the particle swarm optimization by 3.0 percent, 5.8 percent, and 3.6 percent (equivalent to a cost savings of $8332.38,$4219.87, and $5144.64 from the target microgrid project). Results also indicate that the EMS adopted for the control of the microgrid has led to the implementation of a clean and affordable energy system. Moreover, the proposed microgrid configuration has minimized CO2 emission (by 92.3 %) and fuel consumption (by 92.4 %), when compared to the application of a fossil fuel-based diesel generator

Sizing of standalone photovoltaic-thermoelectric cogeneration system using particle swarm optimization

This study aims to optimize a Photovoltaic-Thermoelectric standalone system with a battery storage system at the lowest cost of the system and acceptable reliability using particle swarm optimization algorithm (PSO). For this purpose, a comprehensive rule-based power management mechanism is proposed, which will coordinate the energy flow among the different system components that make up the stand-alone system. Following that, investigation and confirmation of the proposed PSO performance are carried out to determine the system’s optimum size. The proposed method’s ultimate objective is to minimize the cost of energy (COE) and the Loss of Power Supply Probability (LPSP). The proposed system is intended to meet the energy requirements of the FKE Building at UTM in Johor. This project takes annual temperature, solar irradiance, and load profile into account. The proposed PSO’s effectiveness in addressing the optimization problem is evaluated, and its performance is compared to the Iterative technique (IT) Algorithm. The suggested optimization methods are implemented in MATLAB via the simulation package. The simulation results demonstrate that PSO is capable of sizing the system optimally in comparison to Iterative technique (IT) algorithm. As result, the comparison of the algorithms reveals that PSO performed a superior result since it has the lowest COE (objective function), at RM0.5812/kW h, as compared to the iterative technique (IT) at RM0.5846 kW h, for the desired LPSP of 1%

A novel photovoltaic emulator based on current-resistor model using binary search computation

The Photovoltaic (PV) emulator is a nonlinear power supply that produces a similar Current-Voltage characteristic of the PV module. This equipment simplifies the testing phase when developing the PV generation system such as the Maximum Power Point Tracking (MPPT) converter and PV inverter. However, the conventional control strategy used in the PV emulator, the Direct Referencing Method, is highly dependable on the parameters of the power converter circuit and the Proportional-Integral (PI) controller. As a result, the output voltage oscillates and becomes inaccurate at certain load conditions. In this paper, a new control strategy based on the Current-Resistance (I-R) PV model combined with the Binary Search Method is introduced. The I-R PV model is derived based on the single diode model. The closed-loop buck converter system with the current-mode controlled and the PI controller are used in the PV emulator system. The load of the PV emulator consists of the resistive load and the MPPT converter. The results obtained from the proposed control strategy are compared with the conventional Direct Referencing Method. The results show the proposed control strategy produces a more reliable operating point, a higher accuracy, and a faster transient response compared to the conventional Direct Referencing Method