Utility Grid Connection Research Articles

Power quality enhancement of dual stage three phase grid integrated SPV system using sequential neural network-based algorithm

In this paper, a single-layer sequential neural network (SNN) control algorithm has been proposed for managing the power quality (PQ) in the double-stage three-phase grid-integrated solar photovoltaic (SPV) system. The proposed algorithm efficiently extracts the active and reactive fundamental components of the load current, with a higher convergence rate. The extracted reference currents are matched with the sensed source currents to generate gating pulses for the voltage source converter (VSC). To handle power quality issues in distribution networks such as harmonic imbalances, voltage fluctuations (sags/swells), and the need for active and reactive power compensation, the VSC is controlled very precisely. The control algorithm consists of two-stage processes. In the initial stage, the incremental conductance (INC) based DC-DC converter has been incorporated to extract the peak power from the SPV system. In the later stage SNN-based algorithm is used to control the VSC. A 100 KW solar PV system connected to the utility grid has been designed by using a three-leg VSC in the MATLAB/Simulink environment. The system performance has been evaluated by comparing it to existing techniques. The simulation results comfortably meet the requirements of the IEEE-519–2014 and IEEE 1547–2003 standards for utility grid connection.

Economic dispatching of Wind/ photovoltaic/ storage considering load supply reliability and maximize capacity utilization

The asynchrony between wind/photovoltaic complementary power supply and load demand change will affect the stable operation of the microgrid. Considering the stability and economic benefits of micro grid, a multi-objective dispatching model with multi factor constraints is proposed. Firstly, considering the effective utilization of energy storage capacity, the dispatching model is solved based on multiple series exponential iterative optimization (MSIIO) with the micro-objectives of maximum revenue and load supply reliability. Secondly, the logic algorithm of utility grid connection controller is studied according to different operation scenarios in combination with peak load regulation and valley filling dispatching strategy, so that the system can work in island mode or utility grid connection mode. Finally, a virtual simulation system is used to verify the feasibility of the dispatching strategy. Comparing with particle swarm optimization and differential evolution algorithm, the results of MSIIO show that the economic benefit is increased by 4.18%, the capacity utilization rate reached 82.83%.

Simulation of hybrid renewable systems in rural areas

The hybridization of renewable energy resources is a known topic in sustainable technology. Many projects are going on based on the topic. The use of Photovoltaic, wind energy, and other renewable resources can be helpful to optimize the load in the utility grid. Countries like Europe and other western countries have electricity storage, whether the developing countries are still struggling to make sure the stable utility grid connection to the distribution network system. In this research, we would like to discuss the different energy production processes sustainably. As we know, the energy sources are volatile and cannot always assure stable production to keep the requirements or demand properly. We want to use the combination of the sources in a way so that we can make the balance between the demand and the supply system. This research will be an overview in terms of technical and financial sites. Also, by using the different combinations of the Internet of things and data analysis method, we will see the correlation between the different sources and their production. Based on the production data, we can determine the financial feasibility and the outcome of the system. The main problem of renewable energy sources is uncertainty. In terms of wind energy, the velocity is also not stable according to the location. We want to show a predictive model by using the intelligent formula by which we can maintain the hybrid system. The production data from different sources will tell us their contribution to the system. This contribution will help us monitor the system and control which sources have more contribution on the demand side. The predictive model will have consisted of renewable sources such as photovoltaic, wind, utility grid, and inverter systems. In the research, the tool such as Artificial Intelligence can be implemented by sustainable management. The arrangement information is prepared to extricate data and based on resources. The renewable sources data are variant according to their location and it has an impact in terms of energy production. Data acquisition and analysis could help the current technologies such as smart grid, microgrid, and their control systems. This exploration aims to introduce a predictive foundation for the management of enormous volumes of data through large Information instruments (sensors) to help the coordination of environmentally friendly power. The main difference between the conventional electricity system and the renewable energy system is the variability of sources, with conventional sources such as utility grids and diesel generators and renewable sources consisting of photovoltaic (PV), wind, etc.

Evaluation of Coupling PV and Air Conditioning vs. Solar Cooling Systems—Case Study from Jordan

When they were first conceived, solar cooling systems were designed to be cost-effective and environmentally safe alternatives for the majority of the developing nations that are characterised by their hot climates in contrast with the traditional air conditioning systems powered by electricity that is produced from fossil fuel resources. Nevertheless, developments in photovoltaic (PV) and air-conditioning technologies have impacted on the prospects of solar cooling systems. This study examined two different options: a coupled PV and air conditioner system and a solar cooling system (absorption chillers where thermal energy is provided by solar collectors) for a specific developing country located in the Eastern Mediterranean region whose climate is hot and dry (Jordan). The cooling system comprised a pair of cooled multistage compression, both of which were 700 kW, while the PV system’s size was 2.1 MWp, the utility grid connection was a 0.4 kV 50 Hz net meter (2 m) and it was anticipated that 3300 MWh/year would be generated. The solar cooling system operated at a maximum coefficient of performance (COP) of 0.79 and had an actual recorded COP of 0.32 on the site; when the electricity tariff of $0.1/kWh was considered, the respective levelised cost of energy (LCOE) values were $0.9/kWh and $2.35/kWh respectively. The findings indicate that the initial costs for the solar thermal cooling system and the PV system were approximately $3.150M and $3M, respectively. The current value of future cash payments when discounts of 6% per year were applied to the payments for the combination of PV and air conditioning was about $9,745,000, whereas the solar thermal cooling system will not reach the breakeven point at negative $1,730,000. It is clear the absorption chiller did not display economic feasibility, whereas the value for the coupled PV and air-conditioning systems was under $0.05/kWh. In addition to the extensive maintenance needs, the reduced COP and the practicality and feasibility of the solar thermal cooling systems mean these kinds of technologies are under significant pressure to remain competitive when faced with the development of new air conditioning and PV technologies.

Active Node Detection in A Reconfigurable Microgrid using Minimum Spanning Tree Algorithms

<p>Microgrids are the solution to the growing demand for energy in the recent times. It has the potential to improve local reliability, reduce cost and increase penetration rates for distributed renewable energy generation. Inclusion of Renewable Energy Systems (RES) which have become the topic of discussion in the recent times due to acute energy crisis, causes the power flow in the microgrid to be bi-directional in nature. The presence of the RES in the microgrid system causes the grid to be reconfigurable. This reconfiguration might also occur due to load or utility grid connection and disconnection. Thus conventional protection strategies are not applicable to micro-grids and is hence challenging for engineers to protect the grid in a fault condition. In this paper various Minimum Spanning Tree (MST) algorithms are applied in microgrids to identify the active nodes of the current topology of the network in a heuristic approach and thereby generating a tree from the given network so that minimum number of nodes have to be disconnected from the network during fault clearance. In the paper we have chosen the IEEE-39 and IEEE-69 bus networks as our sample test systems.</p>

Design, Simulation and Implementation of Current Fed Isolated Full Bridge DC-DC with Voltage Multiplier for Fuel Cell Grid Applications

Abstract This paper proposes novel current fed converter full bridge isolated DC-DC converter with voltage multiplier and active clamp circuit for fuel cell grid connected applications. The proposed converter is best suited for fuel cells and their interfacing to utility three phase grid. Active clamp concept introduced on the primary side of isolation transformer to reduce the turn-off voltage spikes of full bridge active devices. Innate soft-switching with elongated range can be achieved in the recommended converter by using the parasitic capacitance of MOSFET switches and leakage inductance of the high frequency transformer. Zero Voltage Switching(ZVS) is achieved for all the primary devices which allow greater switching frequency operation and improvement in over-all efficiency of the converter for utility interface. Cost, size and weight of the converter minimizes for the higher switching operation of the converter. Half-wave Cockcroft-Walton Voltage Multiplier (H-W C-W VM) having minimum number of multiplying stages is used on the secondary side of the designed converter in order toget the required DC-link voltage for three phase utility grid connection. The converter's switching frequency is maintained at 100 KHz. This paper is organized as introduction, steady state operation, simulation results with two different cases i.e. full load and half load conditions and finally, test result validation of a 250 Watt experimental setup with the proposed converter.

A Neuro-Fuzzy Controller for Multilevel Renewable Energy System

This paper proposes concept based new topology based seven level inverter with less number of power electronics switches with utility grid connection. This proposed multilevel inverter operates with only eight power electronics switches at their fundamental frequency. This inverter produces seven level output from the input here we considered as a photovoltaic system. The cost, complexity, switching losses is small because of usage of less number of switches. The DC/DC converter receives input from which the three positive output voltages are generated and the multilevel inverter performs as a polarity reversal that provides both the positive and negative cycle output. For further enhancement in the output waveform, the filter circuit can be integrated in the output terminal of the multilevel inverter. This paper also proposed a concept of a neuro-fuzzy controller for controlling the seven level inverters. The simulation results are observed by means of MATLAB simulink toolbox.

Energy management of a microgrid via parametric programming

An energy management system (EMS) for efficient and tractable coordination of distributed energy sources in a residential level microgrid is presented. Sources of energy include renewable (solar photovoltaic and wind turbine), conventional systems (microturbine and utility grid connection) and battery energy storage system. The overall problem is formulated using parametric mixed-integer linear programming (p-MILP) via parameterizations of the uncertain coordinates of the wind and solar resources. This results in a bi-level optimization problem, where choice of the parameterization scheme is made at the upper level while system operation decisions are made at the lower level. The p-MILP formulation leads to significant improvements in uncertainty management, solution quality and computational burden; by easing dependency on meteorological information and avoiding the multiple computational cycles of the traditional online optimization techniques. The problem is solved offline on a day-ahead basis, allowing online implementation to be achieved via real-time system state updates. The proposed parametric programming approach extends the state-of-the-art in microgrid energy management methods, and the simulation evidence its feasibility and effectiveness.

A Novel Neuro-Fuzzy Controller for Multilevel Renewable Energy System

<p>Recently, Development and the utilization of single phase based multilevel inverters has been increased. This paper proposes concept based new topology based seven level inverter with less number of power electronics switches with utility grid connection. This proposed multilevel inverter operates with only eight power electronics switches at their fundamental frequency. This inverter produces seven level output from the input here we considered as a photovoltaic system. The cost, complexity, switching losses are small due to because of usage of less number of switches. The DC/DC converter receives input from which the three positive output voltages are generated and the multilevel inverter performs as a polarity reversal that provides both the positive and negative cycle output. For further enhancement in the output waveform, the filter circuit can be integrated in the output terminal of the multilevel inverter. This paper also proposed a concept of a neuro-fuzzy controller for controlling the seven level inverter. The simulation results are observed by means of MATLAB simulink toolbox.</p>

DG Placements Impact on the Reliability of Typical Industrial Distribution System In Saudi Arabia

Electrical Distribution systems that are usually radially configured with one utility power source are inherently exposed to higher rates of outages and interruptions due to the fact that failures of system components including transformers, breakers and switching devices along with fault conditions caused by different conditions are not preventable but rather improvable. Historically at Saudi Arabia (SA), many industrial and residential distribution networks suffered from the problems incurred by the utility grid connection including equipment failure, low power quality or human, animal and weather conditions. The fact that the large‐size, the growing demand and the cost with the time requirements for enhancements projects have made distributed generation (DG) in all its application, namely, online or backup to play a key role in the residential, commercial and industrial sectors of the power system. In this paper, the value of DG installed as an online power source of typical industrial distribution network at SA (Abqaiq) is quantified by reliability indices that include SAIDI, CAIDI and ENS. The study outcomes will provide power system engineers with the sense of the reliability benefits of DGs penetration and an approach to assess its installations based on different factors such as the size and location.

A Digital Controlled PV-Inverter With Grid Impedance Estimation for ENS Detection

The steady increase in photovoltaic (PV) installations calls for new and better control methods in respect to the utility grid connection. Limiting the harmonic distortion is essential to the power quality, but other requirements also contribute to a more safe grid-operation, especially in dispersed power generation networks. For instance, the knowledge of the utility impedance at the fundamental frequency can be used to detect a utility failure. A PV-inverter with this feature can anticipate a possible network problem and decouple it in time. This paper describes the digital implementation of a PV-inverter with different advanced, robust control strategies and an embedded online technique to determine the utility grid impedance. By injecting an interharmonic current and measuring the voltage response it is possible to estimate the grid impedance at the fundamental frequency. The presented technique, which is implemented with the existing sensors and the CPU of the PV-inverter, provides a fast and low cost approach for online impedance measurement, which may be used for detection of islanding operation. Practical tests on an existing PV-inverter validate the control methods, the impedance measurement, and the islanding detection.