scholarly journals Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2929
Author(s):  
Rami Alamoudi ◽  
Osman Taylan ◽  
Mehmet Azmi Aktacir ◽  
Enrique Herrera-Viedma
Keyword(s):  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Hospital Performance ◽  
System Capacity ◽  
Design Parameters ◽  
System Response ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Inference System

One of the most favorable renewable energy sources, solar photovoltaic (PV) can meet the electricity demand considerably. Sunlight is converted into electricity by the solar PV systems using cells containing semiconductor materials. A PV system is designed to meet the energy needs of King Abdulaziz University Hospital. A new method has been introduced to find optimal working capacity, and determine the self-consumption and sufficiency rates of the PV system. Response surface methodology (RSM) is used for determining the optimal working conditions of PV panels. Similarly, an adaptive neural network based fuzzy inference system (ANFIS) was employed to analyze the performance of solar PV panels. The outcomes of methods were compared to the actual outcomes available for testing the performance of models. Hence, for a 40 MW target PV system capacity, the RSM determined that approximately 33.96 MW electricity can be produced, when the radiation rate is 896.3 W/m2, the module surface temperature is 41.4 °C, the outdoor temperature is 36.2 °C, the wind direction and speed are 305.6 and 6.7 m/s, respectively. The ANFIS model (with nine rules) gave the highest performance with lowest residual for the same design parameters. Hence, it was determined that the hourly electrical energy requirement of the hospital can be met by the PV system during the year.

scholarly journals Research Survey on Different MPP Tracking Optimization Algorithms for Solar Photovoltaic System (SPS)

2021 ◽  
Vol 12 (6) ◽  
pp. 2666-2671
Author(s):  
R. Mohan Kumar, Dr. C. Kathirvel
Keyword(s):  
Renewable Energy ◽  
Direct Method ◽  
Renewable Energy Sources ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Operating Efficiency ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Solar Pv System

Due to increase in global warming, it is required to choose an alternative renewable energy source for the electricity generation. Among various renewable energy sources (RES), photo-voltaic energy is one of the most accessible source of energies. But the conversion rate of solar PV cell is about 25 % to 40 % of solar irradiation level. In Solar Photovoltaic (PV) system, to improve and maximize the operating efficiency level, Maximum Power Point Tracking (MPPT) techniques were required. Because of the change in the level of solar irradiance, and the nature of dynamic temperature, this MPP tracking will be highly important to make the solar PV system (SPS) to operate at higher efficiency level. This MPPT method is mainly categorized into three different types such as direct method, indirect method and intelligent method. This paper will gives and overview about various MPPT methods employed for solar PV system. Various controlling algorithms were discussed in this section for a better understanding.

scholarly journals Neuro-Fuzzy-Based Model Predictive Energy Management for Grid Connected Microgrids

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 900 ◽  
Author(s):  
Ahsen Ulutas ◽  
Ismail Hakki Altas ◽  
Ahmet Onen ◽  
Taha Selim Ustun
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Technology Use ◽  
Energy Use ◽  
Renewable Energy Sources ◽  
Solar Irradiation ◽  
Pv System ◽  
Inference System ◽  
Management Algorithm ◽  
Neuro Fuzzy

With constant population growth and the rise in technology use, the demand for electrical energy has increased significantly. Increasing fossil-fuel-based electricity generation has serious impacts on environment. As a result, interest in renewable resources has risen, as they are environmentally friendly and may prove to be economical in the long run. However, the intermittent character of renewable energy sources is a major disadvantage. It is important to integrate them with the rest of the grid so that their benefits can be reaped while their negative impacts can be mitigated. In this article, an energy management algorithm is recommended for a grid-connected microgrid consisting of loads, a photovoltaic (PV) system and a battery for efficient use of energy. A model predictive control-inspired approach for energy management is developed using the PV power and consumption estimation obtained from daylight solar irradiation and temperature estimation of the same area. An energy management algorithm, which is based on a neuro-fuzzy inference system, is designed by determining the possible operating states of the system. The proposed system is compared with a rule-based control strategy. Results show that the developed control algorithm ensures that microgrid is supplied with reliable energy while the renewable energy use is maximized.

scholarly journals Potential Effect and Analysis of High Residential Solar Photovoltaic (PV) Systems Penetration to an Electric Distribution Utility (DU)

2016 ◽  
Vol 5 (3) ◽  
pp. 179-185 ◽  
Author(s):  
Jeffrey Tamba Dellosa
Keyword(s):  
Renewable Energy ◽  
Energy Demand ◽  
Potential Effect ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Load Profile ◽  
Pv Systems ◽  
Solar Pv System ◽  
Electric Distribution

The Renewable Energy Act of 2008 in the Philippines provided an impetus for residential owners to explore solar PV installations at their own rooftops through the Net-Metering policy. The Net-Metering implementation through the law however presented some concerns with inexperienced electric DU on the potential effect of high residential solar PV system installations. It was not known how a high degree of solar integration to the grid can possibly affect the operations of the electric DU in terms of energy load management. The primary objective of this study was to help the local electric DU in the analysis of the potential effect of high residential solar PV system penetration to the supply and demand load profile in an electric distribution utility (DU) grid in the province of Agusan del Norte, Philippines. The energy consumption profiles in the year 2015 were obtained from the electric DU operating in the area. An average daily energy demand load profile was obtained from 0-hr to the 24th hour of the day based from the figures provided by the electric DU. The assessment part of the potential effect of high solar PV system integration assumed four potential total capacities from 10 Mega Watts (MW) to 40 MW generated by all subscribers in the area under study at a 10 MW interval. The effect of these capacities were measured and analyzed with respect to the average daily load profile of the DU. Results of this study showed that a combined installations beyond 20 MWp coming from all subscribers is not viable for the local electric DU based on their current energy demand or load profile. Based from the results obtained, the electric DU can make better decisions in the management of high capacity penetration of solar PV systems in the future, including investment in storage systems when extra capacities are generated.Article History: Received July 15th 2016; Received in revised form Sept 23rd 2016; Accepted Oct 1st 2016; Available onlineHow to Cite This Article: Dellosa, J. (2016) Potential Effect and Analysis of High Residential Solar Photovoltaic (PV) Systems Penetration to an Electric Distribution Utility (DU). Int. Journal of Renewable Energy Development, 5(3), 179-185.http://dx.doi.org/10.14710/ijred.5.3.179-185

scholarly journals Assessment And Feasibility Analysis Of Off-Grid Solar PV- Pico Hydro Hybrid System

2019 ◽  
Vol 8 (6) ◽  
pp. 2461-2464
Keyword(s):  
Renewable Energy ◽  
Environmental Impact ◽  
Hybrid System ◽  
Renewable Energy Sources ◽  
River System ◽  
Energy System ◽  
Solar Pv ◽  
Pv System ◽  
Technical Data ◽  
Run Of River

As hydropower is one of the commonly available renewable energy sources, so it is experiencing a development in the large part of the world. Pico hydropower is used as a distributed system based renewable energy system meant for rural or remote area load . It is, hence, of most significant to propose an effective methodology to assure the better making reimbursement of a combined Pico hydro system with solar pv system. The proposed method mainly estimates the feasible of installing Pico hydropower in a run-of river. The Methodologies to assess the feasibility and sustainability of such mechanism were depicted. The orderly designing of plant is defined by considering some optimal technological method that considers the dimension of components plus the estimation of the gross energy generation. Economical plus Technical data studies performed to examine the profitability and practicability of the system. This planned method can be examined as a study and the feasibility of developing a PHP in a run of river system is possible. The environmental impact on fixing this plant measured and possibly reduced. This results obtained are demonstrated for already existing infrastructure and analyzed that the cost can be reduced by using an optimized model. A simulation result has obtained the financial expand is more by the technique used for the combine hydro-PV hybrid system. In Addition to the environmental impact and effect an analysis has exposed that yearly more than 200 tons of carbon emission is reduced by producing clean and green liveliness by means of the environmental and ecological solution.

scholarly journals A Solar Photovoltaic Performance and Financial Modeling Solution for Grid-Connected Homes in Zambia

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Katundu Imasiku
Keyword(s):  
Renewable Energy ◽  
Photovoltaic Performance ◽  
Performance Model ◽  
Photovoltaic System ◽  
Performance Ratio ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Coverage Ratio ◽  
Power Load

Zambia is today 90% hydropower dependent, but this may change because Zambia and the World at large are today facing a changing climate that affects the ecosystem, rain patterns, and spurs drought which reduces the production of hydropower. The current power deficit experienced in Zambia points to a need to deploy a renewable energy generation-mix strategy. This study conducts a solar photovoltaic performance and financial analysis for grid-connected homes in Zambia to investigate the role of solar energy as an enabler for energy security in Zambia using the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) simulation method. It further reviews the available solar irradiance, modeling a detailed grid-connected photovoltaic system using locally available products for a single owner in a power purchase agreement (PPA) with the Zambia Electricity Company Limited (ZESCO). This model would alleviate the current power load shedding experienced by the residential sector, of up to 22 hours of no electricity out of 24 hours in a day. Alongside the technical performance model and an unfavorable business climate in Zambia, a financial model is also developed to help assess project feasibility and financial viability. A 1 kW solar PV system was modeled at an installation cost of US$1.27 per watt on a short-term basis of 5 years and found that the project is feasible with a 28.52% IRR achieved in 3 years and a 69% performance ratio and a debt service coverage ratio (DSCR) of 5.12 by the end of the project life, thereby indicating capability to turn around Zambia’s energy poverty to meet the UN SDG 7.

scholarly journals Research Survey on Various MPPT Performance Issues to Improve the Solar PV System Efficiency

2016 ◽  
Vol 2016 ◽  
pp. 1-20 ◽  
Author(s):  
B. Pakkiraiah ◽  
G. Durga Sukumar
Keyword(s):  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Solar Irradiation ◽  
Energy Sources ◽  
Maximum Output ◽  
Solar Pv ◽  
Pv System ◽  
Pv Panel ◽  
Solar Pv System

Nowadays in order to meet the increase in power demands and to reduce the global warming, renewable energy sources based system is used. Out of the various renewable energy sources, solar energy is the main alternative. But, compared to other sources, the solar panel system converts only 30–40% of solar irradiation into electrical energy. In order to get maximum output from a PV panel system, an extensive research has been underway for long time so as to access the performance of PV system and to investigate the various issues related to the use of solar PV system effectively. This paper therefore presents different types of PV panel systems, maximum power point tracking control algorithms, power electronic converters usage with control aspects, various controllers, filters to reduce harmonic content, and usage of battery system for PV system. Attempts have been made to highlight the current and future issues involved in the development of PV system with improved performance. A list of 185 research publications on this is appended for reference.

scholarly journals Design and Simulation of Improved Soft Computing Based MPPT for Solar PV System Under Variable Irradiance Condition

2021 ◽  
Vol 12 (6) ◽  
pp. 1881-1891
Author(s):  
Surendra Singh Dua, Dr. Ruchi Sharma
Keyword(s):  
Renewable Energy ◽  
Low Cost ◽  
Renewable Energy Sources ◽  
Optimization Technique ◽  
Ease Of Use ◽  
Energy Sources ◽  
Solar Pv ◽  
Pv System ◽  
Partial Shading ◽  
Solar Pv System

Renewable energy sources are becoming more common in the energy generation field these days. Renewable energy sources such as photovoltaic (PV) systems, wind power (WP), and biomass are gaining popularity due to their ease of use, low cost, and low environmental impact. The environmental issues, declining fuel supplies, and increasing energy demands have drawn our attention to the glimmer of hope for a future focused entirely on sustainable and non-polluting energy sources. Photovoltaic (PV) power generation is becoming more common in comparison to other renewable energy sources due to advantages such as ease of access, low cost, low environmental emissions, and lower maintenance costs. In this dissertation, three separate Maximum power point monitoring techniques are used to construct a solar PV system (MPPT). Modeling and simulation using the MATLAB Simulink programmeare being used to check the effectiveness of the proposed scheme. The model is investigated using two partial shading patterns. By providing different values of input radiations to all four modules connected in sequence, we were able to create partial shading conditions using the PV array block. The panel's output is fed to the optimization technique block, which then feeds the boost converter from their duty cycle output. Under partial shading, the results show that the Particle Swarm Optimization algorithm outperforms the Perturb and Observe and Incremental Conductance algorithms..

Operation and control of a stand-alone power system with integrated multiple renewable energy sources

2021 ◽  
pp. 0309524X2110241
Author(s):  
Nindra Sekhar ◽  
Natarajan Kumaresan
Keyword(s):  
Renewable Energy ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Solar Pv ◽  
Power Requirement ◽  
Squirrel Cage ◽  
Hysteresis Controller ◽  
Squirrel Cage Induction Generator ◽  
And Control

To overcome the difficulties of extending the main power grid to isolated locations, this paper proposes the local installation of a combination of three renewable energy sources, namely, a wind driven DFIG, a solar PV unit, a biogas driven squirrel-cage induction generator (SCIG), and an energy storage battery system. In this configuration one bi-directional SPWM inverter at the rotor side of the DFIG controls the voltage and frequency, to maintain them constant on its stator side, which feeds the load. The PV-battery also supplies the load, through another inverter and a hysteresis controller. Appropriately adding a capacitor bank and a DSTATCOM has also been considered, to share the reactive power requirement of the system. Performance of various modes of operation of this coordinated scheme has been studied through simulation. All the results and relevant waveforms are presented and discussed to validate the successful working of the proposed system.

scholarly journals Optimal Energy Management of a Grid-Tied Solar PV-Battery Microgrid: A Reinforcement Learning Approach

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2700
Author(s):  
Grace Muriithi ◽  
Sunetra Chowdhury
Keyword(s):  
Renewable Energy ◽  
Reinforcement Learning ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Critical Role ◽  
Winter Season ◽  
Learning Approach ◽  
Solar Pv ◽  
Optimal Energy ◽  
Optimal Energy Management

In the near future, microgrids will become more prevalent as they play a critical role in integrating distributed renewable energy resources into the main grid. Nevertheless, renewable energy sources, such as solar and wind energy can be extremely volatile as they are weather dependent. These resources coupled with demand can lead to random variations on both the generation and load sides, thus complicating optimal energy management. In this article, a reinforcement learning approach has been proposed to deal with this non-stationary scenario, in which the energy management system (EMS) is modelled as a Markov decision process (MDP). A novel modification of the control problem has been presented that improves the use of energy stored in the battery such that the dynamic demand is not subjected to future high grid tariffs. A comprehensive reward function has also been developed which decreases infeasible action explorations thus improving the performance of the data-driven technique. A Q-learning algorithm is then proposed to minimize the operational cost of the microgrid under unknown future information. To assess the performance of the proposed EMS, a comparison study between a trading EMS model and a non-trading case is performed using a typical commercial load curve and PV profile over a 24-h horizon. Numerical simulation results indicate that the agent learns to select an optimized energy schedule that minimizes energy cost (cost of power purchased from the utility and battery wear cost) in all the studied cases. However, comparing the non-trading EMS to the trading EMS model operational costs, the latter one was found to decrease costs by 4.033% in summer season and 2.199% in winter season.

scholarly journals Forecasting and Modelling the Uncertainty of Low Voltage Network Demand and the Effect of Renewable Energy Sources

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2151
Author(s):  
Feras Alasali ◽  
Husam Foudeh ◽  
Esraa Mousa Ali ◽  
Khaled Nusair ◽  
William Holderbaum
Keyword(s):  
Renewable Energy ◽  
Low Voltage ◽  
Renewable Energy Sources ◽  
Golden Ratio ◽  
Clean Energy ◽  
Energy Sources ◽  
Percentage Error ◽  
Ann Model ◽  
Demand Forecast ◽  
Pv System

More and more households are using renewable energy sources, and this will continue as the world moves towards a clean energy future and new patterns in demands for electricity. This creates significant novel challenges for Distribution Network Operators (DNOs) such as volatile net demand behavior and predicting Low Voltage (LV) demand. There is a lack of understanding of modern LV networks’ demand and renewable energy sources behavior. This article starts with an investigation into the unique characteristics of householder demand behavior in Jordan, connected to Photovoltaics (PV) systems. Previous studies have focused mostly on forecasting LV level demand without considering renewable energy sources, disaggregation demand and the weather conditions at the LV level. In this study, we provide detailed LV demand analysis and a variety of forecasting methods in terms of a probabilistic, new optimization learning algorithm called the Golden Ratio Optimization Method (GROM) for an Artificial Neural Network (ANN) model for rolling and point forecasting. Short-term forecasting models have been designed and developed to generate future scenarios for different disaggregation demand levels from households, small cities, net demands and PV system output. The results show that the volatile behavior of LV networks connected to the PV system creates substantial forecasting challenges. The mean absolute percentage error (MAPE) for the ANN-GROM model improved by 41.2% for household demand forecast compared to the traditional ANN model.

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