scholarly journals Performance and Economic Assessment of a Grid-Connected Photovoltaic Power Plant with a Storage System: A Comparison between the North and the South of Italy

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2356 ◽  
Author(s):  
Ferdinando Chiacchio ◽  
Fabio Famoso ◽  
Diego D’Urso ◽  
Luca Cedola
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Low Voltage ◽  
Storage System ◽  
Economic Feasibility ◽  
The South ◽  
Model Based ◽  
The North ◽  
Photovoltaic Power ◽  
Historical Series

Grid-connected low voltage photovoltaic power plants cover most of the power capacity installed in Italy. They offer an important contribution to the power demand of the utilities connected but, due to the nature of the solar resource, the night-time consumption can be satisfied only withdrawing the energy by the national grid, at the price of the energy distributor. Thanks to the improvement of storage technologies, the installation of a system of battery looks like a promising solution by giving the possibility to increase auto-consumption dramatically. In this paper, a model-based approach to analyze and discuss the performance and the economic feasibility of grid-connected domestic photovoltaic power plants with a storage system is presented. Using as input to the model the historical series (2008–2017) of the main ambient variables, the proposed model, based on Stochastic Hybrid Fault Tree Automaton, allowed us to simulate and compare two alternative technical solutions characterized by different environmental conditions, in the north and in the south of Italy. The performances of these systems were compared and an economic analysis, addressing the convenience of the storage systems was carried out, considering the characteristic useful-life time, 20 years, of a photovoltaic power plant. To this end the Net Present Value and the payback time were evaluated, considering the main characteristics of the Italian market scenario.

scholarly journals Economic feasibility of developing large scale solar photovoltaic power plants in Spain

2019 ◽  
Vol 122 ◽  
pp. 02004 ◽  
Author(s):  
Javier Menéndez ◽  
Jorge Loredo
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Large Scale ◽  
Economic Feasibility ◽  
Solar Irradiation ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Photovoltaic Energy ◽  
Profitability Analysis ◽  
Photovoltaic Power

In 2017, electricity generation from renewable sources contributed more than one quarter (30.7%) to total EU-28 gross electricity consumption. Wind power is for the first time the most important source, followed closely by hydro power. The growth in electricity from photovoltaic energy has been dramatic, rising from just 3.8 TWh in 2007, reaching a level of 119.5 TWh in 2017. Over this period, the contribution of photovoltaic energy to all electricity generated in the EU-28 from renewable energy sources increased from 0.7% to 12.3%. During this period the investment cost of a photovoltaic power plant has decreased considerably. Fundamentally, the cost of solar panels and inverters has decreased by more than 50%. The solar photovoltaic energy potential depends on two parameters: global solar irradiation and photovoltaic panel efficiency. The average solar irradiation in Spain is 1,600 kWh m-2. This paper analyzes the economic feasibility of developing large scale solar photovoltaic power plants in Spain. Equivalent hours between 800-1,800 h year-1 and output power between 100-400 MW have been considered. The profitability analysis has been carried out considering different prices of the electricity produced in the daily market (50-60 € MWh-1). Net Present Value (NPV) and Internal Rate of Return (IRR) were estimated for all scenarios analyzed. A solar PV power plant with 400 MW of power and 1,800 h year-1, reaches a NPV of 196 M€ and the IRR is 11.01%.

High Penetration PV in Distribution Networks, Design and Control

2016 ◽  
Vol 1 (2) ◽  
pp. 238
Author(s):  
Ashkan Mohammadi ◽  
Saman Hosseini Hemati
Keyword(s):  
Global Warming ◽  
Power Plant ◽  
Capital Investment ◽  
Power Plants ◽  
Low Voltage ◽  
Direct Consequence ◽  
Distribution Networks ◽  
Transient Effects ◽  
Photovoltaic Power ◽  
High Penetration

<p>Global warming is a direct consequence of consumption of fossil fuels which emit greenhouse gasses as they produce energy. Solar energy is the most available energy throughout the world in which regardless of capital investment is free and most importantly clean and emission free and could be a solution for global warming along with other renewable sources of energy. But as photovoltaic energy is becoming widespread and penetration level of photovoltaic power plants increase, several issues rise in distribution networks. In this paper, a high penetration photovoltaic power plant is designed and issues associated with it are thoroughly discussed. Voltage rise and cloud passage effect are amongst the most challenging issues in design and implementation of a high penetration photovoltaic power plant in distribution networks. Transient effects of cloud passage could lead to unacceptably low voltage in Point of Common Coupling and maximum penetration level must be set according to these issues. An efficient Maximum Power Point Tracking (MPPT) and a DC link voltage control scheme are also presented. Simulations have been done in Matlab/Simulink environment.</p>

Evaluation of energy generation in Iraqi territory by solar photovoltaic power plants with a capacity of 20 MW

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Qusay Hassan ◽  
Saadoon Abdul Hafedh ◽  
Ali Hasan ◽  
Marek Jaszczur
Keyword(s):  
Experimental Data ◽  
Wind Speed ◽  
Power Plant ◽  
Ambient Temperature ◽  
Solar Irradiance ◽  
Electricity Generation ◽  
Power Plants ◽  
Solar Photovoltaic ◽  
Photovoltaic Power ◽  
Plant Capacity

Abstract The study evaluates the visibility of solar photovoltaic power plant construction for electricity generation based on a 20 MW capacity. The assessment was performed for four main cities in Iraq by using hourly experimental weather data (solar irradiance, wind speed, and ambient temperature). The experimental data was measured for the period from 1st January to 31st December of the year 2019, where the simulation process was performed at a 1 h time step resolution at the same resolution as the experimental data. There are two positionings considered for solar photovoltaic modules: (i) annual optimum tilt angle and (ii) two-axis tracking system. The effect of the ambient temperature and wind on the overall system energy generated was taken into consideration. The study is targeted at evaluating the potential solar energy in Iraq and the viability of electricity generation using a 20 MW solar photovoltaic power plant. The results showed that the overall performance of the suggested power plant capacity is highly dependent on the solar irradiance intensity and the ambient temperature with wind speed. The current 20 MW solar photovoltaic power plant capacity shows the highest energy that can be generated in the mid-western region and the lowest in the northeast regions. The greatest influence of the ambient temperature on the energy genrated by power plants is observed in the southern regions.

scholarly journals Design Considerations for the Liquid Air Energy Storage System Integrated to Nuclear Steam Cycle

2021 ◽  
Vol 11 (18) ◽  
pp. 8484
Author(s):  
Seok-Ho Song ◽  
Jin-Young Heo ◽  
Jeong-Ik Lee
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Power Sources

A nuclear power plant is one of the power sources that shares a large portion of base-load. However, as the proportion of renewable energy increases, nuclear power plants will be required to generate power more flexibly due to the intermittency of the renewable energy sources. This paper reviews a layout thermally integrating the liquid air energy storage system with a nuclear power plant. To evaluate the performance realistically while optimizing the layout, operating nuclear power plant conditions are used. After revisiting the analysis, the optimized performance of the proposed system is predicted to achieve 59.96% of the round-trip efficiency. However, it is further shown that external environmental conditions could deteriorate the performance. For the design of liquid air energy storage-nuclear power plant integrated systems, both the steam properties of the linked plants and external factors should be considered.

scholarly journals Industry Experience of Developing Day-Ahead Photovoltaic Plant Forecasting System Based on Machine Learning

2020 ◽  
Vol 12 (20) ◽  
pp. 3420 ◽  
Author(s):  
Alexandra I. Khalyasmaa ◽  
Stanislav A. Eroshenko ◽  
Valeriy A. Tashchilin ◽  
Hariprakash Ramachandran ◽  
Teja Piepur Chakravarthi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Power Plant ◽  
Power Plants ◽  
Machine Learning Algorithms ◽  
Solar Irradiation ◽  
Gradient Boosting ◽  
Forecasting Accuracy ◽  
Photovoltaic Power ◽  
Forecasting System ◽  
Industry Experience

This article highlights the industry experience of the development and practical implementation of a short-term photovoltaic forecasting system based on machine learning methods for a real industry-scale photovoltaic power plant implemented in a Russian power system using remote data acquisition. One of the goals of the study is to improve photovoltaic power plants generation forecasting accuracy based on open-source meteorological data, which is provided in regular weather forecasts. In order to improve the robustness of the system in terms of the forecasting accuracy, we apply newly derived feature introduction, a factor obtained as a result of feature engineering procedure, characterizing the relationship between photovoltaic power plant energy production and solar irradiation on a horizontal surface, thus taking into account the impacts of atmospheric and electrical nature. The article scrutinizes the application of different machine learning algorithms, including Random Forest regressor, Gradient Boosting Regressor, Linear Regression and Decision Trees regression, to the remotely obtained data. As a result of the application of the aforementioned approaches together with hyperparameters, tuning and pipelining of the algorithms, the optimal structure, parameters and the application sphere of different regressors were identified for various testing samples. The mathematical model developed within the framework of the study gave us the opportunity to provide robust photovoltaic energy forecasting results with mean accuracy over 92% for mostly-sunny sample days and over 83% for mostly cloudy days with different types of precipitation.

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