Economically Optimal Solar Power Generation

Author(s):  
Sana Badruddin ◽  
Cameron Ryan Robertson-Gillis ◽  
Janice Ashworth ◽  
David J. Wright

The Ottawa Renewable Energy Cooperative is considering installing solar modules on the roofs of two buildings while they stay connected to the public electricity grid. Solar power produced over their own needs would be sent to the public electricity grid for a credit on their electricity bill. When they need more power than they are generating, these buildings would purchase electricity from the grid. In addition to paying for the electricity they purchase, they would be subject to a “demand charge” that applies each month to the hour during which their consumption is at a peak for that month. Any electricity consumed during that peak hour would be charged at a rate about 100 times the rate for other hours. The case addresses three questions: (1) Is it profitable for these organizations to install solar on their roofs? (2) Can profitability be increased by adding a battery? and (3) How sensitive is profitability to uncertainty in future electricity prices? The case shows how the answers to these questions depend on the profile of hourly electricity consumption during the day, which is very different from one building to the other.

Author(s):  
Sana Badruddin ◽  
Cameron Ryan Robertson-Gillis ◽  
Janice Ashworth ◽  
David J. Wright

The Ottawa Renewable Energy Cooperative is considering installing solar modules on the roofs of two buildings while they stay connected to the public electricity grid. Solar power produced over their own needs would be sent to the public electricity grid for a credit on their electricity bill. When they need more power than they are generating, these buildings would purchase electricity from the grid. In addition to paying for the electricity they purchase, they would be subject to a “demand charge” that applies each month to the hour during which their consumption is at a peak for that month. Any electricity consumed during that peak hour would be charged at a rate about 100 times the rate for other hours. The case addresses three questions: (1) Is it profitable for these organizations to install solar on their roofs? (2) Can profitability be increased by adding a battery? and (3) How sensitive is profitability to uncertainty in future electricity prices? The case shows how the answers to these questions depend on the profile of hourly electricity consumption during the day, which is very different from one building to the other.


2020 ◽  
Vol 7 (3) ◽  
pp. 21-26
Author(s):  
Mohammad Noor Hidayat ◽  
Ahmad Hermawan ◽  
Afriana Viro Fadilla ◽  
Muhammad Aden Herry Prakoso ◽  
Nurhayati

Electrical energy is a very important part of human activity at this time. At present a very popular source of renewable electricity is energy (solar) through the use of solar power generation system. "Design Passive Photovoltaic 50 Wp in Renewable Energy Laboratory State Polytechnic of Malang" aims to plan and analyze the solar power generation system (PLTS), namely a capacity of 50 wp,so that it can be used as a guideline when going to design or implement PLTS on a larger scale. Based on the analysis and testing carried out, namely testing of 50 Wp passive solar panels under normal (clean) angles of 0º, 15º, 30º and shading angles of 0º, as well as the fouling angle of 0º produces the highest energy of 210.7 Wh when the condition of the solar panels is at an angle of normal 30º.


2021 ◽  
Vol 5 (1) ◽  
pp. 50
Author(s):  
Phil Aupke ◽  
Andreas Kassler ◽  
Andreas Theocharis ◽  
Magnus Nilsson ◽  
Michael Uelschen

Recently, there has been growing interest in using machine learning based methods for forecasting renewable energy generation using time-series prediction. Such forecasting is important in order to optimize energy management systems in future micro-grids that will integrate a large amount of solar power generation. However, predicting solar power generation is difficult due to the uncertainty of the solar irradiance and weather phenomena. In this paper, we quantify the impact of uncertainty of machine learning based time-series predictors on the forecast accuracy of renewable energy generation using long-term time series data available from a real micro-grid in Sweden. We use clustering to build different ML forecasting models using LSTM and Facebook Prophet. We evaluate the accuracy impact of using interpolated weather and radiance information on both clustered and non-clustered models. Our evaluations show that clustering decreases the uncertainty by more than 50%. When using actual on-side weather information for the model training and interpolated data for the inference, the improvements in accuracy due to clustering are the highest, which makes our approach an interesting candidate for usage in real micro-grids.


2021 ◽  
Author(s):  
Aqsa Rana ◽  
Gyula Gróf

Abstract Background: Significant innovations in technology and progressing use of renewable energy sources (RES) reinforce the demand for the sustainable, continuous and abundant supply of energy to every consumer. Blockchain, as an emerging technology promises to provide temper proof, secure, transparent and decentralized energy trading mechanisms that help to provide sustainable environmental solutions by circulating economy to empower both consumers and prosumers. The rapid development of blockchain technology has gained interest from energy start-ups, innovation developers, finance suppliers, academic institutions and government. Results: This study outlines potential significance, benefits and application of blockchain technology and analyses how Pakistan can integrate blockchain technology into its distribution system to cope with current challenges. Although the substantial renewable potential of Pakistan is an opportunity to implement blockchain technology but financial management, innovative technology development and acceptance of decentralized technology are the biggest obstacles. After a detailed discussion of Pakistan's current financial position, digital market structure, energy policy and technology situation for the implication of blockchain technology, Photographic Geographical Information System (PVGIS-5) data base tool is used to estimate solar power generation capacity from prosumer community in potential areas of country like Baluchistan. Conclusion: This study recommended feasible site for solar power generation according to PVGIS tool. Then introduces a street scenario about domestic power generation and blockchain based distribution into Pakistan's energy sector like Brooklyn energy system by regulating laws, revising energy polices and suitable development subsidies.


Energy Policy ◽  
2019 ◽  
Vol 131 ◽  
pp. 358-369 ◽  
Author(s):  
Zsuzsanna Csereklyei ◽  
Songze Qu ◽  
Tihomir Ancev

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