Temiz Tükenmez Enerjiler Bölümü
https://hdl.handle.net/11655/601
Temiz Tükenmez Enerjiler Bölümü2024-03-28T09:07:33ZFarklı Perovskit Güneş Gözelerinin Verimliliğinin Simülasyonu ve Karşılaştırması
https://hdl.handle.net/11655/34419
Farklı Perovskit Güneş Gözelerinin Verimliliğinin Simülasyonu ve Karşılaştırması
Dereli, Yağız
Perovskite solar cells have become the focus of interest in research for the development of solar cells due to their high efficiency, low cost, and adjustable structures. The perovskite solar cells have been the fastest-growing solar technology in terms of efficiency, which has been rapidly increased from 3.8% (reported in year 2009 for the first time) to 25.8% reported in 2023 as the recent measured value.
Systems using silicon-based solar cells, known as traditional solar panels, are the only commercialized solar panel technology today. Although perovskite solar cells have not yet been commercialized, they have a high potential to replace conventional solar panels in the future. In order to reach this potential as quickly as possible, perovskite materials, which have a wide variety, need to be researched by simulation studies as well as laboratory researches.
In this study, the behavior of three different perovskite materials, MAPbI3, MAPbBr3, and Cs2AgBiBr6 in an architecture determined from the literature was simulated with the help of OghmaNano (GPVDM) software. It was first studied at a temperature of 27 ºC which is the software default, and at different thicknesses between 100 and 700 nm. Then, based on the optimum thickness values obtained for each perovskite material, the efficiency values obtained by examining different temperatures between -10 and 70 ºC.
2023-08-07T00:00:00ZTürkiye İçin %100 Yenilenebilir Enerji Sisteminin Tekno-Ekonomik Analizi
https://hdl.handle.net/11655/33249
Türkiye İçin %100 Yenilenebilir Enerji Sisteminin Tekno-Ekonomik Analizi
Akgün, Atakan
Greenhouse gas emissions have to be reduced to zero by 2050 in order to stop global climate change. Energy system has to transform into a net zero emission one since currently it consumes large amount of fossil fuels and is the main source of greenhouse gas emissions. However, Turkey does not have any long-term climate or energy policy for planning and execution of its energy transition. In addition to the use of clean energy resources, concepts such as smart energy systems and sector coupling offer the most cost-effective solution for energy transition. In this study, by the use of EnergyPLAN software and smart energy systems approach; two scenarios were applied to Turkey’s energy system including electricity, transportation, heating&cooling and industry sectors so that all energy related emissions will be eliminated. In the first scenario, nuclear power is utilized along with renewable energy sources, while in the second scenario, an energy system was planned using 100% renewable energy. Technology options were added step by step to 2050 reference energy system and the effects of each option was analysed. Simulations were performed at hourly resolution and energy demand and production were balanced at every hour throughout the year. In both scenarios, zero-emission energy
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systems rely heavily on renewable electricity. As the installed power of solar and wind power plants increases, flexibility in the electricity grid is provided by loads such as heat pumps and electrolysers, instead of generation plants. In both scenarios, the cost of zero emission energy systems is only 4.5% higher than reference energy system. In the transition to net zero emission energy systems, Nuclear + Renewable scenario causes lower level of carbon emissions, but the 100% renewable scenario was more advantageous in annual energy system costs.
2021-01-01T00:00:00ZInvestıgatıon of the Impact of the Solar Power Generation Forecast By Using Big Data Analytics On the Local Electrıcity Market
https://hdl.handle.net/11655/33213
Investıgatıon of the Impact of the Solar Power Generation Forecast By Using Big Data Analytics On the Local Electrıcity Market
Demirtaş, Ozan Oğulcan
Integration of Distributed Renewable Energy Sources (RES) into the existing energy system becomes more challenging as the number of RES increases due to their intermittent and variable nature. One way to address this issue is to use Local Electricity Markets (LEM) where consumers and producers can actively participate in trading locally produced electricity within their own Local Energy Communities (LEC). However, knowing the production value in advance (usually for a short period) is crucial for the formation of prices, evaluation of bids, and creating offers in local energy markets. Therefore, short-term load forecasting, which is an important parameter that helps electricity grid operators make decisions such as purchasing and selling electricity, load balancing, and maintenance planning, plays a significant role in system operations.
The aim of this study is to examine the possible role of a solar power plant whose short-term production value is estimated in advance through simulation in the local electricity day-ahead market and the effects it may have on electricity prices. Additionally, this study aims to pre-shape pricing by obtaining bids before the day electricity will be supplied in this market.
In the first stage of the study, a high-capacity solar power plant was selected, and day-ahead electricity generation was estimated for this plant using past electricity production data and meteorological data from the plant's region. Due to the high variety and volume of the data, Big Data Analytics method was used in this analysis, and the analysis was carried out using machine learning techniques in Python programming. Three different models were examined, and the Light GBM model provided the best result for the day's electricity generation estimation In the second stage of the study, the forecasted electricity generation values for the modelled day were used in the local electricity market simulation model. Grid Singularity, an open-source and online software, was used to verify simulated scalable scenarios and evaluate LEMs economically. Firstly, a community was identified under Grid Singularity, and local market players were added for this community. Then, three different scenarios were developed to examine price formation, profitability, and the community's self-sufficiency thoroughly. In the first scenario, a solar power plant was not included in the community, and local market players were forced to meet all their electricity needs from the grid. In the second scenario, a solar power plant with high installed capacity was added to the system, and the simulation was run in this way. Finally, in the third scenario, two batteries with separate capacities of 10 kWh and 30 kWh were added to the system, unlike the second scenario, and the simulation was run again. In situations where solar energy could not be provided, local consumers purchased electricity from the battery, and it was observed that this increased the self-sufficiency of the community. When the results of all scenarios were evaluated, self-sufficiency rates were obtained as 0%, 65.0%, 69.0% & 77.0% (by depending on the battery power) respectively. The values indicates that the community can utilize the green electricity generated in the local market at the stated percentages. However, achieving these percentages fully is not possible due to the fact that solar energy is the primary renewable energy source in the community, and the production of the solar power plant is subject to fluctuations in meteorological values throughout the day. Moreover, it was achieved that penetration of substantial quantity of renewable energy into the system resulted in a decrease of 26.7% and 30% in the average market price of electricity in the second and third scenarios, respectively, as compared to the first scenario. As a result, it has been observed that the integration of a high-capacity solar power plant into the local electricity market lowers market prices. Additionally, it has been emphasized that knowing the production that this plant will generate one day in advance allows market participants to take effective positions in the market.
2023-01-01T00:00:00ZGri Kurt Optimizasyonu Algoritmasına Dayalı Bir Rüzgar / Fotovoltaik / Yakıt Hücreli Hibrid Sisteminin Optimal Büyüklükteki Tasarımı
https://hdl.handle.net/11655/27157
Gri Kurt Optimizasyonu Algoritmasına Dayalı Bir Rüzgar / Fotovoltaik / Yakıt Hücreli Hibrid Sisteminin Optimal Büyüklükteki Tasarımı
Asghari, Iraj
This study developed a hybrid system composed of wind turbines, PV cells, and fuel cells to
supply a specific (deterministic) load model. The purpose of this design was to minimize the
cost of energy generation over a period of 20-year while satisfying a set of system reliability
constraints. In this paper, the data pertaining to load demand, sunlight and wind speed were
considered to be known and deterministic. This design considered the failure of three main
system components, namely, wind turbines, PV cells and AC/DC converter, and
incorporated a number of cost factors such as initial investment, operating and maintenance
expenses, and value of lost load (VoLL). The wind and solar data used in this study pertained
to northwestern regions of Iran. This paper used gray wolf optimization algorithm (GWO) to
optimize the system and compared the results with the results of particle swarm PSO.
The stated objective of this paper was to determine the optimal value of system components,
i.e. the number of wind turbines, the number and angle of PV arrays, and the size of
electrolyzer, hydrogen tanks, fuel cells, and DC/AC converters. The costs incorporated into
this design included net present value (NPV) of investment, costs of equipment, replacement
and maintenance, and the costs arising from power supply interruption (VoLL), all for a
period of 20 years considered as the system lifetime.
2018-01-01T00:00:00Z