scholarly journals CHARACTERISTICS AND TRENDS OF INDICATORS OF EXPORT, IMPORT, AND ELECTRICITY CONSUMPTION IN LATVIA. WIND POWER CONSUMPTION CHARACTERISTICS AND TRENDS

2021 ◽  
Vol 7 (4) ◽  
pp. 188-195
Author(s):  
Veronica Silinevicha
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Renewable Resources ◽  
Electricity Generation ◽  
Electricity Consumption ◽  
Negative Consequences ◽  
Monthly Basis ◽  
Renewable Sources ◽  
High Penetration ◽  
Production And Consumption

Energy markets with high penetration rates of renewables are more likely to face price fluctuations or volatility, which is in part due to the stochastic nature of renewables. Latvia's electricity market is an excellent example of such a market, as more than 40% of Latvia's electricity generation comes from hydropower, which challenges the projected spot electricity prices for Latvia's electricity market. The article identifies trends in the natural and value indicators of total exports, imports, total currency turnover and electricity consumption in Latvia with a more detailed study of the characteristics and trends of electricity consumption indicators from renewable resources for the period 2014, 2015 - 2019. In addition, wind power utilization rates were considered both for the observed period as a whole and on a monthly basis for 2019. In general, the results of the study confirm the feasibility of Latvia's plans to increase both total electricity consumption and its share from renewable sources. At the same time, the coronavirus pandemic has already begun to lead to negative consequences for electricity consumption in EU countries, which have so far affected Latvia to a lesser extent. Nevertheless, these consequences will inevitably lead to an adjustment of Latvia's electricity plans towards an increase in the share of production and consumption of electricity from renewable sources, including wind energy, despite its upward price trend. The author with employment of the tools Excel Trendline obtains trends of indicators, approximating formulae dependencies and the coefficients of determination for the relevant diagrams and charts.

scholarly journals Potential utilization of renewable energy resources for electricity generation in Bosnia and Herzegovina

2005 ◽  
Vol 9 (3) ◽  
pp. 15-23 ◽  
Author(s):  
Fajik Begic ◽  
Anes Kazagic
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Bosnia And Herzegovina ◽  
Electricity Market ◽  
Renewable Resources ◽  
Electricity Generation ◽  
Power Plants ◽  
Energy Resources ◽  
Energy Utilization ◽  
Renewable Energy Resources

Along with the current processes of restructuring of Energy power system of Bosnia and Herzegovina, liberalization of the electricity market, and modernization of the existing power plants, Bosnia and Herzegovina must turn to the utilization of renewable resources in reason able dynamics as well. Respecting this policy, the initial Valuation of the potential of renewable erg resources in Bosnia and Herzegovina is per formed. The methodology of evaluation of wind energy utilization is presented in this paper, as well as some other aspects of utilization of the renewable energy resources in Bosnia and Herzegovina. Implementation of selected projects should improve sustainability of energy power production in Bosnia and Herzegovina, by reducing the total emission of carbon dioxide originated from energy power system of Bosnia and Herzegovina.

Wind energy

2007 ◽  
Author(s):  
Bill Leithead
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Electricity Generation ◽  
Wind Farm ◽  
Power Converter ◽  
Offshore Wind ◽  
Renewable Sources ◽  
Near Term ◽  
The Uk

A wind turbine or even a wind farm, i.e. a group of wind turbines, is becoming an increasingly familiar sight in the countryside today. The wind turbine converts the power in the wind to electrical power and consists of a tower, rotor, typically with three blades as in Fig. 5.1, and a nacelle containing the power converter. From its rebirth in the early 1980s, wind power has experienced a dramatic development. Today, other than hydropower, it is the most important of the renewable sources of power. With an installed capacity equivalent to that required to provide electricity for over 19,000,000 average European homes and annual turnover greater than £5,500,000,000, wind energy has exceeded its year-on-year targets over the last decade. This growth in the contribution to electricity generation from wind power in Europe is likely to continue over the next few years, since the EU Commission has set a European target for 2010 of 12% of electricity generation from renewable sources. In the long term, the achievable limit to the contribution of wind power is estimated to be30%of the total European demand, an amount almost equal to the installed nuclear capacity. In the UK, wind power is the fastest growing energy sector. Over 4,000 people are employed by companies working in the wind sector , and it is estimated by the UK Department of Trade and Industry (DTI) that the next round of offshore wind development could generate a further 20,000 jobs. In a 2003 Energy White Paper, the UK government aspired to achieving a 60% reduction in UK CO2 emissions by 2050. In order to do so, it has set targets for UK electricity generation from renewable sources of 10% of electricity demand by 2010 and20% by 2015. Since it is the most mature of the renewable energies, much of these near term targets must be met by wind power . Irrespective of whether these targets are achieved, the potential for increase in the UK is substantial. The prospects for wind power development in the UK are dependent on the available wind resource, public acceptance, and technical development. Each of these issues is discussed below.

Wind Power Forecasting Using Wavelet Transform and General Regression Neural Network for Ontario Electricity Market

2020 ◽  
Vol 13 (1) ◽  
pp. 16-26
Author(s):  
Sumit Saroha ◽  
Sanjeev K. Aggarwal
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Wavelet Transform ◽  
Wind Power ◽  
Electricity Market ◽  
General Regression Neural Network ◽  
Percentage Error ◽  
Wind Power Forecasting ◽  
General Regression ◽  
Power Forecasting

Objective: The estimation accuracy of wind power is an important subject of concern for reliable grid operations and taking part in open access. So, with an objective to improve the wind power forecasting accuracy. Methods: This article presents Wavelet Transform (WT) based General Regression Neural Network (GRNN) with statistical time series input selection technique. Results: The results of the proposed model are compared with four different models namely naïve benchmark model, feed forward neural networks, recurrent neural networks and GRNN on the basis of Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) performance metric. Conclusion: The historical data used by the presented models has been collected from the Ontario Electricity Market for the year 2011 to 2015 and tested for a long time period of more than two years (28 months) from November 2012 to February 2015 with one month estimation moving window.

scholarly journals Optimal Sizing and Placement of Capacitor Banks in Distribution Networks Using a Genetic Algorithm

Electricity ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 187-204
Author(s):  
Gian Giuseppe Soma
Keyword(s):  
Genetic Algorithm ◽  
Electricity Market ◽  
Distribution Systems ◽  
Reactive Power ◽  
Electricity Consumption ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Capacitor Banks ◽  
Control Pattern ◽  
Definition Of

Nowadays, response to electricity consumption growth is mainly supported by efficiency; therefore, this is the new main goal in the development of electric distribution networks, which must fully comply with the system’s constraints. In recent decades, the issue of independent reactive power services, including the optimal placement of capacitors in the grid due to the restructuring of the electricity industry and the creation of a competitive electricity market, has received attention from related companies. In this context, a genetic algorithm is proposed for optimal planning of capacitor banks. A case study derived from a real network, considering the application of suitable daily profiles for loads and generators, to obtain a better representation of the electrical conditions, is discussed in the present paper. The results confirmed that some placement solutions can be obtained with a good compromise between costs and benefits; the adopted benefits are energy losses and power factor infringements, taking into account the network technical limits. The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of capacitor banks in distribution systems, with the definition of a suitable control pattern, have been proved.

scholarly journals Different Scenarios for the National Transmission Grid, Considering the Extensive Use of On-Site Renewable Energy in the Mexican Housing Sector

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 195
Author(s):  
Ivan Oropeza-Perez ◽  
Astrid H Petzold-Rodriguez
Keyword(s):  
Renewable Energy ◽  
Electricity Generation ◽  
Housing Sector ◽  
Distribution Grid ◽  
Smart Meters ◽  
Long Distance ◽  
Distribution Method ◽  
Transmission Grid ◽  
Production And Consumption ◽  
Transmission And Distribution

The Mexican national electricity transmission and distribution grid (SEN, initials in Spanish) is characterized by the high interconnection between its several electricity generation plants and the millions of final consumers throughout the country. This feature, which is seen first as an adequate transmission and distribution method for electricity between producer and consumer, has the inconvenience of being highly complex when renewable energy is introduced into the SEN. The random nature of renewable energy means that coordination between the producer and consumer is difficult; therefore, these energy sources are considered by the Mexican Federal Commission of Electricity (CFE, initials in Spanish) without priority in their generation and distribution. In this document, a solution for this is given by the consideration of on-site photovoltaic production in the Mexican residential sector, setting a straightforward relationship between production and consumption, neglecting the long-distance transmission, and freeing the transmission and distribution through the SEN at certain hours of the day. Different scenarios are studied, considering the level of penetration of this renewable energy technology into the housing sector. In this way, it is found that, if 80% of the total Mexican dwellings hold a photovoltaic roof, in some seasons of the year, a large part the total national demand can be fulfilled by the photovoltaic generation if certain systems—such as bidirectional smart meters—are applied. In this sense, the results show that, if 80% of the Mexican dwellings had a photovoltaic roof, there would be a money saving of 3418 Million USD and a mitigation of 25 million tons CO2e, for 2018. With this, it is concluded that renewable energy in Mexico could provide a much greater share if the electricity is produced in the same place where it will be consumed. This might be possible in Mexico due to the high interconnection of the transmission and distribution grid, which would manage the surplus electricity generation in the dwellings in a proper manner.

scholarly journals Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm

2021 ◽  
Vol 11 (10) ◽  
pp. 4438
Author(s):  
Satyendra Singh ◽  
Manoj Fozdar ◽  
Hasmat Malik ◽  
Maria del Valle Fernández Moreno ◽  
Fausto Pedro García Márquez
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Large Scale ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimization Methods ◽  
Bidding Strategy ◽  
Wind Speed Profile ◽  
Gravitational Search ◽  
Modified Gravitational Search Algorithm

It is expected that large-scale producers of wind energy will become dominant players in the future electricity market. However, wind power output is irregular in nature and it is subjected to numerous fluctuations. Due to the effect on the production of wind power, producing a detailed bidding strategy is becoming more complicated in the industry. Therefore, in view of these uncertainties, a competitive bidding approach in a pool-based day-ahead energy marketplace is formulated in this paper for traditional generation with wind power utilities. The profit of the generating utility is optimized by the modified gravitational search algorithm, and the Weibull distribution function is employed to represent the stochastic properties of wind speed profile. The method proposed is being investigated and simplified for the IEEE-30 and IEEE-57 frameworks. The results were compared with the results obtained with other optimization methods to validate the approach.

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