Understanding the Dynamics of Electricity Supply and Demand in Canada

2013 ◽  
pp. 157-174
Author(s):  
Hassan Qudrat-Ullah
Keyword(s):  
Supply And Demand ◽  
Electricity Supply

Meeting the Balance of Electricity Supply and Demand in Latin America and the Caribbean

2011 ◽  
Author(s):  
Rigoberto Ariel Yépez-García ◽  
Todd M. Johnson ◽  
Luis Alberto Andrés
Keyword(s):  
Latin America ◽  
Supply And Demand ◽  
Electricity Supply ◽  
The Caribbean

scholarly journals Short-Term Forecasting of Electricity Supply and Demand by Using the Wavelet-PSO-NNs-SO Technique for Searching in Big Data of Iran’s Electricity Market

Data ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 43 ◽  
Author(s):  
Mesbaholdin Salami ◽  
Farzad Movahedi Sobhani ◽  
Mohammad Ghazizadeh
Keyword(s):  
Neural Networks ◽  
Electricity Market ◽  
Simulation Optimization ◽  
Supply And Demand ◽  
Electricity Supply ◽  
Wavelet Neural Networks ◽  
Short Term ◽  
Swarm Optimization ◽  
Forecasting Accuracy ◽  
Short Term Forecasting

The databases of Iran’s electricity market have been storing large sizes of data. Retail buyers and retailers will operate in Iran’s electricity market in the foreseeable future when smart grids are implemented thoroughly across Iran. As a result, there will be very much larger data of the electricity market in the future than ever before. If certain methods are devised to perform quick search in such large sizes of stored data, it will be possible to improve the forecasting accuracy of important variables in Iran’s electricity market. In this paper, available methods were employed to develop a new technique of Wavelet-Neural Networks-Particle Swarm Optimization-Simulation-Optimization (WT-NNPSO-SO) with the purpose of searching in Big Data stored in the electricity market and improving the accuracy of short-term forecasting of electricity supply and demand. The electricity market data exploration approach was based on the simulation-optimization algorithms. It was combined with the Wavelet-Neural Networks-Particle Swarm Optimization (Wavelet-NNPSO) method to improve the forecasting accuracy with the assumption Length of Training Data (LOTD) increased. In comparison with previous techniques, the runtime of the proposed technique was improved in larger sizes of data due to the use of metaheuristic algorithms. The findings were dealt with in the Results section.

scholarly journals STRATEGI PEMASARAN PENGEMBANGAN INVESTASI BISNIS KOMPONEN BAHAN BAKU PADA PT. EGA NUSANTARA

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Eko Yogy Prasetyo ◽  
AEP RUHANDI
Keyword(s):  
Swot Analysis ◽  
Supply And Demand ◽  
Business Plan ◽  
Marketing Strategies ◽  
Electricity Sector ◽  
Electricity Supply ◽  
Current Transformers ◽  
Medium Voltage ◽  
Electricity System ◽  
Brunei Darussalam

PT. Ega Nusantara is one of the medium voltage panel maker companies in Indonesia. Where the majority of products are used by PT. PLN throughout Indonesia. PT. Ega Nusantara seeks to improve its competitiveness by adding new products outside the panel, namely current transformers, voltage transformers, bushings, capacitive deviders, insulators and load break switches. The whole component is a panel supporting component made from epoxy resin. To expand, a study of marketing strategies is needed using SWOT analysis and identifies the company's internal and external environmental factors that influence marketing strategies. Indonesia's current economic growth requires the support of reliable energy supplies including electricity. Electricity needs will increase in line with economic development and population growth. Based on the RUPTL (Electricity Supply Business Plan) PT. PLN, Indonesia have’t get the electricity of all regions could become potential investment in the electricity sector. The electrification ratio up to 2016 was 91.16%. When compared to Singapore it's already 100%, Brunei Darussalam 99.7%, Malaysia 99.0%, Thailand 99.3%, and Vietnam 98.0%. In addition to the condition of the electrification ratio that has not reached 100%, the condition of the electricity supply in the national electricity system also reflects the imbalance between supply and demand, with these conditions, of course, there are still opportunities for investors to participate in electricity supply businesses.

scholarly journals Long-Term Electricity Supply and Demand Forecast (2018–2040): A LEAP Model Application towards a Sustainable Power Generation System in Ecuador

2019 ◽  
Vol 11 (19) ◽  
pp. 5316 ◽  
Author(s):  
Luis Rivera-González ◽  
David Bolonio ◽  
Luis F. Mazadiego ◽  
Robert Valencia-Chapi
Keyword(s):  
Power Generation ◽  
Fuel Consumption ◽  
Current System ◽  
Supply And Demand ◽  
Production Costs ◽  
Electricity Supply ◽  
Generation System ◽  
Demand Forecast ◽  
Power Generation System ◽  
Sustainable Power

This research assesses the Ecuadorian power generation system, estimating the electricity supply and demand forecast until 2040. For this purpose, three potential alternative scenarios were analyzed using the Long-range Energy Alternatives Planning (LEAP) System; S1: Business As Usual; S2: Power Generation Master Plan; and S3: Sustainable Power Generation System. The main goal of this study is to analyze the possible alternatives for electricity supply and demand, fuel consumption, and the future structure of the Ecuadorian power generation system to transform the current system based on petroleum fuels into a sustainable system that consumes natural gas, and progressively introduces renewable power generation plants such as solar, wind, biomass, and hydroelectric until 2040. According to the estimated results through the inclusion of sustainable energy policies, S3 scenario relative to S1 scenario could reduce the average CO2 equivalent (CO2e) emissions by 11.72%, the average production costs by 9.78%, and the average petroleum fuel consumption by 15.95%. Consequently, a correct energy transition contributes to the protection of the environment and public health and has a direct effect on economic savings for the state, which benefits to improve the citizen’s quality of life.

scholarly journals A Study on Optimal Power System Reinforcement Measures Following Renewable Energy Expansion

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5929
Author(s):  
Hyuk-Il Kwon ◽  
Yun-Sung Cho ◽  
Sang-Min Choi
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Transmission Lines ◽  
Large Scale ◽  
Supply And Demand ◽  
Electricity Supply ◽  
Static And Dynamic Analysis ◽  
The Future ◽  
Reinforcement Measures

Renewable energy generation capacity in Korea is expected to reach about 63.8 GW by 2030 based on calculations using values from a power plan survey (Korea’s renewable energy power generation project plan implemented in September 2017) and the “3020” implementation plan prescribed in the 8th Basic Plan for Long-Term Electricity Supply and Demand that was announced in 2017. In order for the electrical grid to accommodate this capacity, an appropriate power system reinforcement plan is critical. In this paper, a variety of scenarios are constructed involving renewable energy capacity, interconnection measures and reinforcement measures. Based on these scenarios, the impacts of large-scale renewable energy connections on the future power systems are analyzed and a reinforcement plan is proposed based on the system assessment results. First, the scenarios are categorized according to their renewable energy interconnection capacity and electricity supply and demand, from which a database is established. A dynamic model based on inverter-based resources is applied to the scenarios here. The transmission lines, high-voltage direct current and flexible alternating current transmission systems are reinforced to increase the stability and capabilities of the power systems considered here. Reinforcement measures are derived for each stage of renewable penetration based on static and dynamic analysis processes. As a result, when large-scale renewable energy has penetrated some areas in the future in Korean power systems, the most stable systems could be optimally configured by applying interconnection measure two and reinforcement measure two as described here. To verify the performance of the proposed methodology, in this paper, comprehensive tests are performed based on predicted large-scale power systems in 2026 and 2031. Database creation and simulation are performed semi-automatically here using Power System Simulator for Engineering (PSS/E) and Python.

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