It includes the detail analysis of the various types electrical load, how to estimatate the load, methods of load forecasting and explanation of the load duration curves.
This document discusses various problems facing the electricity industry and methods for long term load forecasting. It outlines common electrical problems like intermittent power, power surges, sags and outages. It then describes methods for long term load forecasting including trend analysis, econometric modeling and end-use analysis. Trend analysis uses past load data to predict future load. Econometric modeling establishes relationships between load and driving parameters statistically and forecasts load based on projected parameters.
Short-term Load Forecasting based on Neural network and Local RegressionJie Bao
The document outlines different approaches to short-term load forecasting (STLF), including neural networks, moving averages, and local regression. It discusses using neural networks to model the complex relationships between load and determining factors like weather, calendar effects, and past loads. Moving averages are also explored, with modifications like temperature shifting to improve accuracy. Combining neural networks and local regression is proposed to better capture different timescales in load patterns.
Power system planning involves studies ranging from 1-10 years to determine generation, transmission, and distribution infrastructure needs. Key aspects of transmission planning include load forecasting, generation expansion planning to meet load, substation expansion planning, network expansion planning to transmit power from generators to loads, and reactive power planning. Both static planning looking at single time periods and dynamic planning considering multiple time periods simultaneously are used. Transmission planning is interconnected with generation planning, as transmission systems deliver power from generators to loads.
The document discusses load forecasting techniques and scheduling procedures in India's power system. It provides an overview of load forecasting, including the factors that affect load and different forecasting methods like extrapolation and correlation. It also describes the responsibilities of different load dispatch centers in India for scheduling generation and load. The scheduling procedure involves various timelines for generators to declare availability, beneficiaries to submit requisitions, and final schedules to be issued.
The document discusses load forecasting for power system planning. It defines load forecasting as projecting future load requirements using a systematic process. Accurate load forecasting is important for determining generation, transmission, and distribution capacity needs. The document describes different types of loads including domestic, commercial, industrial, agricultural, and others. It discusses various load forecasting techniques including extrapolation, correlation, and combinations. Key factors like weather impacts are also summarized.
This document provides an overview of power system planning and load forecasting. It discusses that load forecasting is the first crucial step for any power system planning study, as it involves predicting future load behavior. It describes different load forecasting techniques including extrapolation methods that use historical load data and trend curves, and correlation methods that relate loads to economic and demographic factors. The document also discusses factors that affect load forecasting like time of day, weather, customer class, and economics. Overall it provides a high-level introduction to the concepts and process of load forecasting for power system planning.
Group 7 load forecasting&harmonics final pptRahul Sharma
1) The document discusses load forecasting, including the objectives, factors influencing it, and types based on time frame.
2) Key factors in load forecasting include population, living standards, geographical location, cost of power, weather, time of day, and customer class. Accurate load forecasting helps utilities with generation planning and infrastructure development.
3) The document covers various load forecasting methods including time series analysis, regression/trend analysis, and correlation theory. Time series models include additive and multiplicative models, while regression analyzes trends using linear, exponential, power, and polynomial curves.
Power system planning & operation [eceg 4410]Sifan Welisa
The document discusses power load forecasting and substation planning. It explains that accurate load forecasting is important for power system planning and operation. Several load forecasting methods are described, including those based on historical load data, economic factors, and standardized load curves. Load forecasts can be short, medium, or long-term. The document also discusses factors to consider in substation planning and design, such as location, equipment requirements, and configuration. Feasibility studies are important for assessing potential hydroelectric and substation projects.
This document discusses various problems facing the electricity industry and methods for long term load forecasting. It outlines common electrical problems like intermittent power, power surges, sags and outages. It then describes methods for long term load forecasting including trend analysis, econometric modeling and end-use analysis. Trend analysis uses past load data to predict future load. Econometric modeling establishes relationships between load and driving parameters statistically and forecasts load based on projected parameters.
Short-term Load Forecasting based on Neural network and Local RegressionJie Bao
The document outlines different approaches to short-term load forecasting (STLF), including neural networks, moving averages, and local regression. It discusses using neural networks to model the complex relationships between load and determining factors like weather, calendar effects, and past loads. Moving averages are also explored, with modifications like temperature shifting to improve accuracy. Combining neural networks and local regression is proposed to better capture different timescales in load patterns.
Power system planning involves studies ranging from 1-10 years to determine generation, transmission, and distribution infrastructure needs. Key aspects of transmission planning include load forecasting, generation expansion planning to meet load, substation expansion planning, network expansion planning to transmit power from generators to loads, and reactive power planning. Both static planning looking at single time periods and dynamic planning considering multiple time periods simultaneously are used. Transmission planning is interconnected with generation planning, as transmission systems deliver power from generators to loads.
The document discusses load forecasting techniques and scheduling procedures in India's power system. It provides an overview of load forecasting, including the factors that affect load and different forecasting methods like extrapolation and correlation. It also describes the responsibilities of different load dispatch centers in India for scheduling generation and load. The scheduling procedure involves various timelines for generators to declare availability, beneficiaries to submit requisitions, and final schedules to be issued.
The document discusses load forecasting for power system planning. It defines load forecasting as projecting future load requirements using a systematic process. Accurate load forecasting is important for determining generation, transmission, and distribution capacity needs. The document describes different types of loads including domestic, commercial, industrial, agricultural, and others. It discusses various load forecasting techniques including extrapolation, correlation, and combinations. Key factors like weather impacts are also summarized.
This document provides an overview of power system planning and load forecasting. It discusses that load forecasting is the first crucial step for any power system planning study, as it involves predicting future load behavior. It describes different load forecasting techniques including extrapolation methods that use historical load data and trend curves, and correlation methods that relate loads to economic and demographic factors. The document also discusses factors that affect load forecasting like time of day, weather, customer class, and economics. Overall it provides a high-level introduction to the concepts and process of load forecasting for power system planning.
Group 7 load forecasting&harmonics final pptRahul Sharma
1) The document discusses load forecasting, including the objectives, factors influencing it, and types based on time frame.
2) Key factors in load forecasting include population, living standards, geographical location, cost of power, weather, time of day, and customer class. Accurate load forecasting helps utilities with generation planning and infrastructure development.
3) The document covers various load forecasting methods including time series analysis, regression/trend analysis, and correlation theory. Time series models include additive and multiplicative models, while regression analyzes trends using linear, exponential, power, and polynomial curves.
Power system planning & operation [eceg 4410]Sifan Welisa
The document discusses power load forecasting and substation planning. It explains that accurate load forecasting is important for power system planning and operation. Several load forecasting methods are described, including those based on historical load data, economic factors, and standardized load curves. Load forecasts can be short, medium, or long-term. The document also discusses factors to consider in substation planning and design, such as location, equipment requirements, and configuration. Feasibility studies are important for assessing potential hydroelectric and substation projects.
Introduction, Factors affecting system planning, present planning techniques, planning models, Sub-transmission and substation design. Sub-transmission networks configurations, Substation bus schemes, Distribution substations ratings, Service areas calculations, and Substation application curves, future trends in planning, systems approach, and Distribution automation.
The document provides an introduction to power system analysis. It discusses the components of a power system including generators, transformers, transmission lines and loads. It explains that power system analysis involves monitoring the system through load flow analysis, short circuit analysis and stability analysis in order to maintain the system safely and economically. It also discusses the need for power system analysis in planning and operating the system, and ensuring power demand is met through reliable generation and transmission of electricity.
Summary of Modern power system planning part one
"The Forecasting of Growth of Demand for Electrical Energy"
the main topic of this chapter is the analysis of the various techniques required for utility planning engineers to optimally plan the expansion of the electrical power system.
concept of resilience and self healing in smart gridKundan Kumar
The document discusses concepts related to resilience and self-healing in smart grids. It defines a smart grid as an electrical grid using communications technologies to improve efficiency. Key functions include enabling customer participation and accommodating different generation options. Self-healing is the ability of a system to automatically restore itself without human intervention. For the electrical grid, this means timely detection of issues and minimizing loss of service through reconfiguring resources. The transmission and distribution components can be modeled using graph theory to analyze resilience. Automatic meter reading is one approach for distribution grids.
Introduction about Power System Planning in the Presence of Uncertainties ahmedgoun
Uncertainties are a key consideration in power system planning. In a regulated environment, a single entity handles generation, transmission, and distribution and faces uncertainties from load forecasting and other input parameters. In a deregulated environment, independent generation, transmission, and distribution companies each aim to maximize profits, introducing new uncertainties as decisions are no longer coordinated. Generation expansion planning faces fuel cost and electricity price uncertainties. Transmission expansion planning uncertainties stem from predicting generation expansions by other market players. Advanced uncertainty calculation methods can help reduce risks and errors in power system planning.
Power system planning involves arranging a scheme beforehand to adequately satisfy future load requirements. It determines new and upgraded generation, transmission, and distribution elements. Load forecasting is an important part of planning to estimate future loads. Short term forecasting is used for operations while long term forecasting informs infrastructure development decisions. Various statistical, artificial intelligence, and hybrid methods are used for load forecasting at different timescales, each with their own advantages and limitations regarding accuracy. Accurate load forecasting is essential for utility planning and operations.
Load forecasting is essential for power system planning to estimate future demand and energy requirements. Accurate load forecasts are needed to determine generation capacity additions, transmission and distribution infrastructure requirements, fuel procurement, and other planning decisions. Load forecasts can predict short-term (1 hour to 1 week) loads with about 1-3% accuracy but long-term (over 1 year) forecasts are less accurate due to uncertainties in weather predictions. Load forecasting helps utilities make important decisions around power purchasing, generation, and infrastructure development.
This document discusses economics factors related to power plants, including:
- Key terms like load factor, utility factor, and plant operating factor that relate to a power plant's usage and efficiency.
- Components of fixed costs for a power plant like land, equipment, and maintenance.
- Operating costs including fuel, labor, water, and transmission/distribution.
- Load curves that show power demand over time and factors like diversity factor and plant capacity factor that relate demand to a plant's maximum output.
- Different tariff methods used to calculate customer bills based on maximum demand, energy consumed, and other factors.
This document provides an overview of load forecasting in the power system planning process. It discusses the need for load forecasting to determine generation, transmission, and distribution capacity needs. Accurate load forecasting is important to avoid excess or insufficient investment. The document outlines different load classification categories and forecasting methodologies. It also examines factors like weather that impact load forecasting and concludes that regular adjustments are needed to forecasts to account for seasonal and other usage changes.
This document describes a project to build a third harmonic distortion meter using a PIC18F2550 microcontroller. It explains that non-linear components can cause harmonics in AC power systems, with the third harmonic being particularly impactful. The project involves using a microcontroller and discrete Fourier transform calculations to measure the amplitude of the fundamental frequency and third harmonic from a rectified input signal. This allows the third harmonic distortion to be displayed as a percentage. The document provides details of the circuit design and software used to implement this third harmonic distortion meter.
1) A load curve shows the variation of load on a power station over time, with daily, monthly, and yearly curves. It is important for generation planning and economic dispatch.
2) A load duration curve arranges all load levels in descending order, with area under the curve representing total energy demanded. It is used for planning, dispatch, and reliability evaluation.
3) An integrated load duration curve plots units generated against load demand, obtained from the load duration curve. A mass curve plots accumulated supply or demand over time and is used to determine required storage capacity.
The document discusses demand side management (DSM) strategies to efficiently manage electricity demand. It covers:
1. The goals of DSM including encouraging off-peak energy use and reducing environmental impacts.
2. Key steps in planning and implementing DSM programs including load forecasting, identifying target sectors and efficiency measures, and designing incentive programs.
3. Examples of DSM strategies for different sectors like encouraging efficient pump use in agriculture and promoting efficient appliances in residential and commercial buildings.
The load on a power station varies over time rather than being constant. This variability in load presents challenges for power stations, as they must produce power whenever demanded by consumers. Variable loads can necessitate additional equipment to vary the fuel supply and increase production costs, as generator efficiency decreases during light loads. Load curves are used to analyze and understand load patterns, showing how demand changes over various time periods from daily to annually. This information is important for power station operation and planning.
Lecture 2: Electrical load demand analysis and management Eyad Adnan
Lecture 2: Electrical load demand analysis and management ;
.. Estimate and Review Load & energy demand assessment
... determine the figure of demand daily kwh consumption for specific building/customers
... Establish Work Plan to Get daily KWH
......Optimizing energy consumption by using potentials for opportunities conservation tools and measures
This document discusses the selection of circuit breakers. It begins by defining a circuit breaker as a protective device that is used to automatically open the faulty part of a power system during a fault. There are two main factors considered when selecting a circuit breaker: 1) its normal working power level and fault level ratings, which are specified by the rated interrupting current or MVA, and 2) its momentary current and speed ratings. The momentary current rating must be higher than the maximum current during fault conditions, while the speed rating depends on transient fault currents and specified cycles. Multiplying factors are used to determine the circuit breaker's short circuit interrupting current from fault analysis calculations.
This document provides an overview of optimization techniques applied to solve the unit commitment problem for a 10 unit power system. It describes the objective function and constraints of the unit commitment problem formulation. It then briefly introduces several common optimization techniques used to solve unit commitment, including simulated annealing, harmony search, and multi-agent evolutionary programming incorporating a priority list. The document presents cost comparisons of applying different optimization techniques to the standard 10 unit test system, including tabular and graphical summaries of results from research papers. It concludes with references.
This document presents an overview of economic load dispatch in power systems. It discusses the objectives of economic dispatch as generating required power at minimum cost. It describes different constraints like generator limits, transmission limits and voltage limits that need to be considered. It explains the operating costs of thermal plants using heat rate and fuel cost curves. It provides formulations for economic dispatch neglecting and including transmission losses. The document uses examples to illustrate the iterative method used to solve economic dispatch problems.
The document provides details of the planning and design of the distribution system for Malda Polytechnic. It includes:
- An introduction to the project members and the importance of planning distribution systems.
- Details of the load survey conducted, including load calculations for hostels, offices, and buildings on campus.
- Definitions of key terms like connected load and demand factors.
- Calculations of the total load for the campus and determination of the optimal load center location.
- Considerations for future load prediction and design of the transmission and distribution system in accordance with Indian electricity rules.
This document discusses national and regional power system planning in India. It begins with an introduction to power system planning, including transmission versus distribution planning and long-term versus short-term planning. It then covers various aspects of planning such as generation planning, capacity resource planning, and transmission planning. The document outlines the five electricity regions in India and discusses the economic benefits of regional coordination in planning. It concludes with mentions of integrated resource planning and least cost utility planning strategies.
The document discusses the mechanical design of overhead power lines. It describes the main components of overhead lines which include conductors, supports, insulators, and cross arms. Conductors carry electric power and are made of materials like copper, aluminum, and steel that have high conductivity and strength. Supports can be wooden poles, steel poles, or lattice towers and must withstand mechanical loads. Insulators provide insulation between conductors and supports to prevent leakage currents. The document also covers factors that affect overhead line design like line voltage, conductor spacing, and methods to reduce corona effects like increasing conductor size.
The document provides information about load forecasting, earthing, megger testing, and earth leakage circuit breakers (ELCBs). It discusses several methods for short, medium, and long-term load forecasting including regression analysis and considering factors like weather, time of day, and customer class. It also describes the principles of earthing systems and equipment, how megger devices test insulation resistance, and the purpose and components of ELCBs in providing electrical safety.
The 5 core tools are recognized as standard quality tools for the automotive ...arvindsinghrathore6
The 5 core tools are recognized as standard quality tools for the automotive industry by AIAG, although they are also used in other manufacturing sectors such as aerospace, defense, medical, and pharmaceutical.
Introduction, Factors affecting system planning, present planning techniques, planning models, Sub-transmission and substation design. Sub-transmission networks configurations, Substation bus schemes, Distribution substations ratings, Service areas calculations, and Substation application curves, future trends in planning, systems approach, and Distribution automation.
The document provides an introduction to power system analysis. It discusses the components of a power system including generators, transformers, transmission lines and loads. It explains that power system analysis involves monitoring the system through load flow analysis, short circuit analysis and stability analysis in order to maintain the system safely and economically. It also discusses the need for power system analysis in planning and operating the system, and ensuring power demand is met through reliable generation and transmission of electricity.
Summary of Modern power system planning part one
"The Forecasting of Growth of Demand for Electrical Energy"
the main topic of this chapter is the analysis of the various techniques required for utility planning engineers to optimally plan the expansion of the electrical power system.
concept of resilience and self healing in smart gridKundan Kumar
The document discusses concepts related to resilience and self-healing in smart grids. It defines a smart grid as an electrical grid using communications technologies to improve efficiency. Key functions include enabling customer participation and accommodating different generation options. Self-healing is the ability of a system to automatically restore itself without human intervention. For the electrical grid, this means timely detection of issues and minimizing loss of service through reconfiguring resources. The transmission and distribution components can be modeled using graph theory to analyze resilience. Automatic meter reading is one approach for distribution grids.
Introduction about Power System Planning in the Presence of Uncertainties ahmedgoun
Uncertainties are a key consideration in power system planning. In a regulated environment, a single entity handles generation, transmission, and distribution and faces uncertainties from load forecasting and other input parameters. In a deregulated environment, independent generation, transmission, and distribution companies each aim to maximize profits, introducing new uncertainties as decisions are no longer coordinated. Generation expansion planning faces fuel cost and electricity price uncertainties. Transmission expansion planning uncertainties stem from predicting generation expansions by other market players. Advanced uncertainty calculation methods can help reduce risks and errors in power system planning.
Power system planning involves arranging a scheme beforehand to adequately satisfy future load requirements. It determines new and upgraded generation, transmission, and distribution elements. Load forecasting is an important part of planning to estimate future loads. Short term forecasting is used for operations while long term forecasting informs infrastructure development decisions. Various statistical, artificial intelligence, and hybrid methods are used for load forecasting at different timescales, each with their own advantages and limitations regarding accuracy. Accurate load forecasting is essential for utility planning and operations.
Load forecasting is essential for power system planning to estimate future demand and energy requirements. Accurate load forecasts are needed to determine generation capacity additions, transmission and distribution infrastructure requirements, fuel procurement, and other planning decisions. Load forecasts can predict short-term (1 hour to 1 week) loads with about 1-3% accuracy but long-term (over 1 year) forecasts are less accurate due to uncertainties in weather predictions. Load forecasting helps utilities make important decisions around power purchasing, generation, and infrastructure development.
This document discusses economics factors related to power plants, including:
- Key terms like load factor, utility factor, and plant operating factor that relate to a power plant's usage and efficiency.
- Components of fixed costs for a power plant like land, equipment, and maintenance.
- Operating costs including fuel, labor, water, and transmission/distribution.
- Load curves that show power demand over time and factors like diversity factor and plant capacity factor that relate demand to a plant's maximum output.
- Different tariff methods used to calculate customer bills based on maximum demand, energy consumed, and other factors.
This document provides an overview of load forecasting in the power system planning process. It discusses the need for load forecasting to determine generation, transmission, and distribution capacity needs. Accurate load forecasting is important to avoid excess or insufficient investment. The document outlines different load classification categories and forecasting methodologies. It also examines factors like weather that impact load forecasting and concludes that regular adjustments are needed to forecasts to account for seasonal and other usage changes.
This document describes a project to build a third harmonic distortion meter using a PIC18F2550 microcontroller. It explains that non-linear components can cause harmonics in AC power systems, with the third harmonic being particularly impactful. The project involves using a microcontroller and discrete Fourier transform calculations to measure the amplitude of the fundamental frequency and third harmonic from a rectified input signal. This allows the third harmonic distortion to be displayed as a percentage. The document provides details of the circuit design and software used to implement this third harmonic distortion meter.
1) A load curve shows the variation of load on a power station over time, with daily, monthly, and yearly curves. It is important for generation planning and economic dispatch.
2) A load duration curve arranges all load levels in descending order, with area under the curve representing total energy demanded. It is used for planning, dispatch, and reliability evaluation.
3) An integrated load duration curve plots units generated against load demand, obtained from the load duration curve. A mass curve plots accumulated supply or demand over time and is used to determine required storage capacity.
The document discusses demand side management (DSM) strategies to efficiently manage electricity demand. It covers:
1. The goals of DSM including encouraging off-peak energy use and reducing environmental impacts.
2. Key steps in planning and implementing DSM programs including load forecasting, identifying target sectors and efficiency measures, and designing incentive programs.
3. Examples of DSM strategies for different sectors like encouraging efficient pump use in agriculture and promoting efficient appliances in residential and commercial buildings.
The load on a power station varies over time rather than being constant. This variability in load presents challenges for power stations, as they must produce power whenever demanded by consumers. Variable loads can necessitate additional equipment to vary the fuel supply and increase production costs, as generator efficiency decreases during light loads. Load curves are used to analyze and understand load patterns, showing how demand changes over various time periods from daily to annually. This information is important for power station operation and planning.
Lecture 2: Electrical load demand analysis and management Eyad Adnan
Lecture 2: Electrical load demand analysis and management ;
.. Estimate and Review Load & energy demand assessment
... determine the figure of demand daily kwh consumption for specific building/customers
... Establish Work Plan to Get daily KWH
......Optimizing energy consumption by using potentials for opportunities conservation tools and measures
This document discusses the selection of circuit breakers. It begins by defining a circuit breaker as a protective device that is used to automatically open the faulty part of a power system during a fault. There are two main factors considered when selecting a circuit breaker: 1) its normal working power level and fault level ratings, which are specified by the rated interrupting current or MVA, and 2) its momentary current and speed ratings. The momentary current rating must be higher than the maximum current during fault conditions, while the speed rating depends on transient fault currents and specified cycles. Multiplying factors are used to determine the circuit breaker's short circuit interrupting current from fault analysis calculations.
This document provides an overview of optimization techniques applied to solve the unit commitment problem for a 10 unit power system. It describes the objective function and constraints of the unit commitment problem formulation. It then briefly introduces several common optimization techniques used to solve unit commitment, including simulated annealing, harmony search, and multi-agent evolutionary programming incorporating a priority list. The document presents cost comparisons of applying different optimization techniques to the standard 10 unit test system, including tabular and graphical summaries of results from research papers. It concludes with references.
This document presents an overview of economic load dispatch in power systems. It discusses the objectives of economic dispatch as generating required power at minimum cost. It describes different constraints like generator limits, transmission limits and voltage limits that need to be considered. It explains the operating costs of thermal plants using heat rate and fuel cost curves. It provides formulations for economic dispatch neglecting and including transmission losses. The document uses examples to illustrate the iterative method used to solve economic dispatch problems.
The document provides details of the planning and design of the distribution system for Malda Polytechnic. It includes:
- An introduction to the project members and the importance of planning distribution systems.
- Details of the load survey conducted, including load calculations for hostels, offices, and buildings on campus.
- Definitions of key terms like connected load and demand factors.
- Calculations of the total load for the campus and determination of the optimal load center location.
- Considerations for future load prediction and design of the transmission and distribution system in accordance with Indian electricity rules.
This document discusses national and regional power system planning in India. It begins with an introduction to power system planning, including transmission versus distribution planning and long-term versus short-term planning. It then covers various aspects of planning such as generation planning, capacity resource planning, and transmission planning. The document outlines the five electricity regions in India and discusses the economic benefits of regional coordination in planning. It concludes with mentions of integrated resource planning and least cost utility planning strategies.
The document discusses the mechanical design of overhead power lines. It describes the main components of overhead lines which include conductors, supports, insulators, and cross arms. Conductors carry electric power and are made of materials like copper, aluminum, and steel that have high conductivity and strength. Supports can be wooden poles, steel poles, or lattice towers and must withstand mechanical loads. Insulators provide insulation between conductors and supports to prevent leakage currents. The document also covers factors that affect overhead line design like line voltage, conductor spacing, and methods to reduce corona effects like increasing conductor size.
The document provides information about load forecasting, earthing, megger testing, and earth leakage circuit breakers (ELCBs). It discusses several methods for short, medium, and long-term load forecasting including regression analysis and considering factors like weather, time of day, and customer class. It also describes the principles of earthing systems and equipment, how megger devices test insulation resistance, and the purpose and components of ELCBs in providing electrical safety.
The 5 core tools are recognized as standard quality tools for the automotive ...arvindsinghrathore6
The 5 core tools are recognized as standard quality tools for the automotive industry by AIAG, although they are also used in other manufacturing sectors such as aerospace, defense, medical, and pharmaceutical.
Power system planning & operation [eceg 4410]Sifan Welisa
The document discusses several key considerations for transmission line design, including electrical, mechanical, and environmental factors. On the electrical side, low voltage drop and minimum power losses are priorities to ensure efficient power transmission. Conductor material and size are important to reduce resistance. Mechanically, the lines and supports must withstand the conductor weight, tension, and weather conditions. Environmental factors like heat, wind, and ice placement are also addressed to maintain safety and reliability of the transmission line.
The document discusses methods of short term, medium term, and long term load forecasting. It explains that load forecasts help electric utilities make important planning decisions. Short term forecasts are from 1 hour to 1 week, medium from 1 week to 1 year, and long term over 1 year. Factors that influence forecasts include time, weather, customer classes, historical load data, economic data, and appliance characteristics. Common forecasting methods include regression models, time series, neural networks, and end-use or econometric approaches. Accurate load forecasting is essential for utility operation and planning.
An overview of electricity demand forecasting techniquesAlexander Decker
This document provides an overview of different techniques for electricity demand forecasting. It begins by explaining the importance of accurate electricity demand forecasting for utility companies and market participants. It then divides forecasting into three categories based on timeframe: short-term (1 hour to 1 week), medium-term (1 week to 1 year), and long-term (over 1 year). The document goes on to group forecasting techniques into three major categories: traditional, modified traditional, and soft computing techniques. Traditional techniques discussed include regression, multiple regression, and exponential smoothing. The document provides mathematical equations to describe some of these traditional forecasting models.
Load foecasting and power procurement planning in power sectorManish Kumar
Load forecasting is important for electric utilities to make decisions around power purchasing, generation, and infrastructure development. There are short, medium, and long-term forecasts. A variety of mathematical methods are used for load forecasting, including statistical methods and artificial intelligence. Load forecasts help utilities properly plan their power systems, operations, transmission and distribution networks, financing, and more. Power procurement involves acquiring power based on load forecasts through processes like bidding and submitting resource plans.
The document provides an overview of power system operation and control. It discusses key definitions related to electric power systems like capacity, energy, load, demand, and load curves. It describes different types of loads including resistive, motor, electronic, and categories like domestic, commercial, industrial, and agricultural loads. It also discusses objectives of power system operation like supplying quality service at minimum cost and with acceptable environmental impact. Finally, it provides explanations of key functions of power system operation control including load frequency control, economic dispatch calculation, and operating reserve calculation. It also introduces the concepts of unit commitment and economic load dispatch in determining the most economic scheduling of power generation units.
This document provides an outline and introduction to load forecasting in power systems. It discusses the importance of load forecasting for system planning and operation. Different types of load forecasts like energy, demand, and peak demand are explained. Methodologies for load forecasting including extrapolation, correlation, and combining techniques are covered. Factors affecting load forecasting like time, weather, customer class are also summarized.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Here are the steps to solve this problem:
1. Calculate the individual maximum demands considering diversity factor:
Domestic load:
Max demand = 20000 kW
With diversity factor of 1.5, individual max demand = 20000/1.5 = 13333 kW
Commercial load:
Max demand = 20000 kW
With diversity factor of 1.4, individual max demand = 20000/1.4 = 14285 kW
Industrial load:
Max demand = 50000 kW
With diversity factor of 1.2, individual max demand = 50000/1.2 = 41667 kW
2. Calculate the total individual maximum demands:
Individual max (Domestic) = 13333 kW
Individual
Load forecasting aims to predict electricity demand with varying levels of accuracy over different timescales. Short-term load forecasting for the next day can predict load within 1-3% accuracy, while long-term forecasting for the next year's peak load is less accurate due to uncertain weather. Multiple factors influence load forecasting models, including weather, customer class, time of day or year, historical load data, and economic indicators. Common statistical techniques used include regression, time series, and neural networks to analyze these influencing factors for both short and long-term load forecasting needs.
Load forecasting aims to predict electricity demand with varying levels of accuracy over different timescales. Short-term load forecasting for the next day can predict load within 1-3% accuracy, while long-term forecasting for the next year is less accurate due to uncertain weather. Load forecasting is important for utilities to plan operations and pricing. Key factors influencing load include weather, customer class, time of day, and special events. Common forecasting methods use statistical and machine learning techniques to model load as a function of these influencing factors.
1. The document discusses various concepts related to power system operation and control including load forecasting, load curves, frequency regulation, and load frequency control.
2. Key terms defined include load factor, plant capacity factor, maximum demand, plant use factor, diversity factor, demand factor, spinning reserve, and area control error.
3. Factors affecting load forecasting are discussed including the need for long term, medium term, and short term forecasting for various power system planning and operation purposes.
The document discusses variable load problems in power plants. It defines key terms related to loads and demand such as load curve, load duration curve, load factor, demand factor, diversity factor, and plant factor. It explains that load varies over time due to different factors like type of service, day of week, season, and weather. Load curves graphically represent the variation in demand over time and are used to calculate important metrics. The document also provides examples of calculating metrics like load factor and presents sample problems.
This document discusses load forecasting methods for electric utilities. It describes short, medium, and long-term load forecasts and factors like weather, time, and customer class that influence accurate forecasts. Mathematical regression models are used to develop statistical learning models for long-term (2-3 years ahead) and short-term (48 hours ahead) load forecasting. Performance is evaluated based on correlation, R-squared value, and normalized distance between actual and predicted loads.
Seminar on load scheduling and load sheddingBIJAY NAYAK
This document discusses load scheduling and load shedding in power systems. It defines electrical load and explains that load scheduling is important for optimal system operation as loads increase. It describes the need for load scheduling to estimate instantaneous loads and guide equipment sizing. Load shedding is defined as disconnecting part of the load to balance demand with capacity during excess load situations, preventing overloads and instability. The document outlines methodologies for load scheduling and procedures for planned load shedding, and discusses advantages like preventing damage but also disadvantages like loss of production.
Similar to Load types, estimation, grwoth, forecasting and duration curves (20)
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
5. What is Load?
The Electrical Load is the part or
component in a circuit that converts
electricity into light, heat, or mechanical
motion. Example of loads are a light bulbs,
heater, motor or combination of all three.
6. Table of Content
Types of Load
Load Estimation
Load Growth
Load Forecasting
Load Duration Curves
7. Types of Load
According To Load Nature-1
Resistive Electrical Loads.
Capacitive Electrical Loads.
Inductive Electrical Loads.
Combination Electrical Loads.
13. What is Load Estimation?
At the beginning of the project , in the
draft design (early design) stage, the
electrical design professionals calculate
the estimate load of a particular confine
area
14. What is Load estimation?
The preliminary calculation of the load before the installation of
the power system is load estimation.
It is planned in the mind and designed on the paper, booklet,
sketch book and checked in the computer simulation software
for the correction, optimization and estimation.
Load estimation is completed, if simulation gives the desire
results of the designing.
15. Load estimation
Methodology
Make Analysis of load characteristics,
Review The available voltage system types/classes and levels.
Review the utility's rate structure,
Make roughly a key single-line diagram and a set of subsidiary
single-line diagrams. The key single-line diagram should show the
sources of power e.g. generators, utility intakes, the main
switchboard and the interconnections to the subsidiary or secondary
switchboards.
Develop Demand factor relationship between connected loads and
the actual demand imposed On the system.
16. How to do Load estimation?
(5) methods of electrical load estimations which are:
A)- Preliminary load calculation which divide to:
1. Space by space (functional area method),
2. Building Area method.
3. Area method.
B)- NEC load calculations.
C- Final load calculations.
17. Load Estimation
Importance
Importance of Electrical Load Estimation (preliminary load calculations)
Plan the connection to upstream network and MV circuit
configurations.
Plan the transformers substation(s) (if any) and the main
switchgear room.
Apply to Power Company for supply.
Calculate initial budget for the electrical works.
18. Table of Content
Types of Load
Load Estimation
Load Growth
Load Forecasting
Load Duration Curves
20. What is Electrical Load Growth?
It is simply an increase in energy demand.
Load growth occurs either through natural growth of a
service territory resulting from increased prosperity,
productivity or population growth.
It was once a common practice of utility companies to
encourage increased energy consumption and reliance
21. Electrical Load Growth
Two Causes of Load Growth
New Customer Addition: In migration, increase in
population, availability of electrical utility to remote
areas.
New uses of electricity: Gas heaters converted to
electrical heaters. Likewise, use of Air Conditioning
increase due to effect of global warming.
22. Load Growth Terms
Dormant period: The time "before growth" when no load growth
occurs. The small area has no load and experiences no growth.
Growth ramp: During this period growth occurs at a relatively
rapid rate, because of new construction in the small area.
Saturated period: The small area is "filled up" — fully developed.
Load growth may continue, but at a low level compared to that
during the growth ramp.
26. Load Forecasting
Definition: A process in which the aim is to decide on
new as well as upgrading existing system elements, to
adequately satisfy the loads for a foreseen future
Elements can be:
Generation facilities
Substations
Transmission lines and/or cables
Capacitors/Reactors
Etc.
27. Load Forecasting
Decision should be
Where to allocate the element (for instance, the
sending and receiving end of a line),
When to install the element (for instance, 2020),
What to select, in terms of the element
specifications (for instance, number of bundles and
conductor type).
The loads should be adequately satisfied.
28. Load Forecasting
The first crucial step for any planning study
Forecasting refers to the prediction of the load
behavior for the future
Words such as, demand and consumption are also
used instead of electric load
Energy (MWh, kWh) and power (MW,kW) are the two
basic parameters of a load.
By load, we mean the power.
Demand forecast
To determine capacity of generation, transmission and
distribution required
Energy forecast
To determine the type of generation facilities required
29. Load Forecasting
Methodology
Forecasting: systematic procedure for quantitatively
defining future loads.
Classification depending on the time period:
Short term
Intermediate
Long term
Forecast will imply an intermediate-range forecast
Planning for the addition of new generation,
transmission and distribution facilities must begin 4-10
years in advance of the actual in-service date.
30. Load Forecasting
Techniques
Three broad categories based on:
• Extrapolation:
– Time series method
– Use historical data as the basis of estimating
future outcomes.
• Correlation:
– Econometric forecasting method
– identify the underlying factors that might
influence the variable that is being forecast.
• Combination of both
31. Load Forecasting
Factors
Time factors such as:
Hours of the day (day/night)
Day of the week (week day/weekend)
Time of the year (season)
Weather conditions (temperature and humidity)
Class of customers (residential, commercial,
industrial, agricultural, public, etc.)
Special events (TV programmes, public holidays, etc.)
Population
Economic indicators (per capita income, Gross
National Product (GNP), Gross Domestic Product
(GDP), etc.)
Trends in using new technologies
Electricity price
32. Load Forecasting
Impact of Weather
Average temperature is the most significant
weather dependent factor that influences load
variations.
Temperature and load are not linearly related.
Non-linearity is further complicated by the
influence of
Humidity
Extended periods of extreme heat or cold spells
In load forecast models proper temperature
ranges and representative average temperatures
which cover all regions of the area served by the
electric utility should be selected.
33. Load Forecasting
Peak Load
Extrapolate historical demand data
Weather conditions can be included
Basic approach for weekly peak demand forecast is:
1. Determine seasonal weather load model.
2. Separate historical weather-sensitive and non-weather sensitive
components of weekly peak demand using weather load model.
3. Forecast mean and variance of non-weather-sensitive component of
demand.
4. Extrapolate weather load model and forecast mean and variance of
weather sensitive component.
5. Determine mean, variance and density function of total weekly forecast.
6. Calculate density function of monthly/annual forecast.
34. Load Forecasting
Peak Load
Assume that the seasonal variations of the peak
demand are primarily due to weather.
Otherwise, before step-3 can be undertaken, any
additional seasonal variation remaining after
weather-sensitive variations must be removed
To use the proposed forecasting method, a data base
of at least 12 years is recommended.
To develop weather load models daily peaks and
coincident weather variable values are needed.
35. Table of Content
Types of Load
Load Estimation
Load Growth
Load Forecasting
Load Duration Curves
36. What is Load Duration Curves?
Definition:
When the load elements of a load curve are
arranged in the order of descending
magnitudes, the curve thus obtained is called a
load duration curve
38. Load Duration Curves
Variations in load on a power station from time to time:
Daily load curves
Monthly load curves
Annual load curves
Load curve gives:
Variation of load during different time
Total no. of units generated
Maximum demand
Average load on a power station
Load factor
We know DC System obeys Ohm’s Law. So what about AC System?
AC System Follows Ohm’s Law
Explain it with Example: Generation side phase angle is φ and at the distribution site it becomes ( φ ± ϵ ). The Є factor is actually non-linearity which disobeys Ohm’s Law.
Non-linearity comes into action due to the reasons of corona losses, magnetization loss, transformer hysteresis & eddy current losses and heating effect of wires.
Ideal capacitors and inductors tends AC System to follow Ohm’s Law.
According To Load Grouping: Individual or Load Centers
According To Load Planning : Estimation, Growth , Forecasting of new loads
According To Load Operation Time: Continuous, Non-Continuous, Periodic
According To Load Importance: Life safety, Emergency (hospitals) , Normal
According To Load /phase distribution Single Phase & Three Phase
Number of instruments and equipment needed and their cost is predicted
IPPS can play the part
Block Rate Tariff
These two factors increases the peak load and eventually the annual load.
Peak Load Forecasting Steps and Techniques
Advantage: Max, Peak and Average demand is easily getable in a descending order by load duration curve
Disadvantage: Time of a single day is not understood by load duration curve, so cant deicide other factors like weather, etc.
Similarity: Area under curve or graph is equal in both cases