Electrical Load and Energy Forecasting, Planning & Demand Side Management

Course Code: EEC 1048

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Course Sector:

Electrical Engineering

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Course Dates and Locations

Choose a date and location to book your seat

No.

Date

Days

Location

Fees

Enrollment

01 - 12 Sep 2025

10 Days

Dubai, UAE

$8,500

07 - 18 Dec 2025

10 Days

Salalah, Oman

$8,500

22 Dec 2025 - 02 Jan 2026

10 Days

Kuala Lumpur,Malaysia

$8,950

Introduction

Training course introducion / brief

This course will assist power system professionals in planning and operating a power system with increasing penetration of Demand Side Management (DSM) Programs renewable resources. Renewable generation impacts both the planning and the operating criteria. These criteria are examined in detail along with the new requirements for generation reserve margins. Distributed generation and smart meter infrastructures are discussed in light of commercial and residential programs. Weather volatility impacts the demand profile. Weather normal methodologies are presented along with short and long terms forecasting models. Demand Side Management programs are a fine balancing act between demand, supply and customer choice (and incentives).

The Power of Agile Virtual Devices.

The course presents various facets of demand side management and the broader smart grid roadmaps for customers. The Internet of Things/ The Internet of Everything is a game changer through the Power of Agile Virtual Devices. The course presents how new Devices bring new Analytics and innovative approaches to Demand Side Management.

Set Power System Planning Objectives
Gain knowledge about Load Forecasting Methodologies
Identify Factors affecting Load Forecasting
Have a good understanding of different kinds of Short Term and Long Term Planning
Examine the principle of Energy supply & demand forecasting with a National and Regional perspectives
Assess the market conditions that effect power and energy generation, transmission and distribution
Understand the critical role of energy demand forecasting in the market.
Utilize the various methodologies and technologies to meet the challenges of energy demand forecasting

Circuits Engineer
Design Engineer
Electrical Controls Engineer
Electrical Design Engineer
Electrical Engineer
Electrical Project Engineer
Electronics-research engineer
Instrumentation and Electrical (I&E) Reliability Engineer
Power Systems Engineer
Project Engineer
Test Engineer
illuminating engineer
Technician, semiconductor development
Power-distribution engineer
Controls design engineer

Module (01) Bulk Electricity System

1.1 Generation System
1.2 Transmission System
1.3 North American Electricity Reliability Council (NERC) STANDARDS and REQUIREMENTS

Module (02) Energy Markets

2.1 Real Time Market
2.2 Day Ahead Market
2.3 Bilateral Contracts
2.3.1 Terms and Structures of Renewable Contracts
2.3.2 FIT in Tariffs in Canada
2.4 Physical versus Financial Transactions
2.4.1 Generator Offers into Market
2.4.2 Dispatchable Loads

Module (03) Load Forecasting Methodology

3.1 3Weather Forecasts
3.2 Simulation, Optimization, Sensitivity Analysis
3.3 Forecasting Methodologies and statistical techniques, Neural-Net modeling, End-Use modeling, Metrix ND & LT)
3.4 Weather Normalization and Probability Distribution Tools

Module (04) Load Demand Patterns

4.1 Short Term Load Forecasting Models: Operating Time Frame
4.2 Long Term Load Forecasting Models: Planning Time Frame
4.3 Weather Normal load forecasting

Module (05) Volumetric Risk

5.1 Weather Response
5.2 Weather Derivatives
5.3 How can data be used for decision making?
5.4 What data will be needed in future?
5.5 What data should be collected (and analyzed) now?

Module (06) Long Term Planning

6.1 Reliability Criteria
6.2 Generation Reserve Margin
6.3 Loss of Load Probability
6.4 Loss of Load Expectation
6.5 Variable generation and their impact on the LOLP, LOLE
6.6 Capacity Planning
6.6.1 Renewable Generation
6.6.2 Demand Management
6.6.3 Case Study

Module (07) Short Term Planning

7.1 Day Ahead
7.2 Real Time
7.3 Secure Islanding of Power Plants
7.4 Operating Reserves in a System With Renewable Generation

Module (08) System Controls for Power Quality for Demand

8.1 Power Electronics
8.1.1 Static VAR Compensators
8.1.2 Voltage and VAR Control
8.1.3 Smart Inverters

Module (09) Demand Side Management and the Physical System

9.1 Load Frequency Control
9.2 Load Pricing Control & Load Shedding

Module (10) Demand Side Management

10.1 Energy Asset Programs: Integrate technical and financial elements under a single contract agreement
10.2 Utility Service Agreement
10.3 Customer Benefits
10.4 Data Management and Analytics for Utilities
10.5 Big Data: How can Data be used for Decision Making?
10.6 Dispatchable Loads

Module (11) Characteristics of Wind and Solar Power Generation

11.1 Short Term variability of a Photovoltaic Plant
11.2 Commercial
11.3 Residential
11.4 Impact of Renewables on the Demand Side Management Programs
11.5 Adjustment Energy Cost

Module (12) Energy Storage

12.1 State of the art in energy storage
12.2 Fly Wheels
12.3 Type of Storage
12.4 Electrical Vehicles
12.5 Impact on Demand Side Management Programs

Module (13) Smart Meter Infrastructure

13.1 Smart Meters: its evolution
13.2 Smart Meters: the new generation
13.3 Metering Infrastructure Standards
13.4 Advanced Metering Infrastructure (AMI)

Module (14) Smart Meter Ecosystem

14.1 Utility data analytics industry ecosystem
14.2 Smart meters and advanced metering infrastructure (AMI) for energy storage
14.3 Advanced grid Controls and Sensors
14.4 Accessible energy data for end-use demand response
14.5 Innovative policies and adaptive social infrastructure (still in development)

Module (15) Interoperability

15.1 Controllers for Local Energy Networks
15.2 Residential Energy Management Systems
15.3 Financial Impacts of Smart Energy Technologies
15.4 The Transactive Energy Model

Module (16) Advanced Grid Applications

16.1 Components of Smart Enabling Demand Response, Storage and Distributed Energy Resources

Module (17) Architectural Platforms

17.1 Roadmap and Architecture
17.2 Centralized versus Un-centralized Architecture
17.3 Systems Interface Architecture
17.4 Plug-In Electric Vehicle Charging Infrastructure

Module (18) Internet of Things (of Everything) – IOT/IOE

18.1 The Next Generation of IOT
18.2 Move from Thermostat to Full Control
18.3 The Future of IOT/IOE

Module (19) Internet of Things World Forum Reference Model

19.1 Why it impacts the DSM Programs
19.2 Two Way Controls: Remote and at Home
19.3 The Power of Virtual Devices
19.4 SMART DEVICES
19.5 Smart Home of the Future : Telecom, Energy, Health
19.6 The Home as an Enterprise
19.7 Data Centric Architecture
19.8 More Big Data

Module (20) Semantic Technologies and the Internet of Services

20.1 Business Objects
20.2 Business Services in the Smart Grid

Boost certificate of completion

BOOST's Professional Attendance Certificate “BPAC” is always given to the delegates after completing the training course, and depends on their attendance of the program at a rate of no less than 80%, besides their active participation and engagement during the program sessions.

ENDORSED EDUCATION PROVIDER

Flexible deadlines

Customized dates accordance to your schedule

Shareable Certificate

Earn certificate upon completion

COURSE METHODOLOGY

Our Training programs are implemented by combining the participants' academic knowledge and practical practice (30% theoretical / 70% practical activities).

At The end of the training program, Participants are involved in practical workshop to show their skills in applying what they were trained for. A detailed report is submitted to each participant and the training department in the organization on the results of the participant's performance and the return on training. Our programs focus on exercises, case studies, and individual and group presentations.

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