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Smart Grids and Energy Management Systems (SGEMS)

SGEMS

1.      SMART GRIDS

1.1      Introduction

The European Union Commission Task Force for Smart Grids provides the following definition for smart:

"A Smart Grid is an electricity network that can cost-efficiently integrate the behaviour and actions of all users connected to it – generators, consumers and those that do both – in order to ensure economically efficient, the sustainable power system with low losses and high levels of quality and security of supply and safety. A smart grid employs innovative products and services together with intelligent monitoring, control, communication, and self-healing technologies in order to:

  1. Better facilitate the connection and operation of generators of all sizes and technologies.
  2. Allow consumers to play a part in optimising the operation of the system.
  3. Provide consumers with greater information and options for how they use their supply.
  4. Significantly reduce the environmental impact of the whole electricity supply system.
  5. Maintain or even improve the existing high levels of system reliability, quality and security of supply.
  6. Maintain and improve existing services efficiently."

Other characteristics of the smart grid as stated in the  Energy Independence and Security Act of 2007 (EISA-2007)of the USA [2] include:

 

  1.  Increased use of digital information and controls technology to improve reliability, security, and efficiency of the electric grid. 
  2. Dynamic optimization of grid operations and resources, with full cyber-security. 
  3. Deployment and integration of distributed resources and generation, including renewable resources. 
  4. Development and incorporation of demand response, demand-side resources, and energy-efficiency resources. 
  5. Deployment of 'smart' technologies (real-time, automated, interactive technologies that optimize the physical operation of appliances and consumer devices) for metering, communications concerning grid operations and status, and distribution automation.
  6. Integration of 'smart' appliances and consumer devices.
  7. Deployment and integration of advanced electricity storage and peak-shaving technologies, including plug-in electric and hybrid electric vehicles, and thermal storage air conditioning. 
  8. Provision to consumers of timely information and control options. 
  9. Development of standards for communication and interoperability of appliances and equipment connected to the electric grid, including the infrastructure serving the grid. 
  10.  Identification and lowering of unreasonable or unnecessary barriers to the adoption of smart grid technologies, practices, and services."

 

1.2       Key Components of Smart Grid

Some of the key components of a smart grid system are listed and briefly discuss below

Integrated Communication

A reliable, high-speed integrated communication platform is considered to be a basic component in the implementation of a smarter transmission system. It connects components to an open architecture for real-time information, control and data exchange to optimise the reliability of the system, utilisation of assets and security.

 

Sensing and Measurements

Advanced sensing and measurement technologies will collect data and alter them to better manage power systems. These technologies are used for the evaluation and monitoring of equipment health, the prevention of energy theft and for control strategies support. They are also used to eliminate billing estimations, assess grid stability and obstruction and support frequent meter readings. They will also help consumers to enhance their electrical usage by providing them with information concerning their daily demands.

 

Advanced Metering Infrastructure (AMI)

It is comprised of systems that measure, gather and evaluate the amount of energy used and communicate with metering devices. These systems consist of hardware, software, communications, Meter Data Management software, consumer energy displays and controls and many others.

 

Advanced Control

In order to have a safe, reliable and environmentally friendly modern grid system, development in advanced control method is a must. These technologies are devices and algorithms that enable rapid diagnosis and analysis of the modern grid system. Whenever necessary, it takes appropriate corrective measures to diminish power outages or even prevent outages from happening. There will be better control at the transmission, distribution and consumer levels when using these methods.

 

Improved interfaces and decision support

Improved interfaces and decision support are important technologies that consist of devices and training that will amplify human-decision making and transforming grid operators and managers into knowledgeable workers to operate the modern grid.

 

These technologies will reduce complexity by converting data from power systems into information that can be easily understood by humans. After the convention, data can be in terms of animation, virtual reality and other data-display techniques that will help the operator to quickly identify, analyse and act on emerging problems. Therefore, time to take a decision regarding certain issues is considerably reduced.

 

1.3       Possible Research Topics in Smart Grid Systems

  1. Communication integration in smart grid with distributed generation
  2. Security and privacy for the integration of smart grid with cloud computing
  3. Modelling and Stability Analysis of smart grid
  4. Smart Grid Computing
  5. Energy trading with dynamic Pricing
  6. Smart Grid Controls technologies
  7. Transactive Energy Modeling and Simulation Challenge for the Smart Grid


[1]  "Smart Grid definition by EU Commission"

[2] Energy Independence and Security Act of 2007 (EISA-2007)

 

2.      Energy Management

2.1      Introduction

Energy Management System (EMS) widely refers to a computer system which is designed specifically for the automated control, monitoring and optimization of electric power and utility systems. They help reduce energy consumption, improve the utilization of systems, increase reliability, and predict electrical system performance as well as optimize energy usage to reduce cost. The scope may span from a load dispatch centre to a group of power networks. Most energy management systems also provide decision making facilities for real-time operation and control. The data obtained from such actions are used to train operators in a control centre and for performing engineering studies for futuristic actions like planning, optimization and maintenance schedules, etc. on a frequent basis and to produce trend analysis and annual consumption forecasts.

EMS applications use real-time data such as frequency, actual generation, tie-line load flows, and plant units’ controller status to provide system changes. EMS had its origin in the need for electric utility companies to operate their generators as economical as possible. To operate power systems as economical as possible, the characteristics of all generating units need to be available in one location so that the most efficient units could be dispatched properly along with the less efficient ones. Energy management systems can also provide metering and monitoring functions that allow facility and building managers to gather data and insight that allows them to make more informed decisions about energy activities across their sites.

 

2.2      Research areas in Energy Management Systems include:

  1. Contingency ranking
  2. Constraint and congestion management
  3. Security analysis
  4. Economic dispatch with emission control
  5. Demand-side management
  6. Real-time optimal operation of distribution networks
  7. Wide area monitoring and control systems
  8. Application of optimization techniques to power systems
  9. Voltage stability assessment and control
  10. Power system state estimation
  11. Development of high capacity transmission technologies for congested urban areas.
  12. Development of technologies for cost-effective operation and management of power systems.
  13. Solutions to technical challenges in renewable energy integration
  14. Solar forecasting
  15.  Integrating energy storage with renewable energy systems