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(IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 3, Sep. 2012) Demand Side Management in Smart Grid Using Heuristic Optimization Thillainathan Logenthiran, Student Member, IEEE, Dipti Srinivasan, Senior Member, IEEE, and Tan Zong Shun

(IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 3, Sep. 2012)

Demand Side Management in Smart Grid Using Heuristic Optimization

Thillainathan Logenthiran, Student Member, IEEE, Dipti Srinivasan, Senior Member, IEEE, and Tan Zong Shun

Prepared By:M. Asghar KhanElectrical Engineering Dept.COMSATS Institute of IT Islamabad,Pakistan.11OUTLINEBACKGROUND

CONTRIBUTION

PROPOSED DSM STRAGTEGY

DETAILS OF THE TEST SMART GRID

SIMULATION RESULTS AND DISCUSSION

CONCLUSION

2BACKGROUND (1/6)Smart Grid: A modernizedelectrical gridUses information and communications technologyto gather and act on information, in an automated fashion To improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity

DSM (Demand Side Management): DSM is one of the important functions in a smart grid, that allows users to: 1. To make informed decisions regarding their energy consumption 2. Helps the energy providers to reduce the peak load demand and 3. Reshape the load profile 33BACKGROUND (2/6)DSM TECHNIQUES: DSM alters customers electricity consumption patterns to produce the desired changes in the load shapes of power distribution systemsMost of the techniques were developed using dynamic programming [13] and linear programming [5], [10]These programming techniques cannot handle a large number of controllable devices which have several computation patterns and heuristicsThe primary objective of the DSM techniques presented is, reduction of system peak load demand and operational cost4[5] K.-H. Ng and G. B. Shebl, Direct load control-A profit-based load management using linear programming, IEEE Trans. Power Syst., vol. 13, no. 2, pp. 688694, May 1998.[10] C. N. Kurucz, D. Brandt, and S. Sim, A linear programming model for reducing system peak through customer load control programs, IEEE Trans. Power Syst., vol. 11, no. 4, pp. 18171824, Nov. 1996.[13] Y. Y. Hsu and C. C. Su, Dispatch of direct load control using dynamic programming, IEEE Trans. Power Syst., vol. 6, no. 3, pp. 10561061, Aug. 1991.4BACKGROUND (3/6)DSM TECHNIQUES: The load shapes which indicate the daily or seasonal electricity demands of industrial, commercial or residential consumers between peak and off peak times can be altered by means of six broad methods [18][20]:

Peak ClippingValley FillingLoad ShiftingStrategic ConservationStrategic Load Growth, andFlexible Load Shape

5[18] I. K. Maharjan, Demand Side Management: Load Management, Load Profiling, Load Shifting, Residential and Industrial Consumer, Energy Audit, Reliability, Urban, Semi-Urban and Rural Setting. Saarbrcken, Germany: LAP (Lambert Acad. Publ.), 2010.[19] D. P. Kothari, Modern Power System Analysis. New Delhi, India: Tata McGraw-Hill, 2003.[20] C. W. Gellings, Demand-Side Management: Concepts and Methods. Liburn, GA: Fairmont, 1988.5BACKGROUND (4/6)DSM TECHNIQUES: Peak Clipping: A direct load control technique to make reduction of the peak loadsValley Filling: Valley filling constructs the off-peak demand by applying direct load controlPeak clipping and valley filling focus on reducing the difference between the peak and valley load levels to mitigate the peak demand, and increase the security of smart grid

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6BACKGROUND (5/6)DSM TECHNIQUES: Load Shifting: Most effective load management technique in current distribution networks Load shifting takes advantage of time independence of loads, and shifts loads from peak time to off-peak timeStrategic Conservation: It aims to achieve load shape optimization through application of demand reduction methods directly at customer premises

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7BACKGROUND (6/6)DSM TECHNIQUES: V. Strategic load growth: Optimizes the daily response in case of large demand introduction beyond the valley filling techniqueIt is based on increasing the market share of loads supported by energy conversion and storage systems or distributed energy resourcesIt is a planning and operations issue to balance the increasing demand with processes for constructing necessary infrastructure that accompanies load growthFlexible load shape: It is mainly related to reliability of smart gridSmart grid management systems identify customers with flexible loads in exchange for various incentive

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CONTRIBUTION (1/2)

This paper presents a DSM strategy based on load shifting technique for future smart grids with a large number of devices of several types

The day-ahead load shifting technique proposed in this paper is mathematically formulated as a minimization problem

A heuristic-based Evolutionary Algorithm (EA) that easily adapts heuristics in the problem was developed for solving this minimization problem this level settings

The operation of smart grid requires a two way communication between central controller and various system elements

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CONTRIBUTION (2/2)

The designed DSM system should therefore be able to handle the communication infrastructure between the central controller and controllable loads

The criteria could be maximizing the use of renewable energy resources, maximizing the economic benefit, minimizing the amount of power imported from the main grid, or reducing peak load demand

Simulations were carried out on a smart grid which contains a variety of loads in three service areas,one with residential customers another with commercial customers and the third one with industrial customers

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PROPOSED DSM STRAGTEGY

Smart grid manager designs an objective load curve according to the objective of the demand side managementThe proposed optimization algorithm aims to bring the final load curve as close to the objective load curve as possibleSuch that the desired objective of the DSM strategy is achievedFor example, if the objective of the DSM is to reduce the utility bill An objective load curve will be chosen such that it is inversely proportional to electricity market prices

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PROPOSED DSM STRAGTEGY

Figure shows the proposed architecture for the day-ahead DSM strategyExchange of information between DSM controller and each appliance is also shown in the figureThe DSM system receives the objective load curve as an input andCalculates the required load control actions in order to fulfill the desired load consumption

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PROPOSED DSM STRAGTEGY

The DSM is carried out at the beginning of a predefined control period which is typically a dayThen, the control actions are executed in real-time based on the resultsWhen a customer presses ON button of an appliance, the connection request is sent to the DSM controllerThe DSM controller replies based on the results of DSM technique that was carried out in advanceThe reply is either the connection permitted or a new connection time.

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PROPOSED DSM STRAGTEGY

A. PROBLEM FORMULATION: The proposed DSM strategy schedules the connection moments of each shiftable device in the system in a way that brings the load consumption curve as close as to the objective load consumption curveProposed load shifting technique is mathematically formulated as Minimize

Where is the value of the objective curve at time and is the actual consumption at time 14

PROPOSED DSM STRAGTEGY

A. PROBLEM FORMULATION: The is given by the following equation: (2)Where is the forecasted consumption at time t, and and are the amount of loads connected and disconnected at time respectively during the load shiftingCc is made up of two parts:the increment in the load at time t due to the connection times of devices shifted to time t and the increment in the load at time t due to the device connections scheduled for times that precede t

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PROPOSED DSM STRAGTEGY

PROBLEM FORMULATION: The is given by the following equation:

Where is the number of devices of type k that are shifted from time step i to t, D is the number of device types, and are the power consumptions at time steps 1 and respectively for device type k, and j is the total duration of consumption for device of type k

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PROPOSED DSM STRAGTEGY

PROBLEM FORMULATION: The is shown in the figure given belowWhere Load A is shifted from tA to (t-1), and Load B is shifted from tB to t

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PROPOSED DSM STRAGTEGY

PROBLEM FORMULATION:

Similarly, also consists of two parts:

the decrement in the load due to delay in connection times of devices that were originally supposed to begin their consumption at time step t and

the decrement in the load due to delay in connection times of devices that were expected to start their consumption at time steps that precede t

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PROPOSED DSM STRAGTEGY

PROBLEM FORMULATION: The is given by the following equation:

Where is the number of devices of type k that are delayed from time step t to q, m is the maximum allowable delay19

PROPOSED DSM STRAGTEGY

PROBLEM FORMULATION: The is shown in the figure given belowWhere Load A is shifted from (t-1) to tA, and Load B is shifted from t