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FEDRP Based Model Implementation of Intelligent Energy Management Scheme for a Residential Community in Smart Grids Network  [PDF]
Qamar Zia, Muhammad Ali, Zulfikar Ahmad Zaidi, Chaudhry Arshad, Amjad Ullah, Hafeez ur Rahman, Muhammad Ahsan Shahzad, Beenish Taj
Smart Grid and Renewable Energy (SGRE) , 2012, DOI: 10.4236/sgre.2012.34045
Abstract: In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy management has forced power supplying agencies to become globally competitive. Demand Response (DR) Programs in context with smart energy network have influenced prosumers and consumers towards it. In this paper Fair Emergency Demand Response Program (FEDRP) is integrated for managing the loads intelligently by using the platform of Smart Grids for Residential Setup. The paper also provides detailed modeling and analysis of respective demands of residential consumers in relation with economic load model for FEDRP. Due to increased customer’s partaking in this program the load on the utility is reduced and managed intelligently during emergency hours by providing fair and attractive incentives to residential clients, thus shifting peak load to off peak hours. The numerical and graphical results are matched for intelligent energy management scenario.
Demand Response Management For Power Throttling Air Conditioning Loads In Residential Smart Grids  [PDF]
Yawar Ismail Khalid,Naveed Ul Hassan,Chau Yuen,Shisheng Huang
Computer Science , 2014,
Abstract: In this paper we develop an algorithm for peak load reduction to reduce the impact of increased air conditioner usage in a residential smart grid community. We develop Demand Response Management (DRM) plans that clearly spell out the maximum duration as well as maximum severity of inconvenience. We model the air conditioner as a power throttling device and for any given DRM plan we study the impact of increasing the number of power states on the resulting peak load reduction. Through simulations, we find out that adding just one additional state to the basic ON/OFF model, which can throttle power to 50% of the rated air conditioner power, can result in significant amount of peak reduction. However, the peak load that can be reduced is diminishing with the increase in number of states. Furthermore, we also observe the impact of inconvenience duration and inconvenience severity in terms of peak load reduction. These observations can serve as useful guidelines for developing appropriate DRM plans.
Market-based Demand Response via Residential Plug-in Electric Vehicles in Smart Grids  [PDF]
Farshad Rassaei,Wee-Seng Soh,Kee-Chaing Chua
Mathematics , 2015,
Abstract: Flexibility in power demand, diverse usage patterns and storage capability of plug-in electric vehicles (PEVs) grow the elasticity of residential electricity demand remarkably. This elasticity can be utilized to form the daily aggregated demand profile and/or alter instantaneous demand of a system wherein a large number of residential PEVs share one electricity retailer or an aggregator. In this paper, we propose a demand response (DR) technique to manage vehicle-to-grid (V2G) enabled PEVs' electricity assignments (charging and discharging) in order to reduce the overall electricity procurement costs for a retailer bidding to a two-settlement electricity market, i.e., a day-ahead (DA) and a spot or real-time (RT) market. We show that our approach is decentralized, scalable, fast converging and does not violate users' privacy. Extensive simulations show significant overall cost savings can be achieved for a retailer bidding to an operational electricity market by using the proposed algorithm. This technique becomes more needful when the power grid accommodates a large number of intermittent energy resources wherein RT demand altering is crucial due to more likely contingencies and hence more RT price fluctuations and even occurring the so-called \textit{black swan events}. Finally, such retailer could offer better deals to customers as well.
Joint Shaping and Altering the Demand Profile by Residential Plug-in Electric Vehicles for Forward and Spot Markets in Smart Grids  [PDF]
Farshad Rassaei,Wee-Seng Soh,Kee-Chaing Chua
Mathematics , 2015,
Abstract: Plug-in electric vehicles (PEVs) can significantly increase the elasticity of residential electricity demand. This elasticity can be employed to shape the daily aggregated electricity demand profile of a system comprised of a large number of residential PEVs' users sharing one electricity retailer or an aggregator. In this paper, we propose a joint demand shaping and altering algorithm for managing vehicle-to-grid (V2G) enabled PEVs' electricity assignments (charging and discharging) in order to diminish the overall electricity procurement costs for a retailer bidding to two-settlement electricity markets, i.e., a day-ahead (DA) and a real-time (RT) market. This approach is decentralized, scalable, fast converging and does not violate users' privacy. Our simulations' results demonstrate significant overall cost savings (up to 28\%) for a retailer bidding to an operational electricity market by using our proposed algorithm. This becomes even more salient when the power system is integrating a large number of intermittent energy resources wherein RT demand altering is crucial due to more likely contingencies and hence more RT price fluctuations and even more so-called \textit{black swan events}. Lower electricity procurement cost for a retailer finally makes it able to offer better deals to customers and expand its market capacity. This implies that customers can enjoy lower electricity bills as well.
Demand and Response in Smart Grids for Modern Power System  [PDF]
Muhammad Qamar Raza, Muhammad Usman Haider, S. Muhammad Ali, Muhammad Zeeshan Rashid, Farooq Sharif
Smart Grid and Renewable Energy (SGRE) , 2013, DOI: 10.4236/sgre.2013.42016

Micro-grid plays a vital role in fulfilling the increasing demand by using distributed renewable energy resources. Demand and response technique can be broadly classified under the setup DR deployed (e.g. ISO’s/RTO’s). Demand response program can be implemented to improve power system quality, reliability and increasing demand. In modern power industry, strategic player can take more benefit from more emphasized DR study in terms of social benefit (uninterrupted power supply to consumers) and economy. This paper proposes the distributed micro-grid control and implemented control setup implemented demand response algorithm, which provides better power system reliability. This paper presents contingencies control demand and response for micro-grid. The main advantage of implementation of demand and response algorithms in Micro-grids provides reliable power supplies to consumers. The proposed micro-grid TCP/IP setup provides a chance to respond the contingencies to recover the shed to active condition. Micro-grid controller implements demand and response algorithm reasonable for managing the demand of the load and intelligent load scheme in case of blackout.

Distributed Demand Response and User Adaptation in Smart Grids  [PDF]
Zhong Fan
Computer Science , 2010,
Abstract: This paper proposes a distributed framework for demand response and user adaptation in smart grid networks. In particular, we borrow the concept of congestion pricing in Internet traffic control and show that pricing information is very useful to regulate user demand and hence balance network load. User preference is modeled as a willingness to pay parameter which can be seen as an indicator of differential quality of service. Both analysis and simulation results are presented to demonstrate the dynamics and convergence behavior of the algorithm.
Building Automation Networks for Smart Grids  [PDF]
Peizhong Yi,Abiodun Iwayemi,Chi Zhou
International Journal of Digital Multimedia Broadcasting , 2011, DOI: 10.1155/2011/926363
Abstract: Smart grid, as an intelligent power generation, distribution, and control system, needs various communication systems to meet its requirements. The ability to communicate seamlessly across multiple networks and domains is an open issue which is yet to be adequately addressed in smart grid architectures. In this paper, we present a framework for end-to-end interoperability in home and building area networks within smart grids. 6LoWPAN and the compact application protocol are utilized to facilitate the use of IPv6 and Zigbee application profiles such as Zigbee smart energy for network and application layer interoperability, respectively. A differential service medium access control scheme enables end-to-end connectivity between 802.15.4 and IP networks while providing quality of service guarantees for Zigbee traffic over Wi-Fi. We also address several issues including interference mitigation, load scheduling, and security and propose solutions to them. 1. Introduction The smart grid is an intelligent power generation, distribution, and control system. It enhances today’s power grid with intelligence, bidirectional communication capabilities and energy flows [1]. These enhancements address the efficiency, stability, and flexibility issues that plague the grid at present. In order to achieve its promised potential, the smart grid must facilitate services including the wide-scale integration of renewable energy sources, provision of real-time pricing information to consumers, demand response programs involving residential and commercial customers, and rapid outage detection. All these tasks demand the collection and analysis of real-time data. This data is then used to control electrical loads and perform demand response. In order to obtain the full benefit of smart grids, their communication infrastructure must support device control and data exchanges between various domains which comprise the smart grid. The smart grid must be allied with smart consumption in order to achieve optimum power system efficiency. This necessitates the integration of smart buildings, appliances, and consumers in order to reduce energy consumption while satisfying occupant comfort. Building automation systems (BASs) already provide this intelligence, enabling computerized measurement, control and management of heating, ventilation, air-conditioning (HVAC), lighting, and security systems to enhance energy efficiency, reduce costs, and improve user comfort. Buildings consume 29% of all electricity generated in the United States [2]; therefore, the ability of BASs to communicate
A Statistical Modelling and Analysis of Residential Electric Vehicles' Charging Demand in Smart Grids  [PDF]
Farshad Rassaei,Wee-Seng Soh,Kee-Chaing Chua
Computer Science , 2014,
Abstract: Electric vehicles (EVs) add significant load on the power grid as they become widespread. The characteristics of this extra load follow the patterns of people's driving behaviours. In particular, random parameters such as arrival time and charging time of the vehicles determine their expected charging demand profile from the power grid. In this paper, we first present a model for uncoordinated charging power demand of EVs based on a stochastic process and accordingly we characterize an EV's expected daily power demand profile. Next, we illustrate it for different charging time distributions through simulations. This gives us useful insights into the long-term planning for upgrading power systems' infrastructure to accommodate EVs. Then, we incorporate departure time as another random variable into this modelling and introduce an autonomous demand response (DR) technique to manage the EVs' charging demand. Our results show that, it is possible to accommodate a large number of EVs and achieve the same peak-to-average ratio (PAR) in daily aggregated power consumption of the grid as when there is no EV in the system. This peak value can be decreased further significantly when we add vehicle-to-grid (V2G) capability in the system.
Customer Engagement Plans for Peak Load Reduction in Residential Smart Grids  [PDF]
Naveed Ul Hassan,Yawar Ismail Khalid,Chau Yuen,Wayes Tushar
Computer Science , 2015,
Abstract: In this paper, we propose and study the effectiveness of customer engagement plans that clearly specify the amount of intervention in customer's load settings by the grid operator for peak load reduction. We suggest two different types of plans, including Constant Deviation Plans (CDPs) and Proportional Deviation Plans (PDPs). We define an adjustable reference temperature for both CDPs and PDPs to limit the output temperature of each thermostat load and to control the number of devices eligible to participate in Demand Response Program (DRP). We model thermostat loads as power throttling devices and design algorithms to evaluate the impact of power throttling states and plan parameters on peak load reduction. Based on the simulation results, we recommend PDPs to the customers of a residential community with variable thermostat set point preferences, while CDPs are suitable for customers with similar thermostat set point preferences. If thermostat loads have multiple power throttling states, customer engagement plans with less temperature deviations from thermostat set points are recommended. Contrary to classical ON/OFF control, higher temperature deviations are required to achieve similar amount of peak load reduction. Several other interesting tradeoffs and useful guidelines for designing mutually beneficial incentives for both the grid operator and customers can also be identified.
An Efficient Impedance Matching Technique for Improving Narrowband Power Line Communication in Residential Smart Grids
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering , 2013,
Abstract: Power line communication is a cost-effective, facile and reliable tool for the current electrical distribution grid and will play a significant role towards realizing smart grids in future. Low voltage electrical networks provide a harsh environment for data communication. Significant attenuation, noise, interferences, multipath reflections and overall unpredictable and time varying access impedance are some of the major problems faced by power line communication in its current state. The demand for smart greenhouses is rapidly increasing to meet the energy demand in future. So the need of an effective communication link between main grid and the residential grid is inevitable. This paper aims at removing one of the big hindrances in achieving power line communication, which is impedance mismatch between the communication system side and load side. Although there are many impedance matching techniques, a thorough comparison of all major techniques is required to find out which one is technically efficient and cost effective. It explains the performance variation in different system areas and therefore helps in providing better perceptive of power line communication in real applications.
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