A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach

Yu, Mengmeng; Hong, Seung Ho

doi:10.1109/tsg.2015.2413813

Cited by 217 publications

(155 citation statements)

References 22 publications

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“…In the proposed Stackelberg game G CM , a unique Stackelberg Equilibrium exists if the following conditions are satisfied [20].…”

Section: A Stackelberg Game Theory For the Chp-mgmentioning

confidence: 99%

“…We stress that recent work has shown Stackelberg games to be very effective and suitable for designing distributed energy management schemes in Smart Grid, especially for the electricity-trading process between the service provider and users [19,20]. For the hybrid multi-party MGs consist of CHP and PV prosumers, the relationship between MGO and PV prosumers is just a bi-directional trading process.…”

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confidence: 99%

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Energy Management for Joint Operation of CHP and PV Prosumers Inside a Grid-Connected Microgrid: A Game Theoretic Approach

Ма

Liu

Zhang

et al. 2016

IEEE Trans. Ind. Inf.

250

125

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This paper mainly focuses on the energy management of microgrids (MGs) consist of combined heat and power (CHP) and photovoltaic (PV) prosumers. A multi-party energy management framework is proposed for joint operation of CHP and PV prosumers with the internal price-based demand response. In particular, an optimization model based on Stackelberg game is designed where the microgrid operator (MGO) acts as the leader and PV prosumers are the followers. The properties of the game are studied and it is proved that the game possesses a unique Stackelberg equilibrium. The heuristic algorithm based on differential evolution is proposed that can be adopted by the MGO, and nonlinear constrained programming can be adopted by each prosumer to reach the Stackelberg equilibrium. Finally, via a practical example, the effectiveness of the model is verified in terms of determining MGO's prices and optimizing net load characteristic, etc.Index Terms-microgrid, combined heat and power, energy management, demand response, Stackelberg game. 1

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“…In the proposed Stackelberg game G CM , a unique Stackelberg Equilibrium exists if the following conditions are satisfied [20].…”

Section: A Stackelberg Game Theory For the Chp-mgmentioning

confidence: 99%

mentioning

confidence: 99%

Energy Management for Joint Operation of CHP and PV Prosumers Inside a Grid-Connected Microgrid: A Game Theoretic Approach

Ма

Liu

Zhang

et al. 2016

IEEE Trans. Ind. Inf.

250

125

View full text Add to dashboard Cite

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“…Finally, the learned results in the outline show that the assumption of the floods of the thyristor valve squares is sensible. This paper [12] proposed a steady esteem (Real-Time Pricing) based demand response (Demand Response) computation for achieving perfect load control of contraptions in an office by moulding a virtual power trading process, where the essentialness organization focal point of the workplace is the virtual retailer (pioneer) offering virtual retail costs, from which devices (lovers) should purchase imperativeness. A one-pioneer, N-fan Shackle berg preoccupation is definite to get the between exercises among them, and streamlining issues are surrounded for each player to help in picking the perfect system.…”

Section: IImentioning

confidence: 99%

A Survey on Smart Energy Monitoring System

Lavanya¹

2018

IJRASET

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The motivation to manage energy usage at residential home in India is influenced by economics environment condition and technical reasons. Economically, it offers reduction of government subsidies and electricity bill. The environment condition aspect enables reduction of CO 2 level. We can limit the power supply to the home by pre-default setting the value to be consumed, so that energy can be managed by limit. The power management system is consist of ZigBee Digital Power meters installed in every consumer unit and an Electricity e-Billing system at the energy provider side. The ZigBee Digital Power Meter (ZPM) is a single phase digital kWh power meter with embedded ZigBee modem which utilize the Wireless Sensor Network to send its power usage reading using information back to the energy provider wirelessly. At the power provider side, they have the control to change priority of the devices when power distributed in low range. Keywords : DSM (Demand Side Management), CTPT (Current Transformer Power Transformer), Potentiometer. I.INTRODUCTION The main objective of Energy Tracking System is to reduce the Energy Consumption at multifamily in a residential house. By using a smart meter and power line communication, so that we can provide the detailed information of energy consumption. The hardware components that we used in this. The potentiometer can operate the high voltage and low voltage. Raspberry pi can be connected with the virtual terminal, motor, lamp and voltage. If the power value gets above 20 is high voltage and it gets below 20 is low voltage. At finally, plug the GSM with the above raspberry pi. We can easily get the meter reading day by day and its shows the threshold unit how much we used in the whole day. This will reduce the consumption of energy. By using GSM technology, our daily usage of current units can be easily gets through message. Meter reading is taken automatically by using the GSM technology. The Meter reading is taken manually. The Errors are occurred due to less concentration. The Meter reading is not accurate. Delayed works are due to external conditions. The Power can be cut manually due to lack of payment. The Meter reading is taken automatically using the GSM technology. A Power cut is achieved from EB office through wireless. A Normal work happens at any time and external conditions. A High Accurate meter reading is done. The Power management can be capable.

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“…T f is not an input parameter and is randomly decided by algorithm using Equation (12). The value of T f is selected to be either 1 or 2 depending on rounding up criteria.…”

Section: Tlbomentioning

confidence: 99%

An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes

et al. 2017

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Smart grid is an emerging technology which is considered to be an ultimate solution to meet the increasing power demand challenges. Modern communication technologies have enabled the successful implementation of smart grid (SG), which aims at provision of demand side management mechanisms (DSM), such as demand response (DR). In this paper, we propose a hybrid technique named as teacher learning genetic optimization (TLGO) by combining genetic algorithm (GA) with teacher learning based optimization (TLBO) algorithm for residential load scheduling, assuming that electric prices are announced on a day-ahead basis. User discomfort is one of the key aspects which must be addressed along with cost minimization. The major focus of this work is to minimize consumer electricity bill at minimum user discomfort. Load scheduling is formulated as an optimization problem and an optimal schedule is achieved by solving the minimization problem. We also investigated the effect of power-flexible appliances on consumers' bill. Furthermore, a relationship among power consumption, cost and user discomfort is also demonstrated by feasible region. Simulation results validate that our proposed technique performs better in terms of cost reduction and user discomfort minimization, and is able to obtain the desired trade-off between consumer electricity bill and user discomfort.

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A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach

Cited by 217 publications

References 22 publications

Energy Management for Joint Operation of CHP and PV Prosumers Inside a Grid-Connected Microgrid: A Game Theoretic Approach

Energy Management for Joint Operation of CHP and PV Prosumers Inside a Grid-Connected Microgrid: A Game Theoretic Approach

A Survey on Smart Energy Monitoring System

An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes

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