Conference Paper

Real-Time Pricing with Demand Response Model for Autonomous Homes

Conference Paper

Real-Time Pricing with Demand Response Model for Autonomous Homes

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Abstract

Smart Grid (SG) is a next-generation electrical power system that use two way communication in the generation, consumption and delivery of the electrical energy. One of the key feature of SG is Demand Response (DR). In DR a pricing signal is provided to the customer via smart meters, and customer modifies their demand in response to price signals. However, most of the load scheduling schemes used day-ahead or Time of Use pricing scheme, these schemes are deviating from Real-time Pricing (RTP) scheme. In this paper, an RTP based scheduling scheme is proposed using Optimal Stopping Rule (OSR). An OSR gives the best operating time of the device to reduce electricity bills. The cost minimization problem is formulated as an unconstrained optimization problem. Moreover, waiting time cost is also formulated as sub problem to reduce waiting time of the device. Waiting time is considered as a function of cost. After that, an algorithm is proposed to solve this optimization problem for various types of loads. Simulation results verify that proposed algorithm has low computational complexity and reduce electricity bill with less waiting time.

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... From the utilities' point of view, load shifting can protect the grid systems from the likelihood of outages, elevate the power generators' utilization, and enhance the grid's reliability [15]. Peak shaving, valley filling, etc. are the other types of DSM techniques that work by decreasing the peak demand and improving the grid's secured operation [16]. ...
... An optimization model for long-term decision-making modeled with the impact of short-term variability of demand and RES [16] To minimize the electricity purchase cost Binary integer programming ...
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... The RTP [77][78][79] tends to be more complex than the TOU because the RTP changes the tariff in a period of minutes. The CPP [80][81][82] allows the distribution grid operator to occasionally increase the tariff for a limited number of hours given the consumption peak. ...
Thesis
This thesis focus on the research of the DC microgrid following two operation models: grid-connected mode, and off-grid mode including the islanded and isolated modes. The aim of this thesis is to propose a DC microgrid combining the advantages of the grid-connected or the off-grid mode, which named full DC microgrid. ln the full DC microgrid, the renewable energy sources, storage, and public grid are included, and the back-up sources also applied to reduce the load shedding. ln the full DC microgrid, a supervisory system is proposed to manage the power. The real-time power management in the operational layer of the supervisory system can keep the power balance. ln the optimization layer of the supervisory system, the day-ahead optimization is proposed to achieve the global minimal operation cost. The simulation results show that the full DC microgrid combines both advantages of the grid-connected and the off-grid mode to minimize the operating cost. Then, the supervisory system considers the dynamic efficiency of the converter to solve the problem that the power quality of the microgrid is degraded due to the unstable DC bus voltage caused by the inaccurate power control. The simulation results show that considering the dynamic efficiency of the converter in the operational layer of the supervisory system, the fluctuation of the DC bus voltage can be reduced. Regarding the importance of the PV prediction for the day-ahead optimization, two prediction modes are studied and compared to give a robust PV prediction power. The results are that the two models almost have the same results.
... Most existing research on dynamic pricing based demand response optimization assume that customers are installed with smart meters and home energy management systems (HEMS), i.e. there is an optimization software which is able to help customers schedule their home appliances usages explicitly to maximize customers' utility such as minimizing their payment bills [13][14][15][16]. ...
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