scholarly journals A Study on the Real-Time Pricing Change and Fuel Mix Change Considering the Customer's Choice on the Smart Grid System

Author(s):  
Seong-Wan Park ◽  
Bal-Ho H. Kim
2021 ◽  
Vol 18 (2(Suppl.)) ◽  
pp. 0907
Author(s):  
Nurhazwani Anang ◽  
Mohammad Safwan AB Hamid ◽  
Wan Mariam Wan Muda

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of the actual smart grid system is high in cost. Thus, simulation and modelling of the system is important to see the capability of the actual system before being employed. Since the smart grid and its components are usually modeled using MATLAB/Simulink, the communication between MATLAB/Simulink, IoT platform such as ThingSpeak and mobile application is crucial to be explored to gain a better understanding of the features of the smart grid. To achieve the objectives, there are five main steps which are simulation of grid-connected photovoltaic (PV) system to generate data to be monitored and controlled using HOMER software, then, development of monitoring on ThingSpeak and mobile application using MIT App Inventor 2.  Next, the control system is developed on mobile application and the communication on how data are transferred between all the softwares are set up. The results show that all the seletected parameters can be monitored in real-time successfully. The developed mobile application can be used to control the MATLAB/Simulink in two modes. During automatic mode, ThingSpeak controls the MATLAB/Simulink by giving a zero signal (OFF) if load demand is less than the power generated by PV and a one signal (ON) if the load demand is greater than PV power. During manual mode, consumer can send ON or OFF signal to MATLAB/Simulink via the mobile application unconditionally. It is hoped that the proposed system will bring many benefits in modeling a complete smart grid system in MATLAB/Simulink.


2019 ◽  
Vol 2019 ◽  
pp. 1-18
Author(s):  
Hongjie Wang ◽  
Yan Gao

The real-time pricing mechanism of smart grid based on demand response is an effective means to adjust the balance between energy supply and demand, whose implementation will impact the user's electricity consumption behaviour, the operation, and management in the future power systems. In this paper, we propose a complementarity algorithm to solve the real-time pricing of smart grid. The Karush–Kuhn–Tucker condition is considered in the social welfare maximisation model incorporating load uncertainty to transforming the model into a system of nonsmooth equations with Lagrangian multipliers, i.e., the shadow prices. The shadow price is used to determine the basic price of electricity. The system of nonsmooth equations is a complementarity problem, which enables us to study the existence and uniqueness of the equilibrium price and to design an online distributed algorithm to achieve the equilibrium between energy supply and demand. The proposed method is implemented in a simulation system composed of an energy provider and 100 users. Simulations results show that the proposed algorithm can motivate the users’ enthusiasm to participate in the demand side management and shift the peak loading. Furthermore, the proposed algorithm can improve the supply shortage. When compared with an online distributed algorithm based on the dual optimisation method, the proposed algorithm has a significantly lower running time and more accurate Lagrangian multipliers.


Author(s):  
Stavros Lazarou ◽  
Rossano Musca ◽  
Mehmet Demitras ◽  
Gianluca Fulli ◽  
Ilhami Colak

Author(s):  
Ulrike Fischer ◽  
Dalia Kaulakienė ◽  
Mohamed E. Khalefa ◽  
Wolfgang Lehner ◽  
Torben Bach Pedersen ◽  
...  

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