Dynamic Pricing for Distributed Generation in Smart Grid

2013 ◽  
Author(s):  
Chong Huang ◽  
Saswati Sarkar
Keyword(s):  
Smart Grid ◽  
Distributed Generation ◽  
Dynamic Pricing

Distributed Generation Units as Ancillary Services Providers in a Pre Smart Grid Environment

2015 ◽  
Vol 9 (1) ◽  
pp. 432-444
Author(s):  
Clainer Bravin Donadel ◽  
Jussara Farias Fardin ◽  
Lucas Frizera Encarnação
Keyword(s):  
Smart Grid ◽  
Distributed Generation ◽  
Ancillary Services ◽  
Grid Environment

Optimal dynamic pricing for an electricity retailer in the price-responsive environment of smart grid

2021 ◽  
Vol 130 ◽  
pp. 107004
Author(s):  
Hossein Taherian ◽  
Mohammad Reza Aghaebrahimi ◽  
Luis Baringo ◽  
Saeid Reza Goldani
Keyword(s):  
Smart Grid ◽  
Dynamic Pricing ◽  
Optimal Dynamic

scholarly journals ToU Pricing-Based Dynamic Electricity Theft Detection in Smart Grid Using Gradient Boosting Classifier

2021 ◽  
Vol 11 (1) ◽  
pp. 401
Author(s):  
Rajiv Punmiya ◽  
Sangho Choe
Keyword(s):  
Smart Grid ◽  
Dynamic Pricing ◽  
Gradient Boosting ◽  
Core Concept ◽  
Actual Usage ◽  
Electricity Theft ◽  
Extreme Gradient Boosting ◽  
New Type ◽  
Near Future ◽  
Very High

In the near future, it is highly expected that smart grid (SG) utilities will replace existing fixed pricing with dynamic pricing, such as time-of-use real-time tariff (ToU). In ToU, the price of electricity varies throughout the whole day based on the respective utilities’ decisions. We classify the whole day into two periods with very high and low probabilities of theft activities, termed as the “theft window” and “non-theft window”, respectively. A “smart” malicious consumer can adjust his/her theft to mostly targeting the theft window, manipulate actual usage reporting to outsmart existing theft detectors, and achieve the goal of “paying reduced tariff”. Simulation results show that existing schemes do not detect well such window-based theft activities conversely exploiting ToU strategies. In this paper, we begin by introducing the core concept of window-based theft cases, which is defined at the basis of ToU pricing as well as consumption usage. A modified extreme gradient boosting (XGBoost) based machine learning (ML) technique called dynamic electricity theft detector (DETD) has been presented to detect a new type of theft cases.

An Autonomous Residential Smart Distribution Board: A Panacea for Demand Side Energy Management for Non-Smart Grid Networks

2018 ◽  
Vol 19 (3) ◽  
Author(s):  
Oladayo O. Olakanmi ◽  
Oluyemi Adetoyi ◽  
Oluwafemi Fajemisin
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Demand Response ◽  
Dynamic Pricing ◽  
Performance Comparison ◽  
Usage Pattern ◽  
Energy Usage ◽  
Grid Networks ◽  
A Priority ◽  
Priority Model

Abstract Despite the benefits of demand response in energy management, the non-existence of its key concepts; dynamic pricing and smart grid, in some countries makes its impracticable in these countries, therefore making energy management unattainable for their consumers. This paper proposed a Smart Distribution Board (SDB) using a priority model for energy management in non-smart grid network. An historical consumption signatures of user’s loads were used to develop a priority model for load units of the SDB. Performance comparison was carried out between the SDB and a conventional Distribution Board which has no level of intelligence. Results obtained indicated that the SDB correctly emulated the energy usage pattern of users, thereby ensuring load preference is maximally satisfied autonomously within a limited budgeted energy and period.

Smart Grid and Distributed Generation: A Panacea for Nigeria’s Power Problems

2019 ◽  
Author(s):  
Obianuju V. Chukwuorji ◽  
Bemdoo Saka ◽  
Ismail D. Inuwa ◽  
Suleiman U. Hussein ◽  
Sadiq Thomas ◽  
...  
Keyword(s):  
Smart Grid ◽  
Distributed Generation

Load forecasting, dynamic pricing and DSM in smart grid: A review

2016 ◽  
Vol 54 ◽  
pp. 1311-1322 ◽  
Author(s):  
Ahsan Raza Khan ◽  
Anzar Mahmood ◽  
Awais Safdar ◽  
Zafar A. Khan ◽  
Naveed Ahmed Khan
Keyword(s):  
Smart Grid ◽  
Dynamic Pricing ◽  
Load Forecasting

Incremental Welfare Consensus Algorithm for Cooperative Distributed Generation/Demand Response in Smart Grid

2014 ◽  
Vol 5 (6) ◽  
pp. 2836-2845 ◽  
Author(s):  
Navid Rahbari-Asr ◽  
Unnati Ojha ◽  
Ziang Zhang ◽  
Mo-Yuen Chow
Keyword(s):  
Smart Grid ◽  
Distributed Generation ◽  
Demand Response ◽  
Consensus Algorithm

scholarly journals Grid-Tied Distributed Generation Systems to Sustain the Smart Grid Transformation: Tariff Analysis and Generation Sharing

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1187 ◽  
Author(s):  
Fernando Yanine ◽  
Antonio Sánchez-Squella ◽  
Aldo Barrueto ◽  
Antonio Parejo ◽  
Felisa Cordova ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Energy Storage ◽  
Smart Grid ◽  
Power Control ◽  
Energy Management ◽  
Distributed Generation ◽  
Electric Utility ◽  
Green Energy ◽  
Supply Capacity

In this paper a novel model is being proposed and considered by ENEL—the largest electric utility in Chile—and analyzed thoroughly, whereby electric power control and energy management for a 60-apartments’ residential building is presented as an example of the utility’s green energy program, part of its Smart Grid Transformation plan to install grid-tied distributed generation (DG) systems, namely microgrids, with solar generation and energy storage in Santiago, Chile. The particular tariffs scheme analysis shown is part of the overall projected tentative benefits of adopting the new scheme, which will require the utility’s customers to adapt their consumption behavior to the limited supply of renewable energy by changing energy consumption habits and schedules in a way that maximizes the capacity and efficiency of the grid-tied microgrid with energy storage. The change in behavior entails rescheduling power consumption to hours where the energy supply capacity in the DG system is higher and price is lower as well as curtailing their power needs in certain hourly blocks so as to maximize DG system’s efficiency and supply capacity. Nevertheless, the latter presents a problem under the perspective of ENEL’s renewable energy sources (RES) integration plan with the electric utility’s grid supply, which, up until now and due to current electric tariffs law, has not had a clear solution. Under said scenario, a set of strategies based on energy homeostasis principles for the coordination and control of the electricity supply versus customers’ demand has been devised and tested. These strategies which consider various scenarios to conform to grid flexibility requirements by ENEL, have been adapted for the specific needs of these types of customers while considering the particular infrastructure of the network. Thus, the microgrid adjusts itself to the grid in order to complement the grid supply while seeking to maximize green supply capacity and operational efficiency, wherein the different energy users and their energy consumption profiles play a crucial role as “active loads”, being able to respond and adapt to the needs of the grid-connected microgrid while enjoying economic benefits. Simulation results are presented under different tariff options, system’s capacity and energy storage alternatives, in order to compare the proposed strategies with the actual case of traditional grid’s electricity distribution service, where no green energy is present. The results show the advantage of the proposed tariffs scheme, along with power control and energy management strategies for the integration of distributed power generation within ENEL’s Smart Grid Transformation in Chile.

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