scholarly journals Integrating renewable energy contracts and wholesale dynamic pricing to serve aggregate flexible loads

Author(s):  
Anthony Papavasiliou ◽  
Shmuel S. Oren
2015 ◽  
Vol 6 (4) ◽  
pp. 1884-1892 ◽  
Author(s):  
Donatello Materassi ◽  
Saverio Bolognani ◽  
Mardavij Roozbehani ◽  
Munther A. Dahleh

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 16876-16892 ◽  
Author(s):  
Muhammad Babar Rasheed ◽  
Muhammad Awais Qureshi ◽  
Nadeem Javaid ◽  
Thamer Alquthami

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4839
Author(s):  
Diego B. Vilar ◽  
Carolina M. Affonso

This paper proposes a novel dynamic pricing scheme for demand response with individualized tariffs by consumption profile, aiming to benefit both customers and utility. The proposed method is based on the genetic algorithm, and a novel operator called mutagenic agent is proposed to improve algorithm performance. The demand response model is set by using price elasticity theory, and simulations are conducted based on elasticity, demand, and photovoltaic generation data from Brazil. Results are evaluated considering the integration effects of renewable energy sources and compared with other two pricing strategies currently adopted by Brazilian utilities: flat tariff and time-of-use tariff. Simulation results show the proposed dynamic tariff brings benefits to both utilities and consumers. It reduces the peak load and average cost of electricity and increases utility profit and load factor without the undesirable rebound effect.


Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4376 ◽  
Author(s):  
Taimoor Ahmad Khan ◽  
Kalim Ullah ◽  
Ghulam Hafeez ◽  
Imran Khan ◽  
Azfar Khalid ◽  
...  

Electricity demand is rising due to industrialisation, population growth and economic development. To meet this rising electricity demand, towns are renovated by smart cities, where the internet of things enabled devices, communication technologies, dynamic pricing servers and renewable energy sources are integrated. Internet of things (IoT) refers to scenarios where network connectivity and computing capability is extended to objects, sensors and other items not normally considered computers. IoT allows these devices to generate, exchange and consume data without or with minimum human intervention. This integrated environment of smart cities maintains a balance between demand and supply. In this work, we proposed a closed-loop super twisting sliding mode controller (STSMC) to handle the uncertain and fluctuating load to maintain the balance between demand and supply persistently. Demand-side load management (DSLM) consists of agents-based demand response (DR) programs that are designed to control, change and shift the load usage pattern according to the price of the energy of a smart grid community. In smart grids, evolved DR programs are implemented which facilitate controlling of consumer demand by effective regulation services. The DSLM under price-based DR programs perform load shifting, peak clipping and valley filling to maintain the balance between demand and supply. We demonstrate a theoretical control approach for persistent demand control by dynamic price-based closed-loop STSMC. A renewable energy integrated microgrid scenario is discussed numerically to show that the demand of consumers can be controlled through STSMC, which regulates the electricity price to the DSLM agents of the smart grid community. The overall demand elasticity of the current study is represented by a first-order dynamic price generation model having a piece-wise linear price-based DR program. The simulation environment for this whole scenario is developed in MATLAB/Simulink. The simulations validate that the closed-loop price-based elastic demand control technique can trace down the generation of a renewable energy integrated microgrid.


Author(s):  
Italo Brito ◽  
Claudio De Farias ◽  
Luci Pirmez ◽  
Leonardo Ribeiro ◽  
Luiz Carmo

Sign in / Sign up

Export Citation Format

Share Document