scholarly journals Machine Learning Based Energy Management Model for Smart Grid and Renewable Energy Districts

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 185059-185078
Author(s):  
Waqar Ahmed ◽  
Hammad Ansari ◽  
Bilal Khan ◽  
Zahid Ullah ◽  
Sahibzada Muhammad Ali ◽  
...  
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Smart Grid ◽  
Energy Management ◽  
Management Model

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.

Application of Optimization to Sizing Renewable Energy Systems and Energy Management in Microgrids

2022 ◽  
pp. 60-94
Author(s):  
Khaled Dassa ◽  
Abdelmadjid Recioui
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Control Systems ◽  
Energy Management ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Optimization Techniques ◽  
Energy Sources ◽  
Huge Investment

The smart grid is the aggregation of emerging technologies in both hardware and software along with practices to make the existing power grid more reliable and ultimately more beneficial to consumers. The smart grid concept is associated with the production of electricity from renewable energy sources (RES). For the distant isolated regions, microgrids (MG) with RES are offering a suitable solution for remote and isolated region electrification. The improper sizing would lead to huge investment cost which could have been avoided. The objective of this chapter is to review the state-of-the-art studies on the use of optimization techniques to renewable energy design and sizing. The chapter reviews the optimization techniques employed at different components of the microgrid including the energy sources, storage elements, and converters/inverters with their control systems.

scholarly journals Energy Management Optimization Techniques for Hybrid Renewable Energy Systems

2020 ◽  
Vol 8 (6S) ◽  
pp. 89-94
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Energy System ◽  
Optimization Techniques ◽  
Energy Sources ◽  
Hybrid Energy ◽  
Management Optimization

A Smart Grid is a reviving structure of traditional centralized power sector which incorporates smart software and hardware technologies. It provides communication among the prosumers and consumers to achieve sustainability and reliability in an economical way. A microgrid (MG) is a unit of smart grid which consists of distributed energy sources with renewable energy sources, energy storage units and variable loads. Because of stochastic nature of renewable energy sources to maintain balance between supply and demand a novel hybrid energy management controller need to be devised. This paper presents various operational objectives and constraints associated with energy management system of hybrid energy system. Also it compares and discusses various optimization algorithms in the literature.

Coordinated power management and control of renewable energy sources based smart grid

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Siva Ganesh Malla ◽  
Jagan Mohana Rao Malla ◽  
Priyanka Malla ◽  
Sreekanth Ramasamy ◽  
Satish Kumar Doniparthi ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Energy Management ◽  
Management System ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Maximum Power ◽  
Energy Management System ◽  
Partial Shading ◽  
Battery Energy

Abstract Renewable energy-based smart grids are famous nowadays due to their high intellectual properties. The world is starting new inventions in renewable energy-based electrical power generation systems to reduce global warming. However, a single renewable energy source cannot maintain a proper energy management system and reliability of power towards loads. Hence, integrating two or more systems is very important and can form a smart grid with an appropriate energy management system. Effective energy management system for a 4-wire 1-MW smart grid system is proposed in this paper. The system is composed of three solar plants and three wind farms with a battery bank. The battery energy management system can operate the complete system as a smart grid with the proper design of the controllers. The maximum power points of PV plants are tracked using a hybrid algorithm that merges the merits of Modified Invasive Weed Optimization and Perturb and Observe (P&O). Thus, the maximum power is obtained under partial shading conditions. The P&O algorithm is also developed to track the maximum power of wind farms. All the loads and generation units are connected in a ring-configuration distribution with a centralized battery energy management system. The loads are selected to be unbalanced, nonlinear and reactive to simulate practical cases. TS-Fuzzy based common inverter controller is implemented to maintain acceptable power quality, which is linked to the battery. The proposed inverter controller can work as a reactive power compensator, active power filter, voltage regulator under unbalanced load, and power balancing device between generation and load. Extensive Hardware-in-Loop (HIL) results are presented to validate the effectiveness of the proposed system.

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