Microgrid energy management strategies assessment through coupled thermal-electric considerations

2021 ◽  
Vol 228 ◽  
pp. 113711
Author(s):  
Spyridon Chapaloglou ◽  
Athanasios Nesiadis ◽  
Konstantinos Atsonios ◽  
Nikos Nikolopoulos ◽  
Panagiotis Grammelis ◽  
...  
Keyword(s):  
Energy Management ◽  
Management Strategies ◽  
Microgrid Energy Management

scholarly journals A Review on Thermal Energy Modelling for Optimal Microgrids Management

Thermo ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 63-76
Author(s):  
Mengxuan Yan ◽  
Dongxiao Wang ◽  
Chun Sing Lai ◽  
Loi Lei Lai
Keyword(s):  
Energy Management ◽  
Thermal Energy ◽  
Critical Role ◽  
Distribution Networks ◽  
Energy Resources ◽  
Future Research ◽  
Renewable Energy Resources ◽  
Energy Modelling ◽  
Microgrid Energy Management ◽  
Combined Cooling

Microgrids have become increasingly popular in recent years due to technological improvements, growing recognition of their benefits, and diminishing costs. By clustering distributed energy resources, microgrids can effectively integrate renewable energy resources in distribution networks and satisfy end-user demands, thus playing a critical role in transforming the existing power grid to a future smart grid. There are many existing research and review works on microgrids. However, the thermal energy modelling in optimal microgrid management is seldom discussed in the current literature. To address this research gap, this paper presents a detailed review on the thermal energy modelling application on the optimal energy management for microgrids. This review firstly presents microgrid characteristics. Afterwards, the existing thermal energy modeling utilized in microgrids will be discussed, including the application of a combined cooling, heating and power (CCHP) and thermal comfort model to form virtual energy storage systems. Current trial programs of thermal energy modelling for microgrid energy management are analyzed and some challenges and future research directions are discussed at the end. This paper serves as a comprehensive review to the most up-to-date thermal energy modelling applications on microgrid energy management.

scholarly journals A Survey on Microgrid Energy Management Considering Flexible Energy Sources

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2156 ◽  
Author(s):  
Hossein Shayeghi ◽  
Elnaz Shahryari ◽  
Mohammad Moradzadeh ◽  
Pierluigi Siano
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Uncertainty Modeling ◽  
Optimization Techniques ◽  
Point Of View ◽  
Energy Sources ◽  
Market Prices ◽  
Distributed Generations ◽  
Peak Loads ◽  
Microgrid Energy Management

Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids’ EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.

scholarly journals Leveraging a Genetic Algorithm for the Optimal Placement of Distributed Generation and the Need for Energy Management Strategies Using a Fuzzy Inference System

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 172
Author(s):  
Sunny Katyara ◽  
Muhammad Fawad Shaikh ◽  
Shoaib Shaikh ◽  
Zahid Hussain Khand ◽  
Lukasz Staszewski ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Management ◽  
Fuzzy Inference System ◽  
Distribution System ◽  
Fuzzy Inference ◽  
Management Strategies ◽  
Test System ◽  
Optimal Placement ◽  
Inference System ◽  
Simulated Environment

With the rising load demand and power losses, the equipment in the utility network often operates close to its marginal limits, creating a dire need for the installation of new Distributed Generators (DGs). Their proper placement is one of the prerequisites for fully achieving the benefits; otherwise, this may result in the worsening of their performance. This could even lead to further deterioration if an effective Energy Management System (EMS) is not installed. Firstly, addressing these issues, this research exploits a Genetic Algorithm (GA) for the proper placement of new DGs in a distribution system. This approach is based on the system losses, voltage profiles, and phase angle jump variations. Secondly, the energy management models are designed using a fuzzy inference system. The models are then analyzed under heavy loading and fault conditions. This research is conducted on a six bus radial test system in a simulated environment together with a real-time Power Hardware-In-the-Loop (PHIL) setup. It is concluded that the optimal placement of a 3.33 MVA synchronous DG is near the load center, and the robustness of the proposed EMS is proven by mitigating the distinct contingencies within the approximately 2.5 cycles of the operating period.

Microgrid energy management in grid-connected and islanding modes based on SVC

2014 ◽  
Vol 86 ◽  
pp. 964-972 ◽  
Author(s):  
Hossam A. Gabbar ◽  
Abdelazeem A. Abdelsalam
Keyword(s):  
Energy Management ◽  
Microgrid Energy Management
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