scholarly journals Price-Response Matrices Design Methodology for Electrical Energy Management Systems Based on DC Bus Signalling

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1787
Author(s):  
Lucas V. Bellinaso ◽  
Edivan L. Carvalho ◽  
Rafael Cardoso ◽  
Leandro Michels
Keyword(s):  
Power Management ◽  
Energy Management ◽  
Low Voltage ◽  
Electrical Energy ◽  
Power Sharing ◽  
Price Response ◽  
Energy Management Systems ◽  
Management Algorithm ◽  
Dc Bus ◽  
Battery Energy

Prosumers’ electrical installations (PEIs), as nanogrids and low-voltage microgrids, have gained importance in recent years following the development of standards such as the IEC 60364-8 series. In these systems, all distributed energy resources (DERs) are usually integrated using dc bus coupling. The IEC 60364-8-3 predicts an electrical energy management system (EEMS) for power-sharing. The overall research framework of this paper is the nanogrid power management, where complex algorithms are required, as well as the conventional state machines and hierarchical controls. However, the addition of new DERs in such systems is not straightforward due to the complicated parameter settings for energy usage optimization. A different control strategy, named price-based power management, has been conceived to make the EEMS scalable to include new sources and simplify parameterization. Since it is analogous to economic markets, most users understand the concepts and feel comfortable tuning parameters according to their own cost/benefits goals. This paper proposes a price-based power management algorithm for EEMS to automatically design the price-response matrices (PRMs). The PRMs are a way to organize power management, considering new DERs and variable price of energy. The main contribution is the methodology to design the PRMs. Experimental results are carried out to demonstrate the effectiveness of the proposed strategy. The results were obtained with a 1.5 kW prototype composed of a PV generator, battery energy storage, loads, and grid connection.

Electrical energy management for low-voltage clients

2007 ◽  
Author(s):  
B. Huyck ◽  
J Cappelle ◽  
K. Stul ◽  
K. Duerloo ◽  
J. Debaenst ◽  
...  
Keyword(s):  
Energy Management ◽  
Low Voltage ◽  
Electrical Energy

Application of State Transition Energy Management Control Algorithm in Fuel Cell

2021 ◽  
Author(s):  
Zheng Pan ◽  
Qihong Xiao ◽  
Yangliang Chen
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
State Transition ◽  
Motor Vehicle ◽  
Transition Energy ◽  
Simulation Software ◽  
Management Control ◽  
Hydrogen Consumption ◽  
Management Algorithm ◽  
Battery Energy

Dynamic programming algorithms are widely used in motor vehicle fuel cells, and can help battery energy management control to perform error analysis. The paper designs the decision-making process of fuel cell charge and discharge management based on the state transition energy management algorithm, which is used to analyse the cumulative causes of errors and the corresponding results. The article uses simulation software to simulate the algorithm proposed in this paper, and finds that the algorithm is an energy management optimization decision, and the error of the hydrogen consumption obtained by the algorithm relative to the theoretical optimal hydrogen consumption is less than 0.25%.

scholarly journals A hybrid power system based on fuel cell, photovoltaic source and supercapacitor

2020 ◽  
Vol 2 (5) ◽  
Author(s):  
Seydali Ferahtia ◽  
Ali Djerioui ◽  
Samir Zeghlache ◽  
Azeddine Houari
Keyword(s):  
Fuel Cell ◽  
Power Sharing ◽  
Dc Microgrid ◽  
Storage Element ◽  
Load Variations ◽  
Management Algorithm ◽  
Controversial Topic ◽  
Management Method ◽  
Dc Bus ◽  
Bus Voltage

Abstract In this study, we present an ameliorated power management method for dc microgrid. The importance of exploiting renewable energy has long been a controversial topic, and due to the advantages of DC over the AC type, a typical DC islanded micro-grid has been proposed in this paper. This typical microgrid is composed of two sources: fuel cell (FC), solar cell (PV) and one storage element [supercapacitor (SC)]. Here, we aimed to provide a management strategy that guarantees optimized bus voltage with arranged power-sharing between the sources. This proposed management aims to provide high-quality energy to the load under different loading conditions with variable solar irradiance, taking into account the FC state. Due to the slow dynamics of the FC, the SC was equipped to supply the transient period. A management algorithm is implemented to hold the DC bus voltage stable against the load variations. The management controller is based on differential flatness approach to generate the references. The DC bus is regulated by the SC energy; to reduce the fluctuations in the DC bus voltage, The PI controller is implemented. This proposed strategy reduces the voltage ripple in the DC bus. Moreover, it provides permanent supplying to the load with smooth behaviour over the sudden changes in the demand as depicted in the simulation results. Our study revealed that this proposed manager can be used for this kind of grids easily.

scholarly journals Residential energy management systems with renewables and battery energy storage

2021 ◽  
Author(s):  
Aidan Brookson
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Predictive Control ◽  
Community Integration ◽  
Cost Savings ◽  
Management Systems ◽  
Modern World ◽  
Future Research ◽  
Energy Management Systems ◽  
Battery Energy

With increasing concern towards the environmental impact of energy production, distribution, and consumption in the modern world, the overall energy landscape is changing. This Master’s Thesis investigates methods of addressing these inevitable transformations through the incorporation of renewable energy and energy storage on the residential-scale using energy management systems (EMSs). A simulated residential house model was developed in order to compare a variety of different energy management techniques on the same basis. The simulated EMS investigation has covered: deterministic EMSs, those in their most basic forms; adaptive EMSs, utilizing machine learning and predictive control algorithms; and, a transactional EMS. The deterministic EMSs produced the least annual cost savings, but are the simplest to implement. Adaptive EMSs have shown the highest estimated cost savings, with increased controller complexity as a trade-off. The transactive EMS has shown intermediate cost savings, with additional potential benefits such as demand response and community integration capabilities. Experimental work has been conducted verifying critical claims of the systems, focusing on battery output control and inter-agent controller communication. The most interesting areas warranting future research involve implementing predictive control experimentally – and on a wider scale – and investigating transactive control on the community level.

scholarly journals A Smart Grid Energy Management Problem for Data-driven Design with Probabilistic Reachability Guarantees

10.29007/5qvt ◽  
2018 ◽  
Author(s):  
Daniele Ioli ◽  
Alessandro Falsone ◽  
Marianne Hartung ◽  
Axel Busboom ◽  
Maria Prandini
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Energy Production ◽  
Electrical Energy ◽  
Environmental Data ◽  
Data Driven ◽  
Management Problem ◽  
Local Power ◽  
Energy Management Strategy ◽  
Battery Energy

In this paper we describe an energy management benchmark problem for a smart grid where electrical energy is supplied to a load via local power production from a solar PhotoVoltaic (PV) installation. The smart grid is connected with the main grid, which can eventually provide the energy needed for balancing demand and generation. The goal is to set the battery energy flow so as to keep the energy exchange with the main grid as close as possible to a nominal profile, within certified bounds, avoiding the fluctuations caused by the local PV energy production. Some energy production profiles of the PV installation and environmental data on irradiation and temperature are available for the design of the energy management strategy, together with a hybrid model for the battery and the electrical load profile. We describe a data-driven solution, pointing out its limits and providing some hint on possible direction for improvement.

scholarly journals Power Management System Based on Predefined Schedule Using Control App

2017 ◽  
Author(s):  
Amel Mazhar Yousif Ali Mohammed ◽  
Vrajesh Dinesh Maheta
Keyword(s):  
Power Management ◽  
Low Voltage ◽  
Electrical Energy ◽  
Android Application ◽  
Sultanate Of Oman ◽  
Project Approach ◽  
Energy Devices ◽  
Time Table ◽  
Power Management System ◽  
Save Energy

In large organizations devices operating on electrical energy are manually switched and remain ON throughout the day. Most venues are seldom used or used according to predefined schedule. When the energy devices remain ON, even when the venue is not being used, a lot of energy is wasted. The proposed approach suggests development of automatic ON or OFF switching devices  to avoid wasting energy for each venue depending on the time table. The proposed project intends to conserve energy consumption by optimizing scheduling of load to optimize utilization. Considering the importance given to energy conservation by the Sultanate of Oman, to save energy, a study on the present prevailing system has been carried out. The results of this study provide an insight to the energy consumed in a sample venue. The project approach has significant improvement to save energy. In order to overcome the energy  wasted over manually switching, this project is designed to load devices according to using time by android application. The android application has been designed to gather all essential timetable details of each room. Which connected directly with microcontroller through Wi-Fi communication. According to received data , the signal which received by microcontroller may include ether high voltage or low voltage. The microcontroller detects the voltage and based on the data which received from android application, its activates the relay driver to switch particular relay.

scholarly journals Residential energy management systems with renewables and battery energy storage

2021 ◽  
Author(s):  
Aidan Brookson
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Predictive Control ◽  
Community Integration ◽  
Cost Savings ◽  
Management Systems ◽  
Modern World ◽  
Future Research ◽  
Energy Management Systems ◽  
Battery Energy

With increasing concern towards the environmental impact of energy production, distribution, and consumption in the modern world, the overall energy landscape is changing. This Master’s Thesis investigates methods of addressing these inevitable transformations through the incorporation of renewable energy and energy storage on the residential-scale using energy management systems (EMSs). A simulated residential house model was developed in order to compare a variety of different energy management techniques on the same basis. The simulated EMS investigation has covered: deterministic EMSs, those in their most basic forms; adaptive EMSs, utilizing machine learning and predictive control algorithms; and, a transactional EMS. The deterministic EMSs produced the least annual cost savings, but are the simplest to implement. Adaptive EMSs have shown the highest estimated cost savings, with increased controller complexity as a trade-off. The transactive EMS has shown intermediate cost savings, with additional potential benefits such as demand response and community integration capabilities. Experimental work has been conducted verifying critical claims of the systems, focusing on battery output control and inter-agent controller communication. The most interesting areas warranting future research involve implementing predictive control experimentally – and on a wider scale – and investigating transactive control on the community level.

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