Efficient Energy Management System Research Articles

The path towards sustainable energy

Civilization continues to be transformed by our ability to harness energy beyond human and animal power. A series of industrial and agricultural revolutions have allowed an increasing fraction of the world population to heat and light their homes, fertilize and irrigate their crops, connect to one another and travel around the world. All of this progress is fuelled by our ability to find, extract and use energy with ever increasing dexterity. Research in materials science is contributing to progress towards a sustainable future based on clean energy generation, transmission and distribution, the storage of electrical and chemical energy, energy efficiency, and better energy management systems.

Optimal energy management system based on stochastic approach for a home Microgrid with integrated responsive load demand and energy storage

In recent years, increasing interest in developing small-scale fully integrated energy resources in distributed power networks and their production has led to the emergence of smart Microgrids (MG), in particular for distributed renewable energy resources integrated with wind turbine, photovoltaic and energy storage assets. In this paper, a sustainable day-ahead scheduling of the grid-connected home-type Microgrids (H-MG) with the integration of non-dispatchable/dispatchable distributed energy resources and responsive load demand is co-investigated, in particular to study the simultaneously existed uncontrollable and controllable production resources despite the existence of responsive and non-responding loads. An efficient energy management system (EMS) optimization algorithm based on mixed-integer linear programming (MILP) (termed as EMS-MILP) using the GAMS implementation for producing power optimization with minimum hourly power system operational cost and sustainable electricity generation of within a H-MG. The day-ahead scheduling feature of electric power and energy systems shared with renewable resources as a MILP problem characteristic for solving the hourly economic dispatch-constraint unit commitment is also modelled to demonstrate the ability of an EMS-MILP algorithm for a H-MG under realistic technical constraints connected to the upstream grid. Numerical simulations highlight the effectiveness of the proposed algorithmic optimization capabilities for sustainable operations of smart H-MGs connected to a variety of global loads and resources to postulate best power economization. Results demonstrate the effectiveness of the proposed algorithm and show a reduction in the generated power cost by almost 21% in comparison with conventional EMS.

Efficient Energy Management System Based on GA and Classical Boolean Approach

In this paper, two intelligent strategies for energy management unit for a home integrated with smart grid are proposed. The strategies are based on classical Boolean and genetic algorithm (GA). The objective is to optimize the cost saving for the end consumer. The price of energy varies by the hour depending on the load on the grid. The two strategies predict when and by how much the storage unit installed in the house should charge and release for 24 h of the day, satisfying the constraint that the load demand of the house at any particular hour should always be met. The strategies were tested by real time data collected by the Department of Energy for a typical house in the Chicago, Illinois region for the year 2013. Both the strategies achieve cost savings; however, it has been found that GA-based strategy results in higher cost saving. The impact of the capacity of the energy storage unit (ESU) on the cost saving has been analyzed for a GA strategy and cost saving obtained when the capacity of ESU is 1.5 times and 2 times the house hold load at any given hour is presented.

Estimation of Required EVs Battery Capacity for Leveling Demand Energy Considering Parking Durations

Vehicle-to-grid (V2G) is a key technology that is receiving significant attention as a method for achieving an efficient energy management system (EMS) by connecting electric vehicles (EVs) to an electric power grid. In this study, a fuzzy control method and an optimization control method were proposed as effective control methods for reducing the installation battery capacity and the electric charge in one day by leveling the electric load. As the result, the required battery capacity was 429 kWh for IEVBS model, and 480 kWh for MEVBS model using optimization control method. The control method could save at most $17.98 of an electric bill and achieve power leveling.

Optimization of Energy Consumption via Artificial Intelligence: A Study

In the future intelligent machines will replace or enhance human capabilities in many areas. Artificial Intelligence is the intelligence exhibited by machines or software.”John McCarthy” who coined the tem in 1955 defines it as the “science and engineering of making intelligent machines”. As we are aware of the fact that energy consumption has grown tremendously over a few decades in all over the world which is environmentally unfriendly. It is essential at this stage of development to pause and critically examine the state of affairs via the application of AI in energy conservation and environmental system engineering. In this paper we describe in a general way on how the existing applications of AI techniques provide intelligent solution to optimize the energy conservation now and in the future. Also, how Wireless Sensor and Actuator Networks are used to remotely monitor and control the environment according to the decisions made by the centralized reasoner and EEMS(Energy Efficiency Management System)provides effective energy saving measures and high quality energy conservation services Energy efficiency has nowadays become one of the most challenging task for both academic and commercial organizations and this has boosted research on novel fields.

Data-Driven Reinforcement Learning–Based Real-Time Energy Management System for Plug-In Hybrid Electric Vehicles

Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off between real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. A case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.

MinNet: toward more intelligent smart home energy management systems with fewer sensors

The smart home technology has attracted considerable attention for decades. Nowadays, as the drastic increase of home energy consumption, efficient home energy management system HEMS has become a major building block. Aiming at building an easy-to-deploy intelligent HEMS, we design MinNet to i monitor the states of individual home appliances using the minimum number of power sensors and ii provide occupancy states of a house/room with inference intelligence. In detail, we use convenient plug-in power sensors to construct a wireless sensor network for data collection and establish an analytical framework based on the power model of appliances. By solving a carefully-designed optimisation problem, we find the minimum number of sensors to decode the states of appliances from their aggregated power and infer the occupancy states of the house/room. We implement MinNet in a house and validate its accuracy in appliance states monitoring and occupancy inference.

Green cloud computing: reduced overload with a better architecture

Software systems architects had been continually facing challenges of scaling up software systems architectures. Scaling up the architectures to meet these needs certainly introduces additional energy cost. Improvement of applications, algorithms, energy efficient hardware has been done to achieve energy efficiency. Reducing the energy demands in such architectures is always challenging. The greatest environmental challenge today is e-wastes and energy crisis, bringing green computing in the limelight. Green computing requires algorithms and mechanisms to be redesigned for energy efficiency. In accordance to the state of art for distributed software architectures, are not aware on green cloud computing while the implementation needs, changing the whole infrastructure cost effectively. Software architectures don’t provide the primitives for reasoning and managing power consumption. In present work, an energy efficient resource management system for virtualized Cloud data centers that reduces operational costs and provides required Quality of Service (QoS) has been proposed and fulfilled. Our proposal towards software engineering demands to be green aware, where the software engineering and design activities should not only be judged by their technical merits, but also by their contributions to energy savings. In particular, the software system architecture seems to be adequate to address green-aware concerns but need revival. Software architectures should be green-aware, providing power management mechanisms as part of the architecture. The results of present work improvised that the proposed technique brings substantial energy savings, while ensuring reliable QoS. This justifies further investigation and development of the proposed resource management system.

IJIREEICE - Electrical, Electronics, Instrumentation and Control

2 Abstract: The environmental aspect like oil depletion, global heating and CO2 gas emissions have become a concern and have propelled the development of an efficient and extendable energy management system (EMS) using fuel cell and battery sources for Hybrid Electric Vehicles. In this paper, a poser of a hybrid electric vehicle with energy management system with multiple source of energy is developed and analyzing the performance of HEV on Matlab. The multiple sources of energy, such as a battery and fuel cell (FC), EMS and power controller are designed and modelled using MATLAB. The developed control strategies continuously support the EMS of the multiple sources of energy for a vehicle under normal load conditions. The performance of the proposed system is analyzed in terms of vehicle speed and Load power. These study results suggest that the proposed control technique provides an efficient and feasible EMS for light electric vehicles. I. INTRODUCTION Around 90% of today's automobiles run on petroleum based product, which are estimated to be depleted by 2050. Moreover, current automobiles utilize only 27% of the energy released from petroleum and rest is wasted into the atmosphere. Despite recent efforts to improve fuel efficiency and reduce toxic emissions in cars, emissions have continued to increase steadily in the past two decades. For preservation of gasoline for future and increasing the efficiency of vehicle an electric vehicle can be a major breakthrough. An electric vehicle is pollution free and is efficient at low speed conditions mainly in high traffic areas. But battery charging is time consuming. Moreover, it cannot provide high power required by drives during high speed conditions or in slopes of hilly areas. Therefore the combination of fuel cell and lithium ion battery is one of the best options for gaining high performance in electric vehicle. Gasoline engine proves its efficiency at higher speeds in high ways and waste a lot of energy in urban areas. A hybrid electric vehicle solves these problems by combining the fuel cell and lithium ion battery and uses both the power sources at their efficient conditions. The objective of this project aims at better utilization of fuel energy and reduces dependence on non- renewable resources using latest technology. The implementation involves development of HEV that uses battery as well as fuel cell power for propulsion of vehicle.

Dynamic programming technique for optimizing fuel cell hybrid vehicles

Transportation industries are incorporating fuel cell hybrid vehicles to lower the levels of polluting emissions. This paper develops a dynamically efficient energy management system for the purpose of achieving an optimal power allocation between the energy sources while adhering to component requirements and maintaining the required operational performance using a weighted improved dynamic programming technique. A power train configuration with a fuel cell dominant model based on a Simulink architecture of the electric vehicle is used for testing the energy management system. Two stage control methodologies are addressed, pre-driving off-line optimization using weighted improved dynamic programming algorithm and on-line optimization using PID controller. The technique proves convergence faster than normal dynamic programming algorithms which suffer from dimensionality problems. Weights are incorporated in the fitness function in-order to improve convergence rate of such a method with long duration driving cycles. The performance criteria is based on the overall operational cost as well as the hydrogen consumption per trip. The stress on the vehicle sources is approximated based on a haar wavelet transform of the instantaneous power. Results indicate lower costs and hydrogen consumption levels using the weighted improved dynamic programming as compared to the rule based algorithms.

Smart microgrid hierarchical frequency control ancillary service provision based on virtual inertia concept: An integrated demand response and droop controlled distributed generation framework

Low inertia stack, high penetration levels of renewable energy source and great ratio of power deviations in a small power delivery system put microgrid frequency at risk of instability. On the basis of the close coupling between the microgrid frequency and system security requirements, procurement of adequate ancillary services from cost-effective and environmental friendly resources is a great challenge requests an efficient energy management system. Motivated by this need, this paper presents a novel energy management system that is aimed to coordinately manage the demand response and distributed generation resources. The proposed approach is carried out by constructing a hierarchical frequency control structure in which the frequency dependent control functions of the microgrid components are modeled comprehensively. On the basis of the derived modeling, both the static and dynamic frequency securities of an islanded microgrid are provided in primary and secondary control levels. Besides, to cope with the low inertia stack of islanded microgrids, novel virtual inertia concept is devised based on the precise modeling of droop controlled distributed generation resources. The proposed approach is applied to typical test microgrid. Energy and hierarchical reserve resource are scheduled precisely using a scenario-based stochastic programming methodology. Moreover, analyzing the results verifies the impressiveness of the proposed energy management system in cost-effectively optimizing the microgrid ancillary service procurement.

Efficient Energy Management System or the technologies of carbon storage and sequestration as aviable alternative to reduce CO2emissions in the short term

Efficient Energy Management System or the technologies of carbon storage and sequestration as aviable alternative to reduce CO₂emissions in the short term

Research on Energy Management Platform Based on Marketing and Distribution Integrated System

Marketing and Distribution Integrated System is the use of modern information technology, on the basis of a unified enterprise network equipment and customer information model, basic information and topological relationship, used in customer-facing supply reliability management, customer outage management, line loss of four sub-management, business expanding auxiliary field and distribution network construction planning decisions such as the standardization of GIS-based, integrated enterprise-wide information platform. This paper describes a GIS-based business integration system with the main content and functionality, energy efficiency management system to achieve a variety of integrated business systems and energy efficiency management decision-making system that can effectively address the development of enterprise information supply information silos that exist , huge amounts of data and processes curing problems with the integration of power supply enterprise business planning and construction of information systems provide a useful reference.

Optimal power allocation for a FCHV based on linear programming and PID controller

Hybrid electric vehicles positively influence the transportation industry with regards to reducing the use of fossil fuels and minimizing polluting emissions. A class of such vehicles incorporates fuel cells and energy storage systems as alternatives to internal combustion engines. This paper develops a dynamically efficient energy management system for fuel cell hybrid vehicles for the purpose of achieving an optimal power allocation between the energy sources while adhering to component requirements and maintaining the essential operational performance. The paper addresses a two stage control methodologies, pre-driving optimization using linear programming algorithms and on-line optimization using PID controllers and component mechanisms. The performance criteria are based on the overall operational cost as well as the hydrogen consumption per trip. Comparison against a state control algorithm shows improvements in hydrogen consumption.

A Study on Supply with Consideration on Expectation Level of Energy-Saving Technology and Consumption Pattern of Consumers – Focusing on Boilers

With To obtain implications for supply of high efficiency home appliance, this study focused on boilers in the household sector to analyze efficiency grade, replacement cycle and usage condition of boilers and to examine possibility for introduction of high efficiency boiler and energy conservation.As a result, about 40% of households had grade 1 boiler, about 54% of households had grade 4 boiler, and remaining 6% had other grades. This did not differ much from the product ratio for each efficiency registered on [Efficiency Comparison], an energy efficiency management system. Increasing ratio of consumers are expected to purchase high efficiency boiler as development and supply of high efficiency products are institutionally reinforced.Also, general replacement cycle of boilers was investigated as 9 years based on living conditions, environment and marketing survey on the market. Energy conservation from sequential replacement of boilers other than grade 1 into grade 1 boilers during this life cycle of 9 years was calculated to be 6%.

An Energy Management System of a Fuel Cell/Battery Hybrid Boat

All-electric ships are now a standard offering for energy/propulsion systems in boats. In this context, integrating fuel cells (FCs) as power sources in hybrid energy systems can be an interesting solution because of their high efficiency and low emission. The energy management strategy for different power sources has a great influence on the fuel consumption, dynamic performance and service life of these power sources. This paper presents a hybrid FC/battery power system for a low power boat. The hybrid system consists of the association of a proton exchange membrane fuel cell (PEMFC) and battery bank. The mathematical models for the components of the hybrid system are presented. These models are implemented in Matlab/Simulink environment. Simulations allow analyzing the dynamic performance and power allocation according to a typical driving cycle. In this system, an efficient energy management system (EMS) based on operation states is proposed. This EMS strategy determines the operating point of each component of the system in order to maximize the system efficiency. Simulation results validate the adequacy of the hybrid power system and the proposed EMS for real ship driving cycles.

Application of Energy Efficiency Optimization Technology in Steel Industry

It's systematically analyzed that energy efficiency optimization technology has been applied in the field of steel industry. The fundamental principal of energy optimization technology is reasonably matching the quality and price of energy as well as energy-dominated systematic energy efficiency management system. Specific measures of energy optimization have been put forward, which include taking high efficiency utilized technology such as energy saving from the original, the production process and recycling of waste heat and waste energy etc., integrating and configuring energy in an optimized way of high efficiency and excellent quality, fully realizing the function of different energy in order to optimize the utilization sequence of energy, and improving the energy medium system by themselves. Finally it is clearly pointed out that the steel industry should pay more consideration about the great deal of energy system which they have used now and an ideal energy evaluation methodology and standard should be built as soon as possible if they want to take full usage of the real role and function of energy in all aspects.

Development of a prototype for remote current measurements of PV panel using WSN

Sensing, monitoring, actuating and information retrieving are expected to play a key role in smart grid energy management strategy. For energy consumption metering, power measurement systems generally implement transformers contactless current sensors but also have a wide variety of technologies especially for integrating renewable generations. One of the key problems of future smart grid is to develop data communication system for distributed intermittent renewable generations to build an efficient energy management and demand response system. In this paper, a test bed has been developed using Wireless Sensor Network (WSN) based on IEEE 802.15.4 standard for remote real time monitoring of current production in a distributed Photovoltaic (PV) plant. ZigBee based WSN is integrated with Arduino microcontroller and current sensor to sense produce current by PV at every moment and forward this data to control unit instantaneously. In the control unit, a LabVIEW based program is developed to receive the data and store in to a database for further processing of energy management by the control unit.

Data Mining-Based Smart Industrial Park Energy Efficiency Management System

Smart industrial park energy efficiency management system is used for solving the demanded side electric power management problem mainly in terms of scientific management. In this system, the data of electric power, electric power quality, and electric energy is acquired in real time by installing an electric power management monitor in the main load points, so as to analyze electric energy efficiency and energy consumption. A large amount of data can be obtained from the system, and if these huge amounts of data are of a value can be further analyzed, finding the unknown factors affecting enterprises energy consumption, equipment performance, and operational efficiency, and the disadvantages of the traditional data processing method. Therefore, an advanced data analysis and processing tool (i.e. efficiency data mining technology) is introduced for analyzing and mining large amounts of data monitored with the smart industrial park system.

Management of a Power System based on Renewable Energy

Abstract The paper presents software and hardware developments for power systems based on renewable energy and their management system. The main purpose is to present the advantage of combined technologies, different solutions for control, communication and data monitoring systems, all of this implemented to develop an efficient energy management system based on renewable energy sources. By using implemented and dedicated hardware and software solutions, the evolution of energy production and consumption can be monitored, and controlled. The advantages of these systems are highlighted by the obtained results from performed experimental simulations such as: implemented SCADA power system based on renewable energy sources, study in GIS models and other informational systems for system performance simulation.