To tackle the contradiction between the computation intensive applications and the resource-hungry mobile user equipments (UEs), mobile edge computing (MEC) has been provisioned as a promising solution, which enables the UEs to offload the tasks to the MEC servers. Considering the characteristics of small cell networks (SCNs), integrating MEC into SCNs is natural. But in terms of the high interference, multi-access property, and limited resources of small cell base stations (SBSs), an efficient computation offloading scheme is essential. However, there still lack comprehensive studies on this problem in the densely deployed SCNs. In this paper, we study the energy-efficient computation offloading management scheme in the MEC system with SCNs. The aim of this paper is to minimize the energy consumption of all UEs via jointly optimizing computation offloading decision making, spectrum, power, and computation resource allocation. Specially, the UEs need not only to decide whether to offload but also to determine where to offload. First, we present the computation offloading model and formulate this problem as a mix integer non-linear programming problem, which is NP-hard. Taking advantages of genetic algorithm (GA) and particle swarm optimization (PSO), we design a suboptimal algorithm named as hierarchical GA and PSO-based computation algorithm to solve this problem. Finally, the convergence of this algorithm is studied by simulation, and the performance of the proposed algorithm is verified by comparing with the other baseline algorithms.

An Efficient Computation Offloading Management Scheme in the Densely Deployed Small Cell Networks With Mobile Edge Computing

Microgrid equipped with heterogenous energy resources and a bank of energy storage devices presents the idea of small scale distributed energy management (DEM). DEM facilitates the minimization of the transmission and operation costs, peak load and environmental pollution. Microgrid also enables active customer participation by giving them the access to the real time information and control. The capability of fast restoration against physical/cyber attack, integration of renewable energy resources and information and communication technologies (ICT) make microgrid as an ideal candidate for distributed power systems. The energy management system of microgrid can perform real time energy forecasting of renewable resources, energy storage elements and controllable loads in making proper short term scheduling to minimize total operating costs. Cost benefit analysis of microgrid reveals that cooperation among different microgrids can play an important role in the reduction of import energy cost from the utility grid. Cooperation among microgrids in smart microgrid network (SMN) brings the energy sharing and management issues. In this paper we present a review of existing optimization objectives, constraints, solution approaches and tools used in microgrid energy management. This review paper can provide a foundation to embark on an in depth study in the area of energy management for smart microgrid network.

A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids

Role of optimization techniques in microgrid energy management systems—A review

Home energy management systems (HEMSs) help manage electricity demand to optimize energy consumption and distributed renewable energy generation without compromising consumers’ comfort HEMSs operate according to multiple criteria, including energy cost, weather conditions, load profiles, and consumer comfort They play an increasingly ubiquitous role in energy efficiency through the reduction of electricity consumption within residential and commercial smart grids This paper presents a comprehensive review of the HEMS literature with reference to main concepts, configurations, and enabling technologies In doing so, it also provides a summary of HEMS computing trends and popular communication technologies for demand response applications The ensuing survey offers the reader with an overall overview of current and future trends in HEMS solutions and technologies

/pdf/home-energy-management-system-concepts-configurations-and-55q7ohig5s.pdf

Home Energy Management System Concepts, Configurations, and Technologies for the Smart Grid

With the increasing use of rechargeable lithium-ion battery packs in numerous applications, it calls for an effective evaluation of active battery cell equalization to enhance the whole battery pack's capacity and performance. Plenty of work has focused on cell equalizing circuit and control algorithm design. Still, none of them is devoted to a comprehensive analysis and comparison of cell balancing methods from the topology level. In this article, a review of the state-of-the-art active battery cell equalization methods is conducted, where it is classified as adjacent-based, nonadjacent-based, direct cell-cell, and mixed topologies. This classification can provide a comprehensive way to analyze and compare the existing active cell balancing methods’ performance. Subsequently, the mathematical models of these balancing structures are developed, and extensive simulation results are provided to compare the performance of these equalization topologies in terms of equalization speed. It then comes up with an inclusive economic comparison between them, followed by a discussion.

Active Cell Equalization Topologies Analysis for Battery Packs: A Systematic Review

Balancing algorithms are based on extracting or adding charge in order to have balanced cells. Their goal is to protect the battery from damage and to help prolong the battery's life. Without a balancing system the total capacity of the pack will decrease more rapidly, and the estimation of the state of charge will be unreal. The paper presents a fuzzy controlled battery equalization method for series connected battery strings. The algorithm was developed in order to reduce the cell equalization time. The simulation and experimental results show the advantage of the predicted equalization algorithm for lithium-ion battery stacks.

Fuzzy controlled energy converter equalizer for lithium ion battery packs

An islanded microgrid energy management controller validated by using hardware-in-the-loop emulators

The paper presents the techno-economic analysis and optimization of a hybrid renewable energy system composed of solar panels, batteries a geothermal generator and a biomass generator in the region of Oradea, Romania that is intended to supply a vegetable greenhouse. Based on the load specifications, after calculation and optimization, the minimum required sizes of the generators are: 14 solar panels, eight 230 Ah batteries and a minimum cumulated power of 2 kW for the biomass and geothermal generator. The renewable energy system is than optimized using PV*Sol software.

Analysis and optimization of a geothermal, biomass, solar hybrid system: An application of PV*Sol software

The aim of this paper is to describe a SCADA tool for an intelligent microgrid. This application provides control over a smart microgrid that contains inverters, batteries and generators with power meters. In this system, the energy is generated by solar panels, a geothermal generator, a biomass generator and stored in batteries. The data is collected and represented on a PC Interface. The communication between the components and the application is accomplished through different protocols and standards. The connected devices can be detected, the inverters and power meter values, such as power and voltage, are read through the software application. These values, such as power, voltage, the speed of generators, can also be modified through this interface.

/pdf/scada-development-for-an-islanded-microgrid-2a4n4ktb81.pdf

SCADA development for an islanded microgrid

This This paper presents a comparison between two digital control methods for a boost power factor correction (PFC) converter based on the dynamic response at load changes and levels for the harmonic currents injected back on to the network The power topology used is a bridgeless boost converter due to its high efficiency and low electromagnetic interferences (EMI) levels The algorithms compared are average current mode control and one cycle control A procedure to develop the digital control methods using software blocks is proposed starting from the standard analog controllers for PFC regulators

Comparison between digital average current mode control and digital one cycle control for a bridgeless PFC boost converter

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