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Discontinuous transmission (DTX) is an efficient technology to improve the energy efficiency of the wireless cellular networks. DTX enables the deactivation of some components of the base station in sufficient short time, which can decrease the energy consumption without affecting the normal operation of the mobile networks. In addition, we consider distributed smart grid which can power the cellular networks using renewable and conventional energy. The distributed smart grid has many different energy retailers with variant energy resource, such as solar energy, wind energy, and conventional energy. Comparing with conventional energy, the renewable energy is more environmental friendly, but more expensive. As a result, it is necessary to obtain a good tradeoff between the operation cost and greenhouse gas (GHG) emission. In this paper, we jointly optimize the DTX, resource allocation, and smart grid energy procurement to maximize the profit of the network operators and minimize the GHG emission. We formulate the joint optimization problem as a mixed integer programming problem. By exploiting the structure of the coupled constraint of the problem, we propose a suboptimal distributed algorithm based on the Lagrangian dual method, and the algorithm can be performed at cellular network and smart grid alternately, which can significantly decrease the signaling and computational overhead. Simulation results illustrate that the proposed DTX scheme can significantly enhance the energy saving, and further improve the energy efficiency of the cellular networks.

Based on analysis of construction and operation of micro integrated energy systems (MIES), this paper presents economic optimization for their configuration and sizing. After presenting typical models for MIES, a residential community MIES is developed by analyzing residential direct energy consumption within a general design procedure. Integrating with available current technologies and local resources, the systematic design considers a prime mover, fed by natural gas, with wind power, photovoltaic generation, and two storage devices serving thermal energy and power to satisfy cooling, heating and electricity demands. Control strategies for MIES also are presented in this study. Multi-objective formulas are obtained by analyzing annual cost and dumped renewable energy to achieve optimal coordination of energy supply and demand. According to historical load data and the probability distribution of distributed generation output, clustering methods based on K-means and discretization methods are employed to obtain typical scenarios representative of uncertainties. The modified non-dominated sorting genetic algorithm is applied to find the Pareto frontier of the constructed multi-objective formulas. In addition, aiming to explore the Pareto frontier, the dumped energy cost ratio is defined to check the energy balance in different MIES designs and provide decision support for the investors. Finally, simulations and comparision show the appropriateness of the developed model and the applicability of the adopted optimization algorithm.

This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to auto-produce part of the energy he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics.

In recent years, there has been a growing interest in cloud technologies. Using current cloud solutions, it is however difficult to create customizable multi-tenant applications, especially if the application must support varying Quality of Service (QoS) guarantees. Software Product Line Engineering (SPLE) and feature modeling techniques are commonly used to address these issues in non-cloud applications, but these techniques cannot be ported directly to a cloud context, as the common approaches are geared towards customization of on-premise deployed applications, and do not support multi-tenancy. In this paper, we propose an architecture for the development and management of customizable Software as a Service (SaaS) applications, built using SPLE techniques. In our approach, each application is a composition of services, where individual services correspond to specific application functionalities, referred to as features. A feature-based methodology is described to abstract and convert the application information required at different stages of the application life-cycle: development, customization and deployment. We specifically focus on how development feature models can be adapted ensuring a one-to-one correspondence between features and services exists, ensuring the composition of services yields an application containing the corresponding features. These runtime features can then be managed using feature placement techniques. The proposed approach enables developers to define significantly less features, while limiting the amount of automatically generated features in the application runtime stage. Conversion times between models are shown to be in the order of milliseconds, while execution times of management algorithms are shown to improve by 5 to 17% depending on the application case.

This paper presents the concept and design of a novel roadway microgrid. It operates as a smart microgrid that optimally utilizes the public right-of-way and roadway infrastructure to provide cost-effective, highly efficient, and reliable wind/solar electric power production, distribution, storage, and utilization. The fundamental unit of the microgrid is called the energy-plus roadway/traffic signal light (EPRTL), which contains a grid-connected wind/solar hybrid generation system installed on the pole of a roadway/traffic signal light for clean electric power production. The term “energy-plus” stands for annual energy consumption that is less than production. The generated electric power will be consumed locally by the roadway/traffic signal light; the excess power generated will be stored in batteries, optimally distributed in the microgrid, and supplied to the utility main grid. The deployment of the proposed roadway microgrid will dramatically change the role of the public right-of-way from an energy consumer to an energy producer, leading to energy-plus roadways. This will not only reduce the roadway agency operating costs but also generate new revenues for the Highway Trust Fund. The use of renewable electric power will also promote the development of green roadways.

The global electrical energy consumption is still rising and there is a demand to double the power capacity within 20 years. The production, distribution and use of energy should be as technological efficient as possible and incentives to save energy at the end-user should also be set up. Deregulation of energy has in the past lowered the investment in larger power plants, which means the need for new electrical power sources may be very high in the near future. Two major technologies will play important roles to solve the future problems. One is to change the electrical power production sources from the conventional, fossil (and short term) based energy sources to renewable energy resources. Another is to use high efficient power electronics in power generation, power transmission/distribution and end-user application. This paper discuss some of the most emerging renewable energy sources, wind energy and photovoltaics, which by means of power electronics are changing from being minor energy sources to be acting as important power sources in the energy system.

The main ambition of the RE-COGNITION Horizon 2020 project (https://re-cognition-project.eu/), in which Technical University of Cluj-Napoca is involved, is to develop a future and technology-proof integration solution aiming to maximize the utilization of the energy that is locally produced by building-level Renewable Energy Sources (RES) technologies, and the reduction of implicit and explicitly induced costs. In the frame of the project, a RES Integration Platform is developed, which incorporate existing, as well as newly developed RES and storage components, along with peripheral electrical and thermal load equipment (HVACs, chillers, ICT devices, conventional load equipment etc.). The RES Integration Platform aims to optimize the building energy flows, regardless of type and conditions. Several pilots with different building environments and climate zones, all around Europe, will be selected to test the RE-COGNITION framework components. This will sufficiently fulfil the validation purposes of the developed technologies and comply with the end-user needs. In this paper, we present the general description of the Romanian pilot site, as well as the energy consumption indicators measured in the last 3 years prior to the project’s start. An analysis of the local context which provides the technical/socio/economic constraints that the project should handle is also presented.