How to integrate electric vehicles in the future energy system?

Main challenges within the energy system of tomorrow are more volatile, less controllable and at the same time more decentralized electricity generation. Furthermore, the increasing research and development activities on electric vehicles (EV) make a significant share of electric vehicles within the passenger car fleet in 2030 more and more likely. This will lead to a further increase of power demand during peak hours. Answers to these challenges are seen, besides measures on the electricity supply side (e. g. investing in more flexible power plants or storage plants), in (1) grid extensions, which are expensive and time consuming due to local acceptance, and in (2) influencing electricity demand by different demand side management (DSM) approaches. Automatic delayed charging of electric vehicles as one demand side management approach can help to avoid peaks in household load curves and, even more, increase the low electricity demand during the night. This facilitates integrating more volatile regenerative power sources, too. Bidirectional charging (V2G) and storing of electricity extends the possibilities to integrate electric vehicles into the grid. But, comparing electricity storage costs and availability of electric vehicles with costs and technical conditions of other technologies leads to the conclusion, that vehicle to grid (V2G) is currently not competitive - but might be competitive in the future, e. g. within the electricity reserve market. In summary, the paper gives an overview of the future electricity market with the focus on electric vehicles and argues for automatic delayed charging of electric vehicles due to economic and technical reasons

Cost-Aware Green Cellular Networks with Energy and Communication Cooperation

Energy cost of cellular networks is ever-increasing to match the surge of wireless data traffic, and the saving of this cost is important to reduce the operational expenditure (OPEX) of wireless operators in future. The recent advancements of renewable energy integration and two-way energy flow in smart grid provide potential new solutions to save the cost. However, they also impose challenges, especially on how to use the stochastically and spatially distributed renewable energy harvested at cellular base stations (BSs) to reliably supply time- and space-varying wireless traffic over cellular networks. To overcome these challenges, in this article we present three approaches, namely, {\emph{energy cooperation, communication cooperation, and joint energy and communication cooperation}}, in which different BSs bidirectionally trade or share energy via the aggregator in smart grid, and/or share wireless resources and shift loads with each other to reduce the total energy cost.Comment: Submitted for possible publicatio

The role of DSM + C to facilitate the integration of renewable energy and low carbon energy technologies

Recent legislation and building regulations have aiming to reduce the energy demands of buildings and include renewable based micro-generation technologies. Due to the variations in energy delivery from these technologies, optimised control over building plant and loads is essential if we are to achieve a good demand-supply match and achieve a reduction in energy demands. This paper reports on research being undertaken as part of the UK EPSRC SuperGen Future Networks programme, specifically relating to the development of algorithms for simulating dynamic demand side control strategies to identify demand-supply matching options when deploying building integrated renewable energy and low carbon technologies. The development of demand side management and control (DSM+c) is a means to improve the dynamic demand-supply match taking account of the available demand side management capacity and time of occurrence. The principle of the developed DSM+c algorithms is to maximise the available control capacity which will enable a better demand-supply match while minimising any impact on users. This paper will demonstrate the application of DSM+c to improve the energy efficiency of a building (e.g. reduced total capacity), restructure the demand pattern via load shifting and switching (e.g. on/off or proportional control) to one more favourable to building integrated renewables. The impact of different control strategies on demand profile restructuring will be demonstrated using simulation to alter the settings of the DSM+c parameters - such as priority, methods and periods - for a given demand profile. The paper will conclude by presenting the outcomes from a case study using the decision support/design tool, MERIT where the developed DSM+c algorithms have been implemented to better facilitate the match between demand and building integrated clean energy supply technologies at the individual multi-familiy building level

Low-Stress Bicycling and Network Connectivity

For a bicycling network to attract the widest possible segment of the population, its most fundamental attribute should be low-stress connectivity, that is, providing routes between people’s origins and destinations that do not require cyclists to use links that exceed their tolerance for traffic stress, and that do not involve an undue level of detour. The objective of this study is to develop measures of low-stress connectivity that can be used to evaluate and guide bicycle network planning. We propose a set of criteria by which road segments can be classified into four levels of traffic stress (LTS). LTS 1 is suitable for children; LTS 2, based on Dutch bikeway design criteria, represents the traffic stress that most adults will tolerate; LTS 3 and 4 represent greater levels of stress. As a case study, every street in San Jose, California, was classified by LTS. Maps in which only bicycle-friendly links are displayed reveal a city divided into islands within which low-stress bicycling is possible, but separated from one another by barriers that can be crossed only by using high-stress links. Two points in the network are said to be connected at a given level of traffic stress if the subnetwork of links that do not exceed the specified level of stress connects them with a path whose length does not exceed a detour criterion (25% longer than the most direct path). For the network as a whole, we demonstrate two measures of connectivity that can be applied for a given level of traffic stress. One is “percent trips connected,” defined as the fraction of trips in the regional trip table that can be made without exceeding a specified level of stress and without excessive detour. This study used the home-to-work trip table, though in principle any trip table, including all trips, could be used. The second is “percent nodes connected,” a cruder measure that does not require a regional trip table, but measures the fraction of nodes in the street network (mostly street intersections) that are connected to each other. Because traffic analysis zones (TAZs) are too coarse a geographic unit for evaluating connectivity by bicycle, we also demonstrate a method of disaggregating the trip table from the TAZ level to census blocks. For any given TAZ, origins in the home-to-work trip table are allocated in proportion to population, while destinations are allocated based on land-use data. In the base case, the fraction of work trips up to six miles long that are connected at LTS 2 is 4.7%, providing a plausible explanation for the city’s low bicycling share. We show that this figure would almost triple if a proposed slate of improvements, totaling 32 miles in length but with strategically placed segments that provide low-stress connectivity across barriers, were implemented

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method

Cloud based testing of business applications and web services

This paper deals with testing of applications based on the principles of cloud computing. It is aimed to describe options of testing business software in clouds (cloud testing). It identifies the needs for cloud testing tools including multi-layer testing; service level agreement (SLA) based testing, large scale simulation, and on-demand test environment. In a cloud-based model, ICT services are distributed and accessed over networks such as intranet or internet, which offer large data centers deliver on demand, resources as a service, eliminating the need for investments in specific hardware, software, or on data center infrastructure. Businesses can apply those new technologies in the contest of intellectual capital management to lower the cost and increase competitiveness and also earnings. Based on comparison of the testing tools and techniques, the paper further investigates future trend of cloud based testing tools research and development. It is also important to say that this comparison and classification of testing tools describes a new area and it has not yet been done

Study on Capacity, Change and Performance: Interim Report

In 2002 the chair of the Govnet, the OECD's Network on Governance and Capacity Building, asked the European Centre for Development Policy Management (ECDPM) in Maastricht, the Netherlands, to undertake a study of the capacity of organisations and groups of organisations, mainly in low-income countries, its development over time and its relationship to improved performance. The specific purposes of this study were twofold:to enhance understanding of the interrelationships amongst capacity, change and performance across a wide range of development experiences; andto provide general recommendations and tools to support the effectiveness of external interventions aimed at improving capacity and performance

D3.2 Cost Concept Model and Gateway Specification

This document introduces a Framework supporting the implementation of a cost concept model against which current and future cost models for curating digital assets can be benchmarked. The value built into this cost concept model leverages the comprehensive engagement by the 4C project with various user communities and builds upon our understanding of the requirements, drivers, obstacles and objectives that various stakeholder groups have relating to digital curation. Ultimately, this concept model should provide a critical input to the development and refinement of cost models as well as helping to ensure that the curation and preservation solutions and services that will inevitably arise from the commercial sector as ‘supply’ respond to a much better understood ‘demand’ for cost-effective and relevant tools. To meet acknowledged gaps in current provision, a nested model of curation which addresses both costs and benefits is provided. The goal of this task was not to create a single, functionally implementable cost modelling application; but rather to design a model based on common concepts and to develop a generic gateway specification that can be used by future model developers, service and solution providers, and by researchers in follow-up research and development projects.<p></p> The Framework includes:<p></p> • A Cost Concept Model—which defines the core concepts that should be included in curation costs models;<p></p> • An Implementation Guide—for the cost concept model that provides guidance and proposes questions that should be considered when developing new cost models and refining existing cost models;<p></p> • A Gateway Specification Template—which provides standard metadata for each of the core cost concepts and is intended for use by future model developers, model users, and service and solution providers to promote interoperability;<p></p> • A Nested Model for Digital Curation—that visualises the core concepts, demonstrates how they interact and places them into context visually by linking them to A Cost and Benefit Model for Curation.<p></p> This Framework provides guidance for data collection and associated calculations in an operational context but will also provide a critical foundation for more strategic thinking around curation such as the Economic Sustainability Reference Model (ESRM).<p></p> Where appropriate, definitions of terms are provided, recommendations are made, and examples from existing models are used to illustrate the principles of the framework