Search results

To foster the grid integration of both electric vehicles (EV) and renewable generators, the purpose of this paper is to investigate the possible synergies between these players so as to jointly improve the production predictability while ensuring a green mobility. It is here achieved by the mean of a grid commitment over the overall power produced by a collaborative system which here gathers a photovoltaic (PV) plant with an EV fleet. The scope of the present contribution is to investigate the conditions to make the most of such an association, mainly regarding to the management strategies and optimal sizing, taking into account forecast errors on PV production.

To evaluate the collaboration added value, several concerns are aggregated into a primary energy criterion: the commitment compliance, the power spillage, the vehicle charging, the user mobility and the battery aging. Variations of these costs are computed over a range of EV fleet size. Moreover, the influence of the charging strategy is specifically investigated throughout the comparison of three managements: a simple rule of thumb, a perfect knowledge deterministic case and a charging strategy computed by stochastic dynamic programming. The latter is based on an original modeling of the production forecast error. This methodology is carried out to assess the collaboration added value for two operators’ points of view: a virtual power plant (VPP) and a balance responsible party (BRP).

From the perspective of a BRP, the added value of PV-EV collaboration for the energy system has been evidenced in any situation even when the charging strategy is very simple. On the other hand, for the case of a VPP operator, the coupling between the optimal sizing and the management strategy is highlighted.

A co-optimization of the sizing and the management of a PV-EV collaborative system is introduced and the influence of the management strategy on the collaboration added value has been investigated. This gave rise to the presentation and implementation of an original modeling tool of the PV production forecast error. Finally, to widen the scope of application, two different business models have been tackled and compared.

Information technology (IT) systems are already ubiquitous, and their future growth is expected to drive the global economy for the next several decades. However, energy consumption by these systems is growing rapidly, and their sustained growth requires curbing the energy consumption, and the associated heat removal requirements. Currently, 20-50 percent of the incoming electrical power is used to meet the cooling demands of IT facilities. Careful co-optimization of electrical power and thermal management is essential for reducing energy consumption requirements of IT equipment. Such modeling based co-optimization is complicated by the presence of several decades of spatial and temporal scales. The purpose of this paper is to review recent approaches for handling these challenges.

In this paper, the authors illustrate the challenges and possible modeling approaches by considering three examples. The multi-scale modeling of chip level transient heating using a combination of Progressive Zoom-in, and proper orthogonal decomposition (POD) is an effective approach for chip level electrical/thermal co-design for mitigation of reliability concerns, such as Joule heating driven electromigration. In the second example, the authors will illustrate the optimal microfluidic thermal management of hot spots, and large background heat fluxes associated with future high-performance microprocessors. In the third example, data center facility level energy usage reduction through a transient measurements based POD modeling framework will be illustrated.

Through modeling based electrical/thermal co-design, dramatic savings in energy usage for cooling are possible.

The multi-scale nature of the thermal modeling of IT systems is an important challenge. This paper reviews some of the approaches employed to meet this challenge.

This paper aims to survey the need for full capacity utilisation of transmission lines in power systems network operations. It proposes a review of the N-1 security criterion that does not ensure reliable dispatch of optimum power flow during outage contingency. The survey aims to enlarge the network capacity utilisation to rely on the entire transmission lines network operation.

The paper suggests transmission line switching (TLS) approach as a viable corrective mechanism for power dispatch. The TLS process is incorporated into a constraint programming language extension optimisation solver that selects the switchable line candidates as integer variables in the mixed integer programming problem.

The paper provides a practical awareness of reserve capacity in the lines that provide network security in outage contingency. At optimum power flow dispatch, the TLS is extended to optimal transmission line switching (OTLS) that indicates optimal capacity utilisation (OCU) of the available reserve capacity (ARC) in the network lines.

Computational efficiency influenced the extension of the OTLS to optimal transmission switching of power flow (OTSPF). The application of OTSPF helps reduce the use of flexible AC transmission systems (FACTS) and construction of new transmission lines..

The paper surveys TLS efforts in network capacity utilisation. The suggested ARC fulfils the need for an index with which the dispatchable lines may be identified for the optimal capacity utilisation of transmission lines network.

The 2030 United Nations Agenda has framed Sustainable Development Goal 9 around eight targets outlined in Resolution A/RES/71/313 (U.N. General Assembly, 2017). The purpose of this chapter is that the lectors, without much previous knowledge on SDG9, understand the fundamental concepts involved in each of the eight targets. Multiple discussion points emerge when reflecting on the nature of these concepts and others emerge when reflecting on them in the industry settings. The first section of this chapter covers issues concerning resilient infrastructure. Resilient infrastructure is related to targets 9.1, 9.4, and 9.a. This concept needs to cope with extreme natural events potentially associated with global warming and climate change. The second section focusses on the importance of technological innovation in the context of targets 9.5 and 9.b. In a business domain, innovation allows to strengthen industrial competitiveness and increases corporate sustainability. The third concept covered in this chapter is the Information and Communication Technology that is a key to understand target 9.c. Last but not the least, two essential ideas are discussed: Inclusive and sustainable industrialisation and financial services, which are fundamental elements in target 9.2 and target 9.3. In a certain way, it is possible to conclude that both concepts integrate all previous conceptions.

Scholars and professionals committed to fostering sustainable development have urged a re‐examination of the curriculum and restructuring of research in engineering‐focused institutions of higher learning. This article will address the following themes and questions: How can multi‐ and trans‐disciplinary teaching and research coexist in a meaningful way in today's university structures? Does education relevant to sustainable development require its own protected incubating environment to survive, or will it otherwise be gobbled up and marginalized by attempting to instil it throughout the traditional curriculum? What roles can national and EU governments have in accelerating the needed changes? How can it be made safe for courageous students to take educational paths different from traditional tracks, even if technical options exist to do so? What can one learn from comparative analysis of universities in different nations and environments?

This chapter focuses on the common occurrence of wholesale electricity prices that fall below the cost of production. This “negative pricing” in effect represents payment to high-volume consumers for taking excess power off the grid, thus relieving overload. Occurrences of negative pricing have been observed since the wholesale electricity markets have been operating, and occur during periods of low demand, while generators are being kept in reserve for rapid engagement when demand increases (it is expensive and time-consuming to shut down generators and then restart them, so they are often kept in “spooling mode”). In such situations power production may temporarily exceed demand, potentially overloading the system. When the federal government began subsidizing the construction of wind generation projects, with regulations in place requiring transmission grids to accept all of the electricity produced by the wind generators, negative pricing became more frequent.

Midwest Independent Transmission System Operator, Inc. (MISO) is a nonprofit regional transmission organization (RTO) that oversees electricity production and transmission across 13 states and 1 Canadian province. MISO also operates an electronic exchange for buying and selling electricity for each of its five regional hubs.

MISO oversees two types of markets. The forward market, which is referred to as the day-ahead (DA) market, allows market participants to place demand bids and supply offers on electricity to be delivered at a specified hour the following day. The equilibrium price, known as the locational marginal price (LMP), is determined by MISO after receiving sale offers and purchase bids from market participants. MISO also coordinates a spot market, which is known as the real-time (RT) market. Traders in the RT market must submit bids and offers by 30minutes prior to the hour for which the trade will be executed. After receiving purchase and sale offers for a given hour in the RT market, MISO then determines the LMP for that particular hour.

The existence of the DA and RT markets allows producers and retailers to hedge against the large fluctuations that are common in electricity prices. Hedge ratios on the MISO exchange are estimated using various techniques. No hedge ratio technique examined consistently outperforms the unhedged portfolio in terms of variance reduction. Consequently, none of the hedge ratio methods in this study meet the general interpretation of FASB guidelines for a highly effective hedge.

Industry 4.0 is a new trend among organizations. Some organizations have been early adopters or later adopters of Industry 4.0. The purpose of this paper is to investigate how performance effects vary between early and late adopters of Industry 4.0.

This study applies a qualitative research methodology using grounded theory. 14 senior management professionals who have implemented Industry 4.0 participated in this study through a theoretical and snowball sampling approach. These professionals were from manufacturing and service sectors, from North America, Europe and Asia. The study used semi structured open-ended interviews to capture the organizational performance on operational, financial, environmental and social dimensions.

The findings were analyzed in terms of four broad themes which emerged from the interviews. In operational performance the operational and implementation cost will be higher for early adopters. The late adopters may enjoy the advantage in terms of improved business models. In terms of financial performance, the early adopters may see a marginal increase in profit and increased stock price compared to late adopters. The performance on the environmental dimension will see early adopters enjoying material efficiency, energy savings and an improved image of the company compared to late adopters. In social performance, the early adopters will provide a better quality of work life, safer manufacturing environment. However, the resistance from labor unions will be higher for early adopters compared to late adopters.

Organizations must decide the timing of implementation of Industry 4.0. This study will act as a guide wherein they can decide to be an early adopter or late adopter based on knowledge of the resulting performance consequences.

This is the first paper that studies the performance effects of early versus late adopters of Industry 4.0.

Lean management has been used in various constructions around the world for more than a quarter of a century, and it is an important factor in the construction of new projects. In relation to demolition management, only standards and codes and general principles of demolition of specific buildings were evaluated. The purpose of this study is providing relation between lean management on demolition processes of municipality buildings evaluated.

This study investigates the lean demolition of demolished and renovated buildings in a metropolitan area that can be extended to all cities. In the first stage, the effective factors in the demolition of the building based on lean management were identified through a valid questionnaire based on the valid Delphi approach. Social, economic and environmental considerations were considered in designing the appropriate questionnaire.

The modified approach between the fuzzy method and partial least squares was used to evaluate important variables. All of the modified processes were developed in MATLAB by the authors of this paper. The results show that customer-focused degradation parameter has the weakest effect and waste removal variable has the most effect on lean management.

Statistical results show that there is no significant difference between the effect of lean management on variables such as demolition time, quality and type of construction (p < 0.05).