scholarly journals Harnessing the Full Potential of Industrial Demand-Side Flexibility: An End-to-End Approach Connecting Machines with Markets through Service-Oriented IT Platforms

2019 ◽  
Vol 9 (18) ◽  
pp. 3796 ◽  
Author(s):  
Martin Roesch ◽  
Dennis Bauer ◽  
Leon Haupt ◽  
Robert Keller ◽  
Thomas Bauernhansl ◽  
...  

The growing share of renewable energy generation based on fluctuating wind and solar energy sources is increasingly challenging in terms of power grid stability. Industrial demand-side response presents a promising way to balance energy supply and consumption. For this, energy demand is flexibly adapted based on external incentives. Thus, companies can economically benefit and at the same time contribute to reducing greenhouse gas emissions. However, there are currently some major obstacles that impede industrial companies from taking part in the energy markets. A broad specification analysis systematically dismantles the existing barriers. On this foundation, a new end-to-end ecosystem of an energy synchronization platform is introduced. It consists of a business-individual company-side platform, where suitable services for energy-oriented manufacturing are offered. In addition, one market-side platform is established as a mediating service broker, which connects the companies to, e.g., third party service providers, energy suppliers, aggregators, and energy markets. The ecosystems aim at preventing vendor lock-in and providing a flexible solution, relying on open standards and offering an integrated solution through an end-to-end energy flexibility data model. In this article, the resulting functionalities are discussed and the remaining deficits outlined.

2018 ◽  
Vol 48 (2) ◽  
pp. 162-177 ◽  
Author(s):  
Susanne Durst ◽  
Pietro Evangelista

Purpose This paper aims to explore knowledge management (KM) practices implemented by third-party logistics service companies (3PLs) and the main barriers slowing down the adoption of such practices. Design/methodology/approach The methodological approach used in this paper is based on a multiple case study analysis involving a set of 3PLs operating in Italy and Sweden. The empirical analysis has explored the KM practices used by 3PLs and the main barrier hindering their adoption. Findings In spite of some adoption, the findings suggest that 3PLs are not sufficiently realizing the full potential of KM. The evidence also indicates that there is a link between the type of 3PL company (in terms of the breadth and complexity of the services supplied) and the sophistication of KM tools adopted. Research limitations/implications From a research point of view, further research should focus on the validation of the link between the number and sophistication of KM tools used and the breadth of services supplied. Further research should also focus on exploring how KM can support 3PL companies in enhancing their performance. Practical implications From a practical point of view, the findings may help the management of 3PL companies to take a more strategic approach to KM and thus its contribution to the firms’ overall goals. Additionally, it is critical to conduct a careful analysis of current and future KM needs to identify the most suitable KM solutions linked to the specific characteristics of the business in which 3PLs operate. Originality/value This study provides fresh insights into the adoption of KM practices in logistics service organizations. The findings advance the limited body of knowledge regarding this topic and contribute to the further development of the study of KM.


Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8600
Author(s):  
Alain Aoun ◽  
Hussein Ibrahim ◽  
Mazen Ghandour ◽  
Adrian Ilinca

Global economic growth, demographic explosion, digitization, increased mobility, and greater demand for heating and cooling due to climate change in different world areas are the main drivers for the surge in energy demand. The increase in energy demand is the basis of economic challenges for power companies alongside several socio-economic problems in communities, such as energy poverty, defined as the insufficient coverage of energy needs, especially in the residential sector. Two main strategies are considered to meet this increased demand. The first strategy focuses on new sustainable and eco-friendly modes of power generation, such as renewable energy resources and distributed energy resources. The second strategy is demand-side oriented rather than the supply side. Demand-side management, demand response (DR), and energy efficiency (EE) programs fall under this category. On the other hand, the decentralization and digitization of the energy sector convoyed by the emersion of new technologies such as blockchain, Internet of Things (IoT), and Artificial Intelligence (AI), opened the door to new solutions for the energy demand dilemma. Among these technologies, blockchain has proved itself as a decentralized trading platform between untrusted peers without the involvement of a trusted third party. This newly introduced Peer-to-Peer (P2P) trading model can be used to create a new demand load control model. In this article, the concept of an energy cap and trade demand-side management (DSM) model is introduced and simulated. The introduced DSM model is based on the concept of capping consumers’ monthly energy consumption and rewarding consumers who do not exceed this cap with energy tradeable credits that can be traded using blockchain-based Peer-to-Peer (P2P) energy trading. A model based on 200 households is used to simulate the proposed DSM model and prove that this model can be beneficial to both energy companies and consumers.


Author(s):  
Jin Han ◽  
Jing Zhan ◽  
Xiaoqing Xia ◽  
Xue Fan

Background: Currently, Cloud Service Provider (CSP) or third party usually proposes principles and methods for cloud security risk evaluation, while cloud users have no choice but accept them. However, since cloud users and cloud service providers have conflicts of interests, cloud users may not trust the results of security evaluation performed by the CSP. Also, different cloud users may have different security risk preferences, which makes it difficult for third party to consider all users' needs during evaluation. In addition, current security evaluation indexes for cloud are too impractical to test (e.g., indexes like interoperability, transparency, portability are not easy to be evaluated). Methods: To solve the above problems, this paper proposes a practical cloud security risk evaluation method of decision-making based on conflicting roles by using the Analytic Hierarchy Process (AHP) with Aggregation of Individual priorities (AIP). Results: Not only can our method bring forward a new index system based on risk source for cloud security and corresponding practical testing methods, but also can obtain the evaluation result with the risk preferences of conflicting roles, namely CSP and cloud users, which can lay a foundation for improving mutual trusts between the CSP and cloud users. The experiments show that the method can effectively assess the security risk of cloud platforms and in the case where the number of clouds increased by 100% and 200%, the evaluation time using our methodology increased by only by 12% and 30%. Conclusion: Our method can achieve consistent decision based on conflicting roles, high scalability and practicability for cloud security risk evaluation.


Network ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 75-94
Author(s):  
Ed Kamya Kiyemba Edris ◽  
Mahdi Aiash ◽  
Jonathan Loo

Fifth Generation mobile networks (5G) promise to make network services provided by various Service Providers (SP) such as Mobile Network Operators (MNOs) and third-party SPs accessible from anywhere by the end-users through their User Equipment (UE). These services will be pushed closer to the edge for quick, seamless, and secure access. After being granted access to a service, the end-user will be able to cache and share data with other users. However, security measures should be in place for SP not only to secure the provisioning and access of those services but also, should be able to restrict what the end-users can do with the accessed data in or out of coverage. This can be facilitated by federated service authorization and access control mechanisms that restrict the caching and sharing of data accessed by the UE in different security domains. In this paper, we propose a Data Caching and Sharing Security (DCSS) protocol that leverages federated authorization to provide secure caching and sharing of data from multiple SPs in multiple security domains. We formally verify the proposed DCSS protocol using ProVerif and applied pi-calculus. Furthermore, a comprehensive security analysis of the security properties of the proposed DCSS protocol is conducted.


2021 ◽  
Vol 13 (13) ◽  
pp. 7354
Author(s):  
Jiekun Song ◽  
Xiaoping Ma ◽  
Rui Chen

Reverse logistics is an important way to realize sustainable production and consumption. With the emergence of professional third-party reverse logistics service providers, the outsourcing model has become the main mode of reverse logistics. Whether the distribution of cooperative profit among multiple participants is fair or not determines the quality of the implementation of the outsourcing mode. The traditional Shapley value model is often used to distribute cooperative profit. Since its distribution basis is the marginal profit contribution of each member enterprise to different alliances, it is necessary to estimate the profit of each alliance. However, it is difficult to ensure the accuracy of this estimation, which makes the distribution lack of objectivity. Once the actual profit share deviates from the expectation of member enterprise, the sustainability of the reverse logistics alliance will be affected. This study considers the marginal efficiency contribution of each member enterprise to the alliance and applies it to replace the marginal profit contribution. As the input and output data of reverse logistics cannot be accurately separated from those of the whole enterprise, they are often uncertain. In this paper, we assume that each member enterprise’s input and output data are fuzzy numbers and construct an efficiency measurement model based on fuzzy DEA. Then, we define the characteristic function of alliance and propose a modified Shapley value model to fairly distribute cooperative profit. Finally, an example comprising of two manufacturing enterprises, one sales enterprise, and one third-party reverse logistics service provider is put forward to verify the model’s feasibility and effectiveness. This paper provides a reference for the profit distribution of the reverse logistics.


2021 ◽  
pp. 1-12
Author(s):  
Gokay Saldamli ◽  
Richard Chow ◽  
Hongxia Jin

Social networking services are increasingly accessed through mobile devices. This trend has prompted services such as Facebook and Google+to incorporate location as a de facto feature of user interaction. At the same time, services based on location such as Foursquare and Shopkick are also growing as smartphone market penetration increases. In fact, this growth is happening despite concerns (growing at a similar pace) about security and third-party use of private location information (e.g., for advertising). Nevertheless, service providers have been unwilling to build truly private systems in which they do not have access to location information. In this paper, we describe an architecture and a trial implementation of a privacy-preserving location sharing system called ILSSPP. The system protects location information from the service provider and yet enables fine grained location-sharing. One main feature of the system is to protect an individual’s social network structure. The pattern of location sharing preferences towards contacts can reveal this structure without any knowledge of the locations themselves. ILSSPP protects locations sharing preferences through protocol unification and masking. ILSSPP has been implemented as a standalone solution, but the technology can also be integrated into location-based services to enhance privacy.


Author(s):  
Wei Zhang ◽  
Yifan Dou

Problem definition: We study how the government should design the subsidy policy to promote electric vehicle (EV) adoptions effectively and efficiently when there might be a spatial mismatch between the supply and demand of charging piles. Academic/practical relevance: EV charging infrastructures are often built by third-party service providers (SPs). However, profit-maximizing SPs might prefer to locate the charging piles in the suburbs versus downtown because of lower costs although most EV drivers prefer to charge their EVs downtown given their commuting patterns and the convenience of charging in downtown areas. This conflict of spatial preferences between SPs and EV drivers results in high overall costs for EV charging and weak EV adoptions. Methodology: We use a stylized game-theoretic model and compare three types of subsidy policies: (i) subsidizing EV purchases, (ii) subsidizing SPs based on pile usage, and (iii) subsidizing SPs based on pile numbers. Results: Subsidizing EV purchases is effective in promoting EV adoptions but not in alleviating the spatial mismatch. In contrast, subsidizing SPs can be more effective in addressing the spatial mismatch and promoting EV adoptions, but uniformly subsidizing pile installation can exacerbate the spatial mismatch and backfire. In different situations, each policy can emerge as the best, and the rule to determine which side (SPs versus EV buyers) to subsidize largely depends on cost factors in the charging market rather than the EV price or the environmental benefits. Managerial implications: A “jigsaw-piece rule” is recommended to guide policy design: subsidizing SPs is preferred if charging is too costly or time consuming, and subsidizing EV purchases is preferred if charging is sufficiently fast and easy. Given charging costs that are neither too low nor too high, subsidizing SPs is preferred only if pile building downtown is moderately more expensive than pile building in the suburbs.


2021 ◽  
Vol 13 (1) ◽  
pp. 20-39
Author(s):  
Ahmed Aloui ◽  
Okba Kazar

In mobile business (m-business), a client sends its exact locations to service providers. This data may involve sensitive and private personal information. As a result, misuse of location information by the third party location servers creating privacy issues for clients. This paper provides an overview of the privacy protection techniques currently applied by location-based mobile business. The authors first identify different system architectures and different protection goals. Second, this article provides an overview of the basic principles and mechanisms that exist to protect these privacy goals. In a third step, the authors provide existing privacy protection measures.


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