Simultaneous energy management and optimal components sizing of a zeroemission ferry boat
مدیریت همزمان انرژی و اندازه بهینه اجزای یک کشتی بدون حرکت-2020
Due to environmental and economic issues as well as the high performance of marine vessels, efficient energy using has been becoming more demanding. Also, in order to have a zero-emission ship, the utilization of a fuel cell combined with energy storage such as batteries gets more and more attention. In this work, a zero-emission hybrid energy system, including fuel cells, batteries, and cold-ironing, is employed to have an environmentally friendly vessel, and to create condition in which ship operates with high performance, both energy management and components sizing of fuel cells and batteries using real data of ferry boat and intelligent optimization method are done simultaneously. In addition, all constraints related to energy management and component sizing with the topography of the boat and electric power sources are represented and analyzed thoroughly. Ultimately, hourly energy management and component sizing for one specific day are considered in this work, and to optimize this problem, the Improved Sine Cosine Algorithm (ISCA) is utilized. According to obtained results, the proposed energy management and component sizing result in the high-performance ship which could be utilized in the marine industry.
Keywords: Energy management | Proton exchange membrane fuel cell | Component Sizing | Zero-emission ships
Quality manipulation and limit corruption in competitive procurement
دستکاری کیفیت و محدود کردن فساد در خرید رقابتی-2020
We study competitive procurement administered by an agent who is supposed to evaluate bids on both price and quality by a scoring rule designed by the principal. Since the agent is in charge of verifying delivered quality, he has an opportunity to manipulate his evaluation of quality proposals in exchange for a bribe. In the presence of corruption, the optimal mechanism can be implemented by both first- score and second-score auctions in such a way that the scoring rule should deemphasize quality relative to price. We further identify factors that influence equilibrium corruption: (1) more efficient suppliers are willing to pay higher bribe; (2) the probability of corruption is decreasing in competition and increasing in the agent’s manipulation power; (3) compared to the first-score auction, the second-score auction leads to higher equilibrium bribe and thus is more vulnerable to corruption.
Keywords: Project management | Multidimensional procurement | Corruption
PV generator and energy storage systems for laboratory building
ژنراتور PV و سیستم های ذخیره انرژی برای آزمایشگاه-2020
A microgrid contains a PV generator and energy storage system connected in a laboratory building. Power generation is scheduled to meet the load of the building to adjust optimally the generation exchange within the microgrid. In this study, the problem of decreasing the cost of energy under varied system constraints and user decisions is addressed. In addition, minimizing electricity costs of the utility grid is proposed as an optimization model. To minimize the using of the grid, ESS is scheduled according to the peak demand. The proposed algorithm schedules the charging and discharging of the battery. A switching control technique is implemented for optimal scheduling of the hybrid system. Simulation is performed using GAMS, the obtained results validate that the intended model can minimize the operation cost.
Keywords: Day ahead | PV generation | Optimization | Multi objective scheduling | Energy management
Crude oil maritime transportation: Market fluctuation characteristics and the impact of critical events
حمل و نقل دریایی نفت خام: ویژگی های نوسانات بازار و تأثیر حوادث مهم-2020
The international crude oil maritime transportation system has always been disturbed by the external environment and its own mechanism of supply and demand, which can sometimes last for a long time. BDTI (Baltic Exchange Dirty Tanker Index) is one of the most typical indexes in the crude oil maritime transportation market, which is affected by many uncertain events and often lasts for a long time. So it is very significant to study fluctuation characteristics of the crude oil maritime transportation system and assess the impact of critical events, which have been referred to in this paper by improving the R/S model and selecting three international transportation lines in marine shipping ranging from 2008 to 2019. Through model applications, numerical results validate the effectiveness of this method, showing all of the three transportation lines possess long-term memory. The impact of the four critical events has also been evaluated. The study will help crude oil enterprises make investment decision on potential transportation lines and give policymakers advice to maintain stability of the crude oil industry.
Keywords: Energy management | Crude oil transportation | Fluctuation characteristics | The impact of critical events
Entrepreneurship, trust and corruption
کارآفرینی ، اعتماد و فساد-2020
I propose a theoretical model where trust towards strangers is a channel through which insti- tutions determine economic outcomes, in particular, entrepreneurship and corruption. More importantly, I show that the role of trust has been overlooked since high levels of trust do not always enhance desirable economic outcomes. Trust helps individuals to participate in eco- nomic exchanges aligned with social welfare, but it also facilitates individuals to cooperate for the achievement of corrupt deals. Under this more general view of trust, the model generates a non-trivial new prediction at the individual level. Speciﬁcally, the individual-level relationship between honesty and trust changes depending on the institutional quality of a country. Dishon- est individuals are the more trusting individuals in countries with poor institutions, and the less trusting in countries with good institutions. Using individual-level data of 80 countries from the World Value Survey and the European Values Study, I present empirical evidence in support of this prediction.
Keywords: Trust | Corruption | Bureaucracy | Entrepreneurship
AI-based optimization of PEM fuel cell catalyst layers for maximum power density via data-driven surrogate modeling
بهینه سازی مبتنی بر هوش مصنوعی لایه های کاتالیزور سلول سوختی PEM برای حداکثر چگالی توان از طریق مدل سازی جایگزین داده محور-2020
Catalyst layer (CL) is the core electrochemical reaction region of proton exchange membrane fuel cells (PEMFCs). Its composition directly determines PEMFC output performance. Existing experimental or modeling methods are still insufficient on the deep optimization of CL composition. This work develops a novel artificial intelligence (AI) framework combining a data-driven surrogate model and a stochastic optimization algorithm to achieve multi-variables global optimization for improving the maximum power density of PEMFCs. Simulation results of a three-dimensional computational fluid dynamics (CFD) PEMFC model coupled with the CL agglomerate model constitutes the database, which is then used to train the data-driven surrogate model based on Support Vector Machine (SVM), a typical AI algorithm. Prediction performance shows that the squared correlation coefficient (R-square) and mean percentage error in the test set are 0.9908 and 3.3375%, respectively. The surrogate model has demonstrated comparable accuracy to the physical model, but with much greater computation- resource efficiency: the calculation of one polarization curve will be within one second by the surrogate model, while it may cost hundreds of processor-hours by the physical CFD model. The surrogate model is then fed into a Genetic Algorithm (GA) to obtain the optimal solution of CL composition. For verification, the optimal CL composition is returned to the physical model, and the percentage error between the surrogate model predicted and physical model simulated maximum power densities under the optimal CL composition is only 1.3950%. The results indicate that the proposed framework can guide the multi-variables optimization of complex systems.
Keywords: Proton exchange membrane fuel cell | Catalyst layer composition | Agglomerate model | Data-driven surrogate model | Stochastic optimization algorithm
Blockchain for Internet of Energy management: Review, solutions, and challenges
بلاکچین برای مدیریت انرژی اینترنت: بررسی ، راه حل ها و چالش ها-2020
After smart grid, Internet of Energy (IoE) has emerged as a popular technology in the energy sector by integrating different forms of energy. IoE uses Internet to collect, organize, optimize and manage the networks energy information from different edge devices in order to develop a distributed smart energy infrastructure. Sensors and communication technologies are used to collect data and to predict demand and supply by consumers and suppliers respectively. However, with the development of renewable energy resources, Electric Vehicles (EVs), smart grid and Vehicle-to-grid (V2G) technology, the existing energy sector started shifting towards distributed and decentralized solutions. Moreover, the security and privacy issues because of centralization is another major concern for IoE technology. In this context, Blockchain technology with the features of automation, immutability, public ledger facility, irreversibility, decentralization, consensus and security has been adopted in the literature for solving the prevailing problems of centralized IoE architecture. By leveraging smart contracts, blockchain technology enables automated data exchange, complex energy transactions, demand response management and Peer-to-Peer (P2P) energy trading etc. Blockchain will play vital role in the evolution of the IoE market as distributed renewable resources and smart grid network are being deployed and used. We discuss the potential and applications of blockchain in the IoE field. This article is build on the literature research and it provides insight to the end-user regarding the future IoE scenario in the context of blockchain technology. Lastly this article discusses the different consensus algorithm for IoE technology.
Keywords: Consensus algorithm | Blockchain | Internet of Energy | Smart grid | Vehicle-to-grid
Business models in process industries: Emerging trends and future research
مدل های تجاری در صنایع فرآیندی: روندهای نوظهور و تحقیقات آینده-2020
This article reviews the literature on business models in process industries. The review reveals that the business model concept has gained an increasing amount of attention in process-industrial research, but it also shows that the literature exhibits a lack of construct clarity and that it is developing in different domains, depending on the perspectives scholars have taken to study business models in process industries. Specifically, while innovation management scholars have explored the relationship between technological innovations and business models as well as the process and outcomes of business model innovation, scholars from the domain of production management have focused on value chain (re)configurations and taken a system-based perspective to consider boundary-spanning exchanges with key stakeholders in the design of business models. However, despite variance in the perspectives, the review further shows that works in these divergent domains point to a family of emerging themes and to common ideas that have not been explored together. This allows us to identify the particularities of business models in process industries and develop a definition of process-industrial business models, which extends prior business model literature into the process industry context. Furthermore, we synthesize these connections to develop an agenda for future, cross-disciplinary research on business models in process industries that assists cumulative theorizing and subsequent empirical progress.
Keywords: Business model | Business model innovation | Process industries | Production management | Innovation management | Literature review
Design and application of fog computing and Internet of Things service platform for smart city
طراحی و استفاده از سیستم عامل محاسبات مه و اینترنت اشیا برای شهر هوشمند-2020
Fog computing and Internet of Things technology play a prominent role in the construction of smart cities, which can greatly promote the exchange and management of urban information. Emerging network technologies such as fog computing and the Internet of Things can be used to make it easier to build smart cities, which is conducive to the development of urban business, industry and other industries, as well as tourism and transportation management. Therefore, the realization of a smart city will greatly enhance the comprehensive development strength of the city. We analyze the advantages of fog computing and propose an IoT architecture based on fog computing, which effectively solves the problems of big data processing and network scalability. On this basis, a layered fog computing network architecture is proposed to make the city’s operation more coordinated, efficient and harmonious through various intelligent perceptions, information processing and network transmission means.© 2020 Elsevier B.V. All rights reserved.
Keywords: Cloud computing | Fog computing | Smart city | Internet of Things
Towards integrated dialogue policy learning for multiple domains and intents using Hierarchical Deep Reinforcement Learning
به سوی یادگیری سیاست گفتگوی یکپارچه برای چندین حوزه و اهداف با استفاده از یادگیری تقویتی عمیق سلسله مراتبی-2020
Creation of Expert and Intelligent Dialogue/Virtual Agent (VA) that can serve complicated and intricate tasks (need) of the user related to multiple domains and its various intents is indeed quite challenging as it necessitates the agent to concurrently handle multiple subtasks in different domains. This paper presents an expert, unified and a generic Deep Reinforcement Learning (DRL) framework that creates dialogue managers competent for managing task-oriented conversations embodying multiple domains along with their various intents and provide the user with an expert system which is a one stop for all queries. In order to address these multiple aspects, the dialogue exchange between the user and the VA is split into hierarchies, so as to isolate and identify subtasks belonging to different domains. The notion of Hierarchical Reinforcement Learning (HRL) specifically options is employed to learn optimal policies in these hierarchies that operate at varying time steps to accomplish the user goal. The dialogue manager encompasses a toplevel domain meta-policy, intermediate-level intent meta-policies in order to select amongst varied and multiple subtasks or options and low-level controller policies to select primitive actions to complete the subtask given by the higher-level meta-policies in varying intents and domains. Sharing of controller policies among overlapping subtasks enables the meta-policies to be generic. The proposed expert framework has been demonstrated in the domains of ‘‘Air Travel” and ‘‘Restaurant”. Experiments as compared to several strong baselines and a state of the art model establish the efficiency of the learned policies and the need for such expert models capable of handling complex and composite tasks.
Keywords: Dialogue management | Multi-domain | Multi-intent | Hierarchical Reinforcement Learning | Options