The global industrial chain and energy supply chain are being reconfigured at an accelerated pace, and the uncertainty of China’s energy supply security is growing significantly. Empowering energy supply chains through the digital economy (diec) has a positive effect on accelerating the transformation of China’s energy supply structure. This paper discusses the effect and mechanisms of the digital economy on energy supply chain efficiency (esce). Specifically, based on the panel data of 112 energy enterprises in China from 2011 to 2019, energy supply chain efficiency and digital economy at the enterprise level were evaluated through three-stage DEA and content analysis, respectively. A two-way fixed effects model and mediation effect mode were adopted to investigate the nexus of diec and esce. The results show that the digital economy improves energy supply chain efficiency, and the conclusion holds water even after a series of robustness tests and endogenous treatment. Meanwhile, its... [more]

In this paper, the problem of charging electric motor vehicles on a motorway is considered. Charging points are located alongside the motorway. It is assumed that there are a number of vehicles on a given section of a motorway. In the motorway, there are several nodes, and for each vehicle, the entering and the leaving nodes are known, as well as the time of entrance. For each vehicle, we know the total capacity of its battery, and the current amount of energy in the battery when entering the motorway. It is also assumed that for each vehicle, there is a finite set of speeds it can use when traveling the motorway. The speed is chosen when entering the motorway, and cannot be changed before reaching the charging station. For each speed, there is given a corresponding power usage; the higher the speed, the larger the power usage. Each vehicle can only use one charger, and when its battery is full, the amount of energy is sufficient for reaching the outgoing node. We look for a feasible s... [more]

Pakistan has been facing energy crises for more than a decade as a result of its reliance on imported fossil fuels, circular debt, political instability, and absurd energy policies. However, the country has abundant renewable energy resources which, if harnessed, may help to effectively cope with ever-increasing energy demand. This review study investigates the country’s economic and energy situations, energy crises, and energy sector performance. A critical analysis of studies conducted on Pakistan’s energy planning since its independence in 1947 is, and policies announced to date are assessed. This review reveals that the economic situation of the country has remained severely stressed, and energy sector performance has been compromised over the years for various underlying reasons. The energy policy narrative in the early decades of the post-independence period focused on water resource management, whereas energy concerns were only realized in the late 1960s as demand grew. The firs... [more]

In recent years, the peak−valley differences in urban power loads have been increasing. It is difficult to maintain the real-time balance of a power system by relying solely on the generation-side resources. As a typical flexible load, an air conditioning load can balance the supply and demand of a power grid by adjusting power using the thermal inertia of buildings. From the perspective of a load aggregator, this study models and aggregates the dispatch of a single inverter air conditioner distributed in a region to determine the adjustment potential of an air conditioning cluster. Then, according to the demand response capacity requirements, an optimal strategy for the aggregate dispatch of an inverter air conditioner considering incentive compensation measures is proposed with the objective of maximizing the load quotient economic benefit. The sensitivity analysis of the compensation factor for temperature rise is also performed. The results show that 3000 inverter air conditioners... [more]

Delays in completing the construction of oil and gas projects impact the production, sustainability, reliability, and revenues of the company, which result in market share losses in the long term. This research aimed to determine, evaluate, and rank the root causes of schedule delays in oil and gas pipeline projects in Saudi Arabia. Forty-seven different causes were identified firstly from a wide-ranging literature review and then finalized through conducting interviews with two local experts. These causes were ranked by distributing and analyzing questionnaires on the topic. Client-related materials, delays in materials and equipment delivery, permit approval, delays in subcontractor work, and delays in preparing and approving engineering drawings were found to be the top five major causes affecting oil and gas pipeline construction projects. From the initial analyses, it was observed that an adversarial relationship was apparent as the results indicated that the parties tended to bla... [more]

The concurrent planning of multiple Distributed Generations (DGs), consisting of solar-DG and DSTATCOM with reconfiguration in IEEE 33 and 69 bus Radial Distribution Network (RDN), using Adaptive Particle Swarm Optimization (APSO) and hybrid Grey Wolf-Particle Swarm Optimization (GWO-PSO), is reported in this paper. For this planning, a novel multiple objective-based fitness-function (MOFF) is proposed based on various performance parameters of the system, such as power losses (both active, as well as reactive loss), system voltage profile, short circuit level of line current (SCLLCurrent), and system reliability. The economic perspective of the system has also been considered based on the various costs, such as fix, loss, and Energy Not Supplied (ENS) cost. Two case studies have been presented on IEEE 33 and 69 bus RDN to validate the efficacy of the proposed methodology. The results analysis of the system shows that better performance can be achieved with the proposed technique for 3... [more]

The electrification of vehicles is considered to be the means of reducing the greenhouse gas (GHG) emissions of the transport sector, but “range anxiety” makes most people reluctant to adopt electric vehicles (EVs) as their main method of transportation. Workplace charging has been proven to counter range anxiety and workplace charging is becoming quite common. A workplace parking lot can house hundreds of EVs. In this paper, a program has been developed in MATLAB that uses the well-known evolutionary optimization algorithm, the genetic algorithm (GA), to optimize the charging schedule of fifty EVs that aims at achieving three goals: (a) keeping the electricity demand low, (b) reducing the cost of charging and (c) applying load shifting. Three schedules were developed for three scenarios. The results demonstrate that each schedule was successful in achieving its goal, which means that scheduling the charging of a fleet of EVs can be used as a method of demand-side management (DSM) in w... [more]

A battery-swapping station (BSS) can serve as a flexible source in distribution systems, since electric vehicle (EV) batteries can be charged at different time periods prior to their swapping at a BSS. This paper presents an EV battery service transformation from charging to swapping batteries for EVs for the capacity enhancement of a distribution system. A novel mathematical model is proposed to optimally quantify and maximize the flexibility of BSS loads in providing demand response for the utility operator while considering technical operations in the distribution grid. Case studies and numerical findings that consider data from the National Household Travel Survey and a 32-bus distribution system are reported and discussed to demonstrate the effectiveness of the proposed model. Offering battery-swapping services helps reduce not only the peak load, but also the station operation cost.

The aim of this study is to evaluate the rate of the changes of the annual volume of the municipal waste deposited in the landfill in Promnik, Poland in the period 2003−2020, and to assess the applicability of archival aerial photos for this kind of survey. The landfill analyzed in this article is the main recipient of garbage from the city of Kielce, with a population of 200,000. That assessment is crucial for municipal waste management planning, bio-gases management, expected use time and reclamation of landfill area. Important issues to consider are how the new legal regulations, in effect from 2012, affected the amount of the municipal waste and the rate of landfill growth. Measurement of the volume changes was conducted using a photogrammetric method on the archival aerial photos from 2003 to 2015 and aerial photos acquired using an unmanned air vehicle in 2020. Reference material was digital elevation model (DEM) of this area, derived from aerial laser scanning performed in 2014.... [more]

This paper presents the results of a study on city logistics in the urban tourist area as a research field. Both disciplines are developing intensively, and the research results have many implications for business practices, in particular for alternative fuel for transport, energy savings, waste management, and creating new business models that meet the challenges of modern society. In the era of decarbonisation, city logistics and tourism must define new rules for coexistence. The identified dominant subfields (tourism, logistics, urban transport, urban development and planning, new technologies, and sustainable development) and the links between them have pointed to some research gaps and suggested a direction for further research. The research procedure applied, adapted to the overall goal of the study, consists of an analysis of publications in the Scopus database (February 2022). A keyword co-occurrence network for the research field of city logistics in the urban tourist area is... [more]

Green hydrogen supply chain includes supply sources, production, and distribution of hydrogen produced from renewable energy sources (RES). It is a promising scientific and application area, as it is related to the problem of instability of power grids supplied with RES. The article presents the conceptual assumptions of the research on the design of a functional multi-criteria model of the stabilization model architecture of energy distribution networks based on a hydrogen energy buffer, taking into account the applicable use of hydrogen. The aim of the research was to identify the variables contributing to the stabilization of the operation of distribution networks. The method used to obtain this result was a systematic review of the literature using the technique of in-depth analysis of full-text articles and expert consultations. The concept of a functional model was described as a matrix in two dimensions in which the identified variables were embedded. The first dimension covers... [more]

The high penetration of electric vehicles (EVs) will burden the existing power delivery infrastructure if their charging and discharging are not adequately coordinated. Dynamic pricing is a special form of demand response that can encourage EV owners to participate in scheduling programs. Therefore, EV charging and discharging scheduling and its dynamic pricing model are important fields of study. Many researchers have focused on artificial intelligence-based EV charging demand forecasting and scheduling models and suggested that artificial intelligence techniques perform better than conventional optimization methods such as linear, exponential, and multinomial logit models. However, only a few research studies focused on EV discharging scheduling (i.e., vehicle-to-grid, V2G) because the concept of EV discharging electricity back to the power grid is relatively new and evolving. Therefore, a review of existing EV charging and discharging-related studies is needed to understand the rese... [more]

In recent years, there has been a growing interest in the study of energy communities. This new definition refers to a community sharing energy resources of different types to meet its needs and reduce the associated costs. Optimization is one of the most widely used techniques for scheduling the operation of an energy community. In this study, we extensively reviewed the mathematical models used depending on the objectives and constraints considered. The models were also classified according to whether they address uncertainty and the inclusion of flexibility constraints. The main contribution of this study is the analysis of the most recent research on the mathematical formulation of optimization models for optimal scheduling of resources in energy communities. The results show that the most commonly used objectives are profit maximization and cost minimization. Additionally, in almost all cases, photovoltaic generation is one of the main energy sources. Electricity prices, renewable... [more]

With the development of microgrids (MGs), an energy management system (EMS) is required to ensure the stable and economically efficient operation of the MG system. In this paper, an intelligent EMS is proposed by exploiting the deep reinforcement learning (DRL) technique. DRL is employed as the effective method for handling the computation hardness of optimal scheduling of the charge/discharge of battery energy storage in the MG EMS. Since the optimal decision for charge/discharge of the battery depends on its state of charge given from the consecutive time steps, it demands a full-time horizon scheduling to obtain the optimum solution. This, however, increases the time complexity of the EMS and turns it into an NP-hard problem. By considering the energy storage system’s charging/discharging power as the control variable, the DRL agent is trained to investigate the best energy storage control method for both deterministic and stochastic weather scenarios. The efficiency of the strategy... [more]

The number of international collaborations in research and development (R&D) has been increasing in the energy sector to solve global environmental problems—such as climate change and the energy crisis—and to reduce the time, cost, and risk of failure. Successful international project planning requires the analysis of research fields and the technology expertise of cooperative partner institutions or countries, but this takes time and resources. In this study, we developed a method to analyze the information on research organizations and topics, taking advantage of data analysis as well as deep learning natural language processing (NLP) models. A method to evaluate the relative superiority of efficient international collaboration was suggested, assuming international collaboration of the National Renewable Energy Laboratory (NREL) and the Korea Institute of Energy Research (KIER). Additionally, a workflow of an automated executive summary and a translation of tens of web-posted article... [more]

Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum among researchers all over the world. Different planning and scheduling models have been proposed in the literature. Each model is unique and has both advantages and disadvantages. Moreover, the performance of the models also varies and is location specific. A model suitable for a developing country may not be appropriate for a developed country and vice versa. This paper provides a classification and overview of charging station placement and charging activity scheduling as well as the global scenario of charging infrastructure planning. Further, this work provides the challenges and solutions to the EV charging infrastructure demand and deployment. The recommendations and fut... [more]

Electrical energy can be traded in liberalized organized markets or by negotiating private bilateral contracts. Competitive markets are central systems where market players can purchase and sell electrical energy. Bilateral contracting consists typically in a private negotiation of power over several months or years between two parties. Price-based demand response considers the active participation of consumers in electricity markets. Consumers adopt demand response programs when responding to market prices or tariffs, as they change over time. Those tariffs can be proposed by retailers by considering their load shape goals, influencing consumers to change their behavior. Consumers may adopt strategies from two different groups, namely by curtailing energy at times of high prices (e.g., peak and intermediate periods) and rescheduling energy away from those times to other times (shifting). This article considers bilateral contracting in electricity markets with demand response. It inves... [more]

Nowadays, the integration of multi-energy carriers is one of the most critical matters in smart energy systems with the aim of meeting sustainable energy development indicators. Hydrogen is referred to as one of the main energy carriers in the future energy industry, but its integration into the energy system faces different open challenges which have not yet been comprehensively studied. In this paper, a novel day-ahead scheduling is presented to reach the optimal operation of a hydrogen-based energy hub, based on a stochastic multi-attribute decision-making approach. In this way, the energy hub model is first developed by providing a detailed model of Power-to-Hydrogen (P2H) facilities. Then, a new multi-objective problem is given by considering the prosumer’s role in the proposed energy hub model as well as the integrated demand response program (IDRP). The proposed model introduces a comprehensive approach from the analysis of the historical data to the final decision-making with t... [more]

This research focuses on the problem of scheduling a set of jobs on unrelated parallel machines subject to release dates, sequence-dependent setup times, and additional renewable resource constraints. The objective is to minimize the maximum completion time (makespan). To optimize the problem, a modified harmony search (MHS) algorithm was proposed. The parameters of MHS are regulated using full factorial analysis. The MHS algorithm is examined, evaluated, and compared to the best methods known in the literature. Four algorithms were represented from similar works in the literature. A benchmark instance has been established to test the sensitivity and behavior of the problem parameters of the different algorithms. The computational results of the MHS algorithm were compared with those of other metaheuristics. The competitive performance of the developed algorithm is verified, and it was shown to provide a 42% better solution than the others.

The procedure of ceramics fusion to cobalt−chromium (Co−Cr) base dental crowns affects their corrosion behavior and biological tolerance. This study’s purpose was to comparatively evaluate the effect of heat treatment (HT) applicable for dental ceramics firing on the corrosion properties among Co−Cr base alloys fabricated via different methods: casting (CST), milling soft metal and post sintering (MSM), and selective laser melting (SLM). All specimens were subjected to a heat treatment corresponding to a full firing schedule. The microstructure and elemental composition of oxidized surfaces were investigated by scanning electron microscopy and energy dispersive spectroscopy. Corrosion properties were examined by electrochemical potentiodynamic polarization tests. The values of jcorr, Ecorr, Rp, and breakdown potential Ebr were estimated. The oxide layers formed during the HT process corresponded to the composition of the original alloys’ structure. Among the thermal treated alloys, SLM... [more]

Due to the impact of globalization, the competition between enterprises has become fierce and led the supply chains of many industries to be reorganized. One of the consequences is that the operation of many small and medium enterprises (SMs) had become very difficult. Hence, many of SMEs in Taiwan have gone bankrupt and some of them have moved to other places where they have lower production costs, in order to survive; this not only hollowed out the industries but also disconnected the supply chains in their mother countries. Because Taiwan’s SMEs are generally poor in innovation, this study explored the implementation of the theory of inventive problem-solving (TRIZ) with alignment of new product development (NPD) and supply chain management (SCM) to strengthen the innovation and productivity of new products, so that SMEs can refer to its use to aid sustainable business operation. We considered an SME in Taiwan as a case to study and investigate the strategies that it employed to ach... [more]

As the complexity of supply chains increases, the enhancement of resilience for mitigating sustainable disruption risks in supply chains is an important issue. Quality function deployment (QFD) has been successfully applied in many domains to solve multicriteria decision-making (MCDM) problems. However, research on developing two houses of quality to connect sustainable supply chain disruption risks, resilience capacities, and resilience-enhancing features in elevator manufacturing supply chains by using the MCDM approach is lacking. This study aims to develop a framework for exploring useful decision-making by integrating the MCDM approach and QFD. By applying the framework, supply chain resilience can be improved by identifying the major sustainable risks and the key resilience to mitigate these risks. Important managerial insights and practical implications are obtained from the framework implementation in a case study of the elevator manufacturing industry. To strengthen resilience... [more]

This work focuses on the study of robust no-wait flow shop scheduling problem (R-NWFSP) under the interval-valued fuzzy processing time, which aims to minimize the makespan within an upper bound on total completion time. As the uncertainty of actual job processing times may cause significant differences in processing costs, a R-NWFSP model whose objective function involves interval-valued fuzzy sets (IVFSs) is proposed, and an improved SAA is designed for its efficient solution. Firstly, based on the credibility measure, chance constrained programming (CCP) is utilized to make the deterministic transformation of constraints. The uncertain NWFSP is transformed into an equivalent deterministic linear programming model. Then, in order to tackle the deterministic model efficiently, a simulated annealing algorithm (SAA) is specially designed. A powerful neighborhood search method and new acceptance criterion are applied to find better solutions. Numerical computations demonstrate the high e... [more]

In this work, a study of the water level control of an inverted conical tank system is presented. This type of tank has highly nonlinear mathematical and dynamic characteristics. Four control strategies are designed, applied, and compared, namely classical Proportional−Integral−Derivative (PID), Gain Scheduling (GS), Internal Model Control (IMC), and Fuzzy Logic (FL). To determine which of the designed control strategies are the most suitable for an inverted conical tank, a comparative study of the behavior of the system is carried out. With this purpose, and considering situations much closer to reality, a variety of scenarios, such as step responses, random input disturbances, and momentary load disturbances, are conducted. Additionally, performance indexes (error- and statistics-based) are calculated to assess the system’s response.

A system dynamics model was developed with the primary purpose of visualizing the behavior of a supply chain (SC) when it adopts a disruptive technology such as additive manufacturing (AM). The model proposed a dynamic hypothesis that defines the following issue: what is the impact of the AM characteristics and processes in the SC? The model was represented through a causal diagram in thirteen variables related to the SC, organized in two feedback cycles and a data flow diagram, based mainly on the three-essential links of the SC and the order display traceability: supplier−focal manufacturer−distribution Network. Once proposed, the model was validated through the evaluation of extreme conditions and sensitivity analysis. As a result, the dynamic behavior of the variables that condition the chain management was analyzed, evidencing reduction times in production, especially in products that require greater complexity and detail, as well as reductions in inventories and the amount of raw... [more]