This work presents a model for determining the availability of continuous systems at open pits by applying fuzzy logic and fuzzy inference systems. The applied model was formed by the synthesis of independent partial indicators of availability. The model is based on an expert system for assessing the availability of continuous mining systems. The availability of the system, as a complex state parameter, is decomposed into the partial indicators, reliability, and convenience of maintenance, and the fuzzy compositions, used for integration the partial indicators, are the max−min and min−max compositions. The advantage of this model in comparison to the conventional models is that it takes into account the effect of practical indicators of availability, does not require long-term monitoring, and records necessary to determine the time picture of the system state. This model for determining the availability has a role to help responsible persons at open pits in the planning and control of... [more]

Renewable energy sources (RES) generation has huge environmental and social benefits, as a clean energy source with great potential. However, the difference in the uncertainty characteristics of RES and electric−thermal loads poses a significant challenge to the optimal schedule of an integrated energy system (IES). Therefore, for the different characteristics of the multiple uncertainties of IES, this paper proposes a type-II fuzzy interval chance-constrained programming (T2FICCP)-based optimization model to solve the above problem. In this model, type-II fuzzy sets are used to describe the uncertainty of RES in an IES, and interval numbers are used to describe the load uncertainty, thus constructing a T2FICCP-based IES day-ahead economic scheduling model. The model was resolved with a hybrid algorithm based on interval linear programming and T2FICCP. The simulations are conducted for a total of 20 randomly selected days to obtain the advance operation plan of each unit and the operat... [more]

This paper proposes a smart system for managing the operations of grid-connected charging stations for electric vehicles (EV) that use photovoltaic (PV) sources. This system consists of a mobile application for EV drivers to make charging reservations, an algorithm to optimize the charging schedule, and a remote execution module of charging operations based on the open charge point protocol (OCPP). The optimal charging schedule was obtained by solving a binary integer programming problem. The merits of our solution are illustrated by simulating different charging demand scenarios.

This paper develops and analyzes four energy scenarios for Colombia that consider the El Niño phenomenon and the inclusion of renewable energies in the energy generation matrix for the period 2020−2035. A comparative analysis is presented between the results of the different scenarios proposed. The most relevant finding is the use of the reserve margin as an indicator of system reliability. A scenario which included 7214 MW of large-scale non-conventional renewable energy, 10,000 MW of distributed generation, and 12,240 MW of hydroelectric power was assumed, with a reserve margin of over 50%. Additionally, it was found that for the scenarios in which a generation capacity with non-conventional renewable energies of less than 10,000 MW in 2034 was assumed, the reserve margin of the system in the seasons of the El Niño phenomenon will be less than historical records of the system. Alternatively, it was found that the scenarios in which the inclusion of at least 9600 MW of the electric po... [more]

Recent economic anomalies, including the unprecedented lockdown generated by the COVID-19 crisis, have demonstrated that the weighted average cost of capital (WACC) remains an actual topic in the financial literature and in practice. Companies operate in an increasingly volatile environment, due to twin transitions and interlinked crises, and so they must have specific tools for measuring risk and profitability, in order to enable them to have a sound financial policy. Based on the earlier results obtained by Modigliani and Miller (1963), Harris and Pringle (1985), and Farber, Gillet, and Szafarz (2006), this study shows the relationship between WACC and interest rate. It offers a modified WACC formula that considers unstable market circumstances. The new redefined WACC can be a valuable tool in business planning for companies from different fields. The companies in the energy sector are very interested in the topic of WACC, considering not only the complex nature of the investments ma... [more]

The direct release of energy from the groundwater under the building of the Sobieski Family Palace in Lublin, Poland, and the obtainment of heat and cooling energy for Heating, Ventilation, and Air Conditioning systems (HVAC) provide an opportunity to reduce electricity and heat consumption and to limit CO2 emissions by 15−50%. The upgrade to the Sobieski Family Palace and the addition of new educational and administrative functions require state-of-the-art, energy-saving, and environmentally friendly solutions such as Fuel Cells and Hydrogen for Heating, Ventilation, and Air Conditioning (FCH HVAC) systems. As part of the program “Research for high-quality air in architecture and urban studies,” carried out since 2018 at the Institute of Architecture Planning, Department of Contemporary Architecture, Faculty of Civil Engineering and Architecture of the Lublin University of Technology, in 2021, further research was carried out in order to prepare for the potential implementation in 202... [more]

Dynamic inductive charging is a contact-free technology to provide electric vehicles with energy while they are in motion, thus eliminating the need to conductively charge the batteries of those vehicles and, hence, the required vehicle downtimes. Airport aprons of commercial airports are potential systems to employ this charging technology to reduce aviation-induced CO2 emissions. To date, many vehicles operating on airport aprons are equipped with internal combustion engines burning diesel fuel, hence contributing to CO2 emissions and the global warming problem. However, airport aprons exhibit specific features that might make dynamic inductive charging technologies particularly interesting. It turns out that using this technology leads to some strategic infrastructure design questions for airport aprons about the spatial allocation of the required system components. In this paper, we experimentally analyze these design questions to explore under which conditions we can expect the re... [more]

In order to mitigate the negative effects of global climate change, the Chinese government has committed to achieving peak carbon emissions by 2030 and carbon neutrality by 2060. Since municipal cities are the bottom administrative level for drawing up development plans, it is necessary and important to conduct decarbonization pathway research on municipal energy systems (MESs). However, there is little research on decarbonization at the municipal level, and the impact of development paths in each forecast scenario is mostly based on expert evaluation and qualitative assessment. Therefore, this study established a complete decarbonization framework for MESs, including general research procedures, models, and a sustainable evaluation method. The models of energy consumption and carbon emission were adapted and improved for MESs. In order to quantitatively evaluate the energy system development for each scenario, we proposed an energy−economy−environment−security (3E−S) evaluation method... [more]

Indonesia is currently undergoing the energy transition from heavily fossil fuel-dependent energy to cleaner sources of energy in order to achieve its net-zero emissions by 2060. In addition to reducing fossil fuel dependency, as one of the countries with the most geothermal reserves, the optimization of geothermal energy in Indonesia could be key to facilitating the energy transition. The objective of this paper is to elaborate on the transition process, which incorporates the destabilization of fossil fuel and the growth of geothermal energy, by analyzing the impact of both exogenous and endogenous factors on the supply chain structures of both sectors. This study employs workshop involving geothermal stakeholders in Indonesia, combined with the application of the Multi-Level Perspective (MLP) framework as the theoretical lens. The study found that energy demand, environmental awareness, energy regulations, energy supply chain, and geothermal potential breakthroughs are important asp... [more]

Active Buildings that allow users to adjust their demands on the grid to the needs of the energy system could greatly assist the transition to net zero, but will not be widely adopted unless the businesses involved can make money from doing so. We describe the construction, flexibility and information supply chains of activities needed to make these buildings work. Drawing on the results of an expert workshop, we set out four possible business models deserving further investigation. Developers may find it profitable to build or upgrade energy-efficient buildings with the monitoring and control equipment needed to adjust demand and energy storage as required, selling them soon after completion. Aggregators monitor the state of the building and communicate with the energy system to adjust the building’s demand while maintaining comfort levels, in return for suitable payments. Energy service companies may sell energy-as-a-service and own the equipment instead of a consumer who wishes to m... [more]

This paper studies the multi-level supply chain network equilibrium optimization problem of multi-energy-efficiency products under different government subsidies and demand scales. In the equilibrium optimization problem, manufacturers determine the production volume of the energy-saving products; retailers decide the transaction volume with manufacturers, distribution volume for markets, and marketing efforts of energy-saving products; markets determine the transaction price. Firstly, the optimal decision-making behaviors of manufacturers, retailers, and markets are described. Simultaneously, the global optimization problem is transformed into a finite-dimensional variational inequality formulation. Then, the equilibrium conditions of the whole supply chain network are derived by the Euler method. Finally, a case study verifies the effectiveness of the proposed method. Interestingly, we found that energy-saving subsidies and demand scales were negatively correlated with the marketing... [more]

The power systems of today seem inseparable from clean energy sources such as wind turbines (WTs) and photovoltaics (PVs). However, due to their uncertain nature, operational challenges are expected when WT and PV energy is added to the electricity network. It is necessary to introduce new technologies to compensate for the intermittent nature of renewable energy sources (RESs). Therefore, rationally implementing a demand response (DR) program with energy storage systems (ESSs) in a virtual power plant (VPP) environment is recommended as a way forward to minimize the volatile nature of RESs and improve power system reliability. Our proposed approach aims to maximize social welfare (SW) (i.e., maximization of consumer benefits while minimizing energy costs). Our method assesses the impact of the DR program on SW maximization. Two scenarios are examined, one with and one without a DR program. Stochastic programming theory is used to address the optimization problem. The uncertain behavio... [more]

Even if flat glass is 100% recyclable, only 1% is currently handled in circular or closed-loop supply chains (CLSCs) in Sweden. This has an unnecessary environmental impact, indicating not only the potential for more energy-efficient solutions but also the challenges that need to be understood. The purpose of this article is to increase the knowledge of challenges in applying different types of more or less energy-efficient CLSCs for flat glass. Through a literature review, an overview of CLSC types, together with challenges in different areas, is provided. The CLSC types and challenges are corroborated in a flat glass context, including focus groups and expert interviews. Four CLSC types—two CLSCs based on remanufacturing, one on reconditioning, and one on reuse—are identified. A framework provides implications for both literature and practice. It contains 19 challenges—such as lack of large-scale actors, lack of material knowledge, lack of knowledge of customers’ behavior, lack of pr... [more]

The article proposes methods by which an in-depth analysis of the factors determining the planning activity of municipalities for renewable energy sources can be carried out. The article aims to determine the relationship between the number of local spatial plans specifying designation for renewable energy sources and the municipality’s area, population and planning situation. All local spatial plans in Poland (a total of 104,720 plans) were analysed, distinguishing in each municipality the number of plans with designation for renewable energy sources and micro-installations (a total of 11,338 plans). Then, using quantitative methods, this data was matched with data on the municipalities’ population, area, and planning activity. At the same time, the article provides a literature review of the critical problems concerning the relationship between investments in renewable energy sources and local planning. The barriers encountered are transnational in nature. The discussion section indi... [more]

In this paper, an improved probabilistic roadmap (IPRM) algorithm is proposed to solve the energy consumption problem of multi-unmanned aerial vehicle (UAV) path planning with an angle. Firstly, in order to simulate the real terrain environment, a mathematical model was established; secondly, an energy consumption model was established; then, the sampling space of the probabilistic roadmap (PRM) algorithm was optimized to make the obtained path more explicit and improve the utilization rate in space and time; then, the sampling third-order B-spline curve method was used to curve the rotation angle to make the path smoother and the distance shorter. Finally, the results of the improved genetic algorithm (IGA), PRM algorithm and IPRM algorithm were compared through a simulation. The data analysis shows that the IGA has significant advantages over other algorithms in some aspects, and can be well applied to the path planning of UAVs.

This article provides the state-of-the-art on the optimal planning and design of future district heating (DH) systems. The purpose is to provide practical information of first-step actions for countries with a low DH market share for heating and cooling supply. Previous research showed that for those countries, establishing a heat atlas with accurate geographical data is an essential prerequisite to promote the development of DH systems. In this review, essential techniques for building a high-quality heat atlas are elaborated. This includes a review of methodologies for district thermal energy demand prediction and the status of the integration of sustainable resources in DH systems. In the meanwhile, technical barriers for the implementation of various sustainable heat sources are identified. Furthermore, technologies for the optimal planning of DH systems are discussed. This includes the review of current approaches for the optimal planning of DH systems, discussions on various nove... [more]

Due to the rapidly increasing power demand worldwide, the development of power systems occupies a significant position in modern society. Furthermore, a high proportion of renewable energy resources (RESs) is an inevitable trend in further power system planning, due to traditional energy shortages and environmental pollution problems. However, as RESs are variable, intermittent, and uncontrollable, more challenges will be introduced in transmission expansion planning (TEP). Therefore, in order to guarantee the security and reliability of the power system, research related to TEP with the integration of RESs is of great significance. In this paper, to solve the TEP problem considering load and wind power uncertainties, an AC TEP model solved by a mixed integer non-linear programming (MINLP) is proposed, the high-quality optimal solutions of which demonstrate the accuracy and efficiency of the method. Latin hypercube sampling (LHS) is employed for the scenario generation, while a simulta... [more]

The contact problem of a trochoidal gear is a drawback and a well-known performance indicator of a gerotor pump. Although numerical simulations aid in the evaluation of contact stress, the difficult task of determining geometrical parameters, operating conditions, and the number of simulations to run falls to the designer. This paper presents the Taguchi techniques as an effective simulation-based strategy to narrow down the geometrical parameter combinations, reducing the solution space and optimizing the number of simulations. The work is first focused on the validation of the proposed numerical model by means of published contact stress results of recognized researchers in the field, as well as the unification of nomenclature and notation. Then, the Taguchi approach is based on a sequence of four experiments, ranging from the screening case with two levels and seven parameters to multiple levels and four parameters with three software input operating conditions (temperature, torque,... [more]

As one of the power auxiliary services, peak shaving is the key problem to be solved in the power grid. With the rapid development of DGs, the traditional peak shaving scheduling method for centralized adjustable energy is no longer applicable. Thus, this paper proposes two-layer optimization methods of allocating the peak shaving task for DGs. Layer 1 mainly proposes four evaluation indexes and the peak shaving priority sequence can be obtained with modified TOPSIS, then the DG cluster’s task is allocated to the corresponding DGs. On the basis of dynamic evaluation and the self-renewal mechanism, layer 2 proposes a peak shaving optimization model with dynamic constraints which assigns peak shaving instructions to each cluster. Finally, the effectiveness of the method is verified by using the real DGs data of a regional power grid in China based on the MATLAB simulation platform. The results demonstrate that the proposed methods can simply the calculation complexity by ranking the DGs... [more]

This paper proposes a novel regional carbon emission inequality (RCI) index based on a special kind of general distribution. Using the proposed RCI index and based on China’s county-level panel data over the time span of 1997−2017, the regional carbon emission inequality of China is evaluated at intra-provincial, sub-national, and national levels. Based on that, the dependence between regional carbon inequality and carbon efficiency is studied by using copula functions and nonlinear dependence measures. The empirical results show that: (1) Shanghai, Tianjin, and Inner Mongolia have the worst carbon inequalities; while Hainan, Qinghai, and Jiangxi are the three most carbon-equal provinces; (2) there is a divergence phenomenon in RCI values of municipalities over the past decade; (3) from the national-level perspective, the inter-provincial carbon emission inequality is much greater than that at the intra-provincial level; (4) from the sub-national-level perspective, the east region has... [more]

Since the rules and regulations strongly emphasize environmental preservation and greenhouse gas GHG reduction, researchers have progressively noticed a shift in the transportation means toward electromobility. Several challenges must be resolved to deploy EVs, beginning with improving network accessibility and bidirectional interoperability, reducing the uncertainty related to the availability of suitable charging stations on the trip path and reducing the total service time. Therefore, suggesting DQN supported by AIoT to pair EVs’ requests and station invitations to reduce idle queueing time is crucial for long travel distances. The author has written a proposed methodology in MATLAB to address significant parameters such as the battery charge level, trip distance, nearby charging stations, and average service time. The effectiveness of the proposed methodology is derived from hybridizing the meta-heuristic techniques in searching DQN learning steps to obtain a solution quickly and i... [more]

In recent years, renewable energy has received extensive attention due to its advantages of sustainability, economy, and environmental protection. However, with the rapid development of renewable energy, the problem of curtailment is becoming increasingly serious. Studying the calculation method and establishing a quantitative evaluation system of renewable energy accommodation capacity are important means to solve this problem. This paper comprehensively considers the factors affecting the accommodation of renewable energy, establishes a accommodation calculation model with the maximum accommodation of renewable energy as the optimization target based on the time series production simulation method, and uses the hybrid particle swarm optimization (PSO) algorithm to solve it. The model is verified with historical data such as load, photovoltaic (PV), and wind power in a certain region throughout the year. The experimental results verify the rationality of the renewable-energy accommoda... [more]

Moving towards clean energy generation seems essential. To do so, renewable energy penetration is growing in the power systems. Although energy sources such as wind and solar are clean, they are not available consistently. Using energy storage will help to tackle variability. Liquid air energy storage is gaining attention among different energy storage technologies, as it is a promising option for grid-scale energy storage. This paper presents a detailed mixed integer linear model of liquid air energy storage to be used in scheduling and planning problems. A comprehensive cycle diagram of different processes of liquid air energy storage is presented, and a model has been developed accordingly. Simulations of the proposed model are carried out for the power system of Tenerife island and compared with the basic models. Basic models overlook specific characteristics of liquid air energy storage systems, such as charging and discharging start energy. Results confirm that the use of simple... [more]

The supply chain strategy has a significant impact on energy consumption. This strategy determines the location of individual links in the chain (suppliers, producers, distributors), which affects the costs of logistics processes, including, in particular, transport processes. Currently, due to the rapid increase in fuel prices, the issue of energy consumption in the supply chains is becoming increasingly important. The aim of the article is to present the impact of the increase in fuel and energy costs on the costs of logistics processes and, as a result, on the profitability of different supply chain strategies. The profitability of changing from global to local sources of supply as a result of rising energy prices was especially taken into account. The article presents the results of interviews from enterprises carried out by the authors and the results of simulations carried out using a model developed by the authors. The need to conduct such research resulted from the existing res... [more]

Distributed energy resources (DERs) and demand side management (DSM) strategy implementation in smart grids (SGs) lead to environmental and economic benefits. In this paper, a new DSM strategy is proposed for the day-ahead scheduling problem in SGs with a high penetration of wind energy to optimize the tri-objective problem in SGs: operating cost and pollution emission minimization, the minimization of the cost associated with load curtailment, and the minimization of the deviation between wind turbine (WT) output power and demand. Due to climatic conditions, the nature of the wind energy source is uncertain, and its prediction for day-ahead scheduling is challenging. Monte Carlo simulation (MCS) was used to predict wind energy before integrating with the SG. The DSM strategy used in this study consists of real-time pricing and incentives, which is a hybrid demand response program (H-DRP). To solve the proposed tri-objective SG scheduling problem, an optimization technique, the multi-o... [more]