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]

Security constrained unit commitment is an essential part of the day-ahead energy markets. The presence of discrete and continuous variables makes it a complex, mixed-integer, and time-hungry optimization problem. Grid operators solve unit commitment problems multiple times daily with only minor changes in the operating conditions. Solving a large-scale unit commitment problem requires considerable computational effort and a reasonable time. However, the solution time can be improved by exploiting the fact that the operating conditions do not change significantly in the day-ahead market clearing. Therefore, in this paper, a novel multi-layer data-driven approach is proposed, which significantly improves the solution time (90% time-reduction on average for the three studied systems). The proposed approach not only provides a near-optimal solution (<1% optimality gap) but also ensures that it is feasible for the stable operation of the system (0% infeasible predicted solutions). The e... [more]

The European Commission introduced a package of measures to accelerate the shift to low-carbon energy transition in Europe. In 2014, EU member states agreed to reduce greenhouse gas emissions by at least 40% by 2030 compared to 1990 levels. The binding greenhouse gas emission targets for Member States from 2021 to 2030 for the transport, buildings, agriculture, waste, and land-use and forestry sectors were established. EU Member States should decide on their own how to meet the agreed upon 2030 target and implement climate-change-mitigation measures. All EU MSs have committed to prepare national energy and climate plans based on regulation on the governance of the energy union and climate action (EU)2018/1999, agreed as part of the Clean Energy for All Europeans package approved in 2019. The national plans outline how the EU Member States intend to implement the GHG reduction target by increasing their in energy efficiency, use of renewables, greenhouse-gas-emission reductions, interco... [more]

Distributed energy systems (DES) are currently at the forefront of the energy transition. Their placement brings production closer to the demand side of urban and sub-urban environments, making optimal design a necessity. However, the complexity of accurately addressing the energy demands via DES has received increasing research attention. This is mainly due to the impact they have on the energy transition’s socioeconomic aspect, as these systems are far from viable in most cases, especially when cutting-edge renewable technologies are involved. The current study aims to provide a practical and non-repetitive approach to DES design, explicitly referring to thermal distributed supply systems (TDESS). The authors present the last two of their three-layer Hierarchically Dependent Layering Methodology (HDLM) approach in designing a thermal local energy community (TLEC) from the ground up. The 2nd layer is the superstructure design of the TLEC, where a map approach is introduced and explore... [more]

Increasing distributed generations (DGs) are integrated into the distribution network. The risk of not satisfying operation constraints caused by the uncertainty of renewable energy output is increasing. The energy storage (ES) could stabilize the fluctuation of renewable energy generation output. Therefore, it can promote the consumption of renewable energy. A distributed photovoltaic (PV) and ES optimal allocation method based on the security region is proposed. Firstly, a bi-level optimal allocation model of PV and ES is established. The outer layer is a nonlinear optimization model, taking the maximum power supply benefit as the objective function. The inner layer is a day-ahead economic dispatching model. Then, a quick model solving method based on the steady-state security region is proposed. An initial allocation scheme of PV and ES is determined with the redundancy capacity. In addition, the linear hyperplane coefficient of the security region is used to convert the nonlinear d... [more]

Multi-criteria decision analyses (MCDAs) have been developed to support and evaluate decision-making on multi-layered problems. The benefit lies in creating transparency, among other benefits, especially in tackling divergent stakeholder interests. Within the energy transition, area shortage can lead to sustainability trade-offs, calling for the reconciliation of planning processes and satisfactory compromises. While ex ante MCDAs complement planning, the ex post consideration of processes has been less widely studied. Using a case study of offshore wind energy (OWP) within German marine spatial planning, we investigated the shifting weights of sustainability criteria and stakeholder interests. A multi-criteria approach (Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE)) addressed how decision-making can be iteratively traced, and the winners and losers indicated in sustainability dilemmas, such as between climate and biodiversity implications. Findings i... [more]

The large-scale integration of variable renewable energy sources into the energy system presents techno−economic challenges. Long−term energy system optimization models fail to adequately capture these challenges because of the low temporal resolution of these tools. This limitation has often been addressed either by direct improvements within the long−term models or by coupling them to higher resolution power system models. In this study, a combined approach is proposed to capitalize on the advantages and overcome the disadvantages of both methods. First, the temporal resolution of an energy model was enhanced by approximating the joint probability of the electricity load and the supply of intermittent sources. Second, the projected electricity mix was simulated by a power model at an hourly resolution. This framework was used to analyze mid−century deep decarbonization trajectories for Colombia, subject to future uncertainties of hydroclimatic variability and the development of the b... [more]

There are two situations of transmission redundancy and transmission congestion when large-scale offshore wind farms send power out. The energy storage system can store the power blocked by wind power due to insufficient transmission capacity and release it in the period when the wind power output level is low. In this paper, a full-life-cycle cost model is established for energy storage, and a joint planning model for offshore wind power storage and transmission considering carbon emission reduction benefits is established, which integrates power grid transmission benefits, carbon emission reduction benefits, energy storage construction costs, transmission project construction costs and wind abandonment penalty costs. The channel construction and energy storage configuration scheme with the greatest net benefit can be obtained. The relationship between the transmission channel capacity setting and the energy storage parameter configuration under this model is studied, and the combined... [more]

The integrated scheduling problem in automated storage and retrieval systems (AS/RS) and the hybrid flowshop is critical for the realization of lean logistics and just-in-time distribution in manufacturing systems. The bi-objective model that minimizes the operation time in AS/RS and the makespan in the hybrid flowshop is established to optimize the problem. A mixed algorithm, named GA-MBO algorithm, is proposed to solve the model, which combines the advantages of the strong global optimization ability of genetic algorithm (GA) and the strong local search ability of migratory birds optimization (MBO). To avoid useless solutions, different cross operations of storage and retrieval tasks are designed. Compared with three algorithms, including improved genetic algorithm, improved particle swam optimization, and a hybrid algorithm of GA and particle swam optimization, the experimental results showed that the GA-MBO algorithm improves the operation efficiency by 9.48%, 19.54%, and 5.12% and... [more]

For decision-making and governance, smart cities depend on tracking data collected via a substantial percentage of wireless sensing nodes. However, several limitations affect Wireless Sensor Network (WSN)-based Internet of Things (IoT) services, such as low battery life, recurrent connectivity problems due to multi-hop connections, and a limited channel capacity. Furthermore, in many systems, clustering and routing are handled independently, which prevents the adaptation of effective strategies for optimal energy usage and prolonged network lifespan. This research gathers data from heterogeneous IoT nodes linked via WSN and distributed across a smart infrastructure. There are two interrelated problems to be addressed with respect to energy efficiency computations: clustering and routing. We provide a new clustering strategy through which efficient routing of critical and regular data is handled. As a result, both clustering and routing have been significantly strengthened, which balanc... [more]

Microgrids using renewable energy sources play an important role in providing universal electricity access in rural areas in the Global South. Current methods of system dimensioning rely on stochastic load profile modeling, which has limitations in microgrids with industrial consumers due to high demand side uncertainties. In this paper, we propose an alternative approach considering demand side management during system design which we implemented using a genetic scheduling algorithm. The developed method is applied to a test case system on Idjwi Island, Democratic Republic of the Congo (DRC), which is to be powered by a micro hydropower plant (MHP) in combination with a photovoltaic (PV) system and a battery energy storage system (BESS). The results show that the increased flexibility of industrial consumers can significantly reduce the cost of electricity. Most importantly, the presented method quantifies the trade-off between electricity cost and consumer flexibility. This gives loc... [more]

Keeping the global temperature rise below 2 degrees Celsius, as foreseen by the Paris Agreement, requires a new global roadmap for the energy transition. For this reason, the European Commission decided to directly involve local municipalities in reaching these objectives through multilevel, bottom-up actions for sustainable energy. The Covenant of Mayors is a very concrete demonstration of this trend of development and adoption of sustainable energy action plans (SEAP), rethinking the way cities operate and bringing them closer to energy self-sufficiency, with measures favouring local economic development and improving citizens’ quality of life. The numerous RES/RUE actions included in SEAPs at the regional level have led both to the request for huge funding and to increased complexity for regional managers to identify the best projects to be financed. To manage the multitude of data (emissions, energy consumption, cost, etc.) present in the SEAPs at a regional level, a web-based plat... [more]

The Kingdom of Saudi Arabia (KSA) has an ambitious plan to install 40 GW of solar photovoltaic (PV) capacity via large scale projects (majority of which are >100 MW) across the country by 2030. These projects are required to achieve a threshold percentage of the overall project cost as in country expenditure, termed “local content”. This threshold will rise to 40−45% by 2028, ensuring solar projects do not simply become investment opportunities for overseas companies but deliver jobs and skills development within the Kingdom. Local content is assessed across all aspects of a PV system—module, inverter, structure, etc. Typically, the PV module cost can range between ~34% to ~44% of the overall system cost. However, 56% of this module cost represents the manufacture of the solar cells. To maximise local content, the opportunity for KSA lies in module fabrication of imported solar cells. This study assesses the capacity readiness of the KSA to meet this opportunity in relation to its 2030... [more]

Optimal power flow (OPF) represents one of the most important issues in the electrical power system for energy management, planning, and operation via finding optimal control variables with satisfying the equality and inequality constraints. Several optimization methods have been proposed to solve OPF problems, but there is still a need to achieve optimum performance. A Slime Mould Algorithm (SMA) is one of the new stochastic optimization methods inspired by the behaviour of the oscillation mode of slime mould in nature. The proposed algorithm is characterized as easy, simple, efficient, avoiding stagnation in the local optima and moving toward the optimal solution. Different frameworks have been applied to achieve single and conflicting multi-objective functions simultaneously (Bi, Tri, Quad, and Quinta objective functions) for solving OPF problems. These objective functions are total fuel cost of generation units, real power loss on transmission lines, total emission issued by fossil... [more]

This article deals with the issue of human capital as a factor responsible for the emergence of development inequalities in rural areas. Its main goal is to analyze and evaluate the existing differences in the distribution of human capital resources in rural areas in Poland in relation to their socio-economic situation. The essence of human capital is expressed through the analogy of energy and capital in relation to the concept of homo energeticus. The essence of human capital is also expressed in terms of two components of its structure, i.e., health and the labor market. The level of human capital was expressed using two synthetic measures, i.e., the human capital ratio in the field of health (HCH) and the labor market (HCLM). The obtained research results indicate the existing differences in the spatial distribution of human capital, resulting in a polarization effect in the center-periphery system, and showing relations with the socio-economic structure of rural areas, their agric... [more]