Robust Operation Method for Renewable‐Integrated Port‐Ship System With Ship‐Participated Grid‐Forming Control

Aiming at the large-scale random power supply being integrated into the power grid, this paper builds an adaptive distributionally robust unit commitment model (ADRUC) to solve the optimal scheduling problem of the power system under uncertain operating conditions. First, the ambiguity set is built based on confidence bands for cumulative distribution function (CDF) from non-parametric statistics, and the interval of acceptable wind power output is obtained, then a polyhedral uncertainty set is constructed considering both the range and temporal domains. Then, in view of the flexibility and economy of fully adjustable robust optimization (FARO), the primal problem is divided into day-ahead UC master problem and the sub-problem of economic dispatch under the worst-case scenario. The strong duality theorem and the Big-M method are employed to transform the sub-problem into a MILP problem, the column and constraint generation (C & CG) algorithm is iterated repeatedly to obtain the target solution. Finally, the ADUC model is analyzed and validated by a ten-machine system.

Integrated Energy Systems (IESs) interconnect various energy networks to achieve coordinated planning and optimized operation among heterogeneous energy subsystems, making them a hot topic in current energy research. However, with the high integration of renewable energy sources, their fluctuation characteristics introduce uncertainties to the entire system, including the corresponding indirect carbon emissions from electricity. To address these issues, this paper constructs a two-stage, three-layer robust optimization operation model for IESs from day-ahead to intra-day. The model analyzes the uncertainties in carbon emission intensity at grid-connected nodes, as well as the uncertainty characteristics of photovoltaic, wind turbine, and cooling, heating, and electricity loads, expressed using polyhedral uncertainty sets. It standardizes the modeling of internal equipment in the IES, introduces carbon emission trading mechanisms, and constructs a low-carbon economic model, transforming the objective function and constraints into a compact form. The column-and-constraint generation algorithm is applied to transform the three-layer model into a single-layer main problem and a two-layer subproblem for iterative solution. The Karush–Kuhn–Tucker (KKT) condition is used to convert the two-layer subproblem into a linear programming model. A case study conducted on a park shows that while the introduction of uncertainty optimization increases system costs and carbon emissions compared to deterministic optimization, the scheduling strategy is more stable, significantly reducing the impact of uncertainties on the system. Moreover, the proposed strategy reduces total costs by 5.03% and carbon emissions by 1.25% compared to scenarios considering only source load uncertainty, fully verifying that the proposed method improves the economic and low-carbon performance of the system.

The modern features of transportation and storage of grain cargoes in conditions of military aggression and changes in transport supply chains is considered in the article. Agriculture is one of the most important sectors of the domestic economy, which provides food not only for our country, but is an important element of global food security. Ukraine is one of the five world leaders in grain exports. Before the war, the total capacity of the country's grain storage facilities was approximately 58 million tons, and during the first six months of the war 15.7 % Ukrainian grain storage facility was destroyed, damaged, or came under the control of the occupiers. The blockade of the Black Sea ports forced farmers to look for new ways to export grain. Unfortunately, neither the western borders nor the Danube ports were unprepared for such a huge cargo flow. The destruction of transport and storage infrastructure requires huge risky investments from farmers, which prompts them to look for new innovative ways of transportation, storage and transshipment of grain cargoes. The emergence of a significant cargo flow of grain cargoes in the Danube region contributed to the transformation of the region from depressed (as it was recently) to attractive for investment. Making huge investments in the construction of new grain terminals turned out to be quite risky, from the point of view of ensuring security and competitive advantages. In this regard, the work considers innovative technologies of transportation, storage and transshipment of grain cargoes using flexible containers, which allow to deliver grain cargoes «door to door» without additional technological operations. A flexible container protects grain cargo from adverse weather conditions, preserves the quality of the cargo, greatly simplifies the transshipment process and is a universal means of transportation by any type of transport.

The strong uncertainty of renewable energy poses significant reliability and safety challenges for the coordinated operation of multi-integrated energy systems (MIES). To address this, a data-driven two-stage distributed robust collaborative optimization scheduling model for MIES is proposed, based on a spatiotemporal fusion conditional diffusion model (STF-CDM). First, to more accurately capture the uncertainty in renewable energy output, the model utilizes a scenario set generated by the STF-CDM model and reduced via the K-means clustering algorithm as the initial renewable energy scenarios for the distributed robust optimization set. The STF-CDM model employs a Temporal module component (TMC) unit composed of Transformer time-series modules and a Spatial module component (SMC) unit composed of CNN neural networks for feature extraction and fusion of time-series and spatial-series data. Second, a benefit allocation method based on multi-energy trading contribution rates is proposed to achieve equitable distribution of cooperative gains. Finally, to protect participant privacy and enhance computational efficiency, an alternating direction multiplier method (ADMM) coupled with parallelizable column and constraint generation (C&CG) is employed to solve the energy trading problem. The case analysis results demonstrate that the STF-CDM model proposed in this study exhibits superior performance in addressing the uncertainty of renewable energy output. Concurrently, the asymmetric Nash game mechanism and the ADMM-C&CG solution algorithm proposed in this study achieve a fair and reasonable distribution of benefits among all participants when handling energy transactions and cooperative gains. This is accomplished while ensuring system robustness, economic efficiency, and privacy.

This study is devoted to modeling economic processes in grain cargo storage and transportation systems using innovative bunker technologies. Based on a comprehensive analysis of statistical data, industry ministry reports, and the results of field experiments from 2020-2023, key trends in the development of agrologistics infrastructure have been identified. Through a comparative analysis of operational costs and environmental indicators of traditional and innovative storage systems, the economic efficiency of implementing new bunker technologies has been substantiated. The results of pilot project testing in 2023 confirm the potential for scaling innovations by reducing grain losses by 1-1.5%, increasing productivity by 15-20%, and shortening investment payback periods to 4-6 years. The study contributes to the development of a methodology for analyzing the economic efficiency of innovations in the agricultural sector and provides practical recommendations for optimizing grain cargo storage and transportation processes.

Seaport Rijeka is the largest seaport in Croatia. It specializes in transport of cargo, with the primary activities of loading, unloading, storage and transport of general cargo, timber, bulk cargo, livestock, containers, and other cargo at five specialized terminals. It is focused on increasing the quality of services and the competitiveness of the transport routes in Croatia. Due to its favourable position on the TEN-T network, Seaport Rijeka provides the shortest maritime connection between the countries of Central and Eastern Europe as well as the overseas countries. In the past 20 years Seaport Rijeka keeps record of continuous growth in container traffic. Due to increasing demand in container traffic, it seeks for the solutions to expand. One of the possible solutions that would satisfy the increasing demand in container traffic is establishing a dry port. Dry port is an inland intermodal terminal which has direct connection to the seaport by road or rail and its main purpose is to provide logistic activities and transport to inland destinations. Dry ports have many advantages, faster transport of cargo from seaports, use of more efficient modes of transport, providing facilities for the storage and consolidation of goods, the maintenance of road or rail freight carriers, customs services, etc. In the case of container transport, dry ports can be used to outsource the logistic activities of transport process, away from congested area of seaports. Due to the fact that Seaport Rijeka is reaching the limits of its capacity, one of possible solutions of its expansion is establishing a dry port. The focus of this paper is to prove that establishing a dry port would speed up the transport process of containers between Seaport Rijeka and its destinations. Due to this hypothesis, four simulations were made. First simulation shows the transport process in the existing set-up of the Seaport Rijeka. Second, third and fourth simulation shows the transport process in the future possible set-up of the Seaport Rijeka with established dry port in Miklavlje, Zagreb or Vinkovci.

To address the increase of wind power uncertain along with wind power capacity, a bi-level robust unit commitment (RUC) model is built to obtain the optimal unit commitment scheme in the worst-case scenario. The objective function considers the start-up/off cost and operation cost of all units. Considering the temporal correlation characteristics of wind power forecast errors, a polyhedral uncertainty set is designed. Conditional Value-at Risk (CVaR) is adopted to describe the risk loss when the real wind power output is beyond the predefined uncertainty set and also determine the interval of acceptable wind power output. In view of the inner and outer layers of model interact with each other, the primal problem is decomposed into day-ahead UC master problem and the sub-problem which considers economic dispatch. In the solving process, the strong duality theorem and the Big-M method are employed to transform the sub-problem with max-min structure into a MILP problem, then the problem is solved by the column and constraint generation (C&CG) algorithm. Finally, the results show the effectiveness of the proposed model.

Chapter 12 - Cool chain and temperature-controlled transport: An overview of concepts, challenges, and technologies

Compared with dry cargo, temperature-sensitive products have some distinctive features which make managing the logistics process much more challenging. The importance of product quality, the need for specific transport fleets, the energy requirements for storage, handling and transportation of perishable cargo are some of these specific characteristics. Meanwhile, as cool chains keep getting longer and more complex, transportation options are also changing right along with it. This chapter provides an overview of different stages of a cool chain and the changes in managing transportation processes in each stage. We also discuss the concepts and technologies to achieve high-quality products as well as the sustainability in the agri-food supply chains.

Risk management provides an effective method for ensuring safety and preventing accidents towards achieving port sustainability. This article describes a study of the implementation of a risk management framework for handling of cargo at ports. To achieve the study’s objectives, data was collected using a questionnaire and disseminated to port experts at three major ports in Malaysia. The collected data were analyzed using the Statistical Package for the Social Sciences (SPSS) software and calculated using risk matrix calculations. Based on the calculations, for port A and port B, 42% of risk falls under risk category II and 58% under risk category III. Meanwhile, for Port C, 31% under risk category II and 69% under risk category III. Risk reduction measures should be implemented within a defined period of time (12 months). Additional risk control measures were proposed accordingly. The novelty of the study was an improvement of risk management framework. The risk management framework was proposed with an introduction of risk frequency into risk rating calculation, risk criteria parameter for risk likelihood and risk severity, new risk matrix dimension and instruments to evaluate the existing control measure factor and new risk categories with five levels which provide more details and sustainable risk assessment method.

Hydraulic gantry cranes (hereinafter referred to as “gantry cranes”) are highly susceptible to instability during dynamic operations due to high-speed unsteady airflow in mountainous and canyon areas, leading to safety risks such as derailment and overturning. Traditional single data-driven or model-driven methods fall short in ensuring real-time performance, accuracy, and comprehensiveness for the safety state perception of gantry cranes during dynamic operations. To overcome this, we draw inspiration from the way biomechanics integrates multiple data sources and models. A digital prototype of the gantry crane was established, mimicking the creation of a virtual model of a biological structure for in-depth analysis. A surrogate model for the dynamic response of the gantry crane under the coupled effects of wind load, lifting load, and self-driving force was constructed. In biomechanics, models are developed to simulate the combined actions of different forces on biological tissues and organs. Here, we approach the gantry crane’s force analysis in a similar fashion, considering the complex interactions of various loads. Based on this, a data model fusion driven method for safety state perception during dynamic operations of gantry cranes was proposed. This method is in line with the practice in biomechanics of integrating experimental data and theoretical models to gain a more complete understanding of biological processes. By fusing data and models, we aim to enhance the safety state perception of gantry cranes, just as biomechanics uses integrated approaches to improve our understanding of biological systems. Simulation results of a 150 t gantry crane at a hydropower station demonstrate the feasibility and practicality of the proposed method. This validation process is comparable to how biomechanical models are tested and verified through experiments on biological specimens or simulations of biological movements, providing evidence for the effectiveness of our approach inspired by biomechanics.

Adaptive robust scheduling of a hydro/photovoltaic/pumped-storage hybrid system in day-ahead electricity and hydrogen markets

Introduction/Background Critical assets are the organizational resources of crucial importance for maintaining operations and achieving the organization's mission. The criticality of organization assets is continuously researched by numerous authors. Ports have critical importance for the global supply chain. Together with the port workforce, port infrastructure, and port superstructure, which are interconnected with the port information system, port machinery enables the functioning of a port. Depending on the characteristics of a port (level of its specialization, etc.), there are various port machinery types used in the cargo handling process, and all of them do not have the same criticality level. In the available literature, no research directly related to the criticality analysis of shore cranes in use at a terminal in a seaport can be found. It was one of the principal initial motives of the author to write this paper. Methodology After an overview of literature sources dealing with assets` criticality analysis and a condensed theoretical consideration of the general importance of ports and port machinery, this paper shows the results of research on the port`s shore cranes‘ criticality ranks, using Analytic Hierarchy Process (AHP) method. The research included a group of shore cranes at the Dry Bulk Cargo Terminal in the Port of Bar JSC (Montenegro), which consists of three gantry cranes (with a capacity per item of 12 t), two mobile harbor cranes with a capacity of 144 t and 124 t and a ship loader for cereals with a capacity of 300 t/h. Criticality analysis was conducted based on four selection criteria: C1-if the shore crane type is an element of cargo handling technology with priority cargo group; C2-level of hourly productivity; C3-level of operating costs; C4-level of cost generated by shore crane downtime during the loading/unloading process. The AHP hierarchy framework used was a three-level model: “level 0” – goal; “level 1” the – criterion; “level 2” the – choice. Results/Discussion According to the calculated level of criticality based on the defined selection criteria, the highest criticality rank was observed for the mobile harbor crane with a capacity of 144 t, which had the highest rank for three out of four selection criteria. Conclusion The results of the research can be used as a base for further research studies in this field as well as a reliable base for a very wide range of managerial activities directed to improvements in the maintenance system of shore cranes as well as in the cargo handling system where the cranes are used. As one of the potential purposes of the results, with a high level of importance, their potential usage for introducing, adequate modeling, and implementing the concept of predictive maintenance of shore cranes (with all related benefits) is pointed out.

The patterns and technological recommendations on the formation of multilayer biological protection for floating objects, performing the function of overload and temporary storage of radioactive cargo of low and intermediate level are discussed. The purpose of the article is development of science-based practical recommendations for the development of protective structures with using of new materials. The mechanism of multiple internal reflection of radiation absorption in a heterogeneous environment is fundamental in the design. This mechanism is created by the introduction of the composite layer of hollow glass microspheres, powders of sodium silicate and plumbiferous glasses. The results are based on established patterns in the interaction of ionizing radiation of cargo with materials of constructions and include the selection of compositions and methods for forming of new materials and coatings on their surfaces. The basis of the design of protective constructions of floating structures is new scientific understanding of the processes and mechanisms of interaction of ionizing radiation of transported cargo with new materials of constructions. The research results can be applied in the design of specialized vessels, floating structures and other equipment for the transport and storage of radioactive cargo.

On the solution of robust transmission expansion planning using duality theorem under polyhedral uncertainty set