Stochastic Approach to Hosting Limit of Transmission System and Improving Method Utilizing HVDC

According to the global de-carbonization trends, renewable energy integration has become an increasingly important issue in power systems. To achieve 100% renewable energy integration and operate a system with these resources, it is necessary to appropriately evaluate the system hosting capability and prepare appropriate planning and operation strategies using the evaluation result. So far, these interests have focused particularly on distribution-level systems. However, although the hosting limit in transmission-level systems requires further consideration, previous study is limited. This study introduces the constraints on the transmission-level hosting limit. In addition, a stochastic estimation of the hosting limit methodology in the transmission system and the use of a high voltage direct current system to improve hosting capacity are proposed and evaluated. Moreover, these methodology-based simulations are conducted using possible scenarios on the IEEE 39 bus system with some constraints, and the simulation results are presented herein. The results showed that the HVDC location selection and operation using the proposed method and optimization technique is appropriate. The strategy can be used to integrate more renewable energy. Furthermore, the proposed methodology can be applied to renewable energy integration scenario establishing a plan.

A New Approach for Spherical Fuzzy TOPSIS and Spherical Fuzzy VIKOR Applied to the Evaluation of Hydrogen Storage Systems

This study proposes a new perspective of the TOPSIS and VIKOR methods using the recently introduced spherical fuzzy sets (SFSs) to handle the vagueness in subjective data and the uncertainties in objective data simultaneously. When implementing these techniques using SFSs, two main problems might arise that can lead to incorrect results. Firstly, the reference points might change with the utilized score function. Secondly, the distance between reference points might not be the largest, as known, among the available ratings. To overcome these deficiencies and increase the robustness of these two methods, they are implemented without utilizing any reference points to minimize the effect of defuzzification and without measuring the distance to eliminate the effect of distance formulas. In the proposed methods, when using an SFS to express the performance of an alternative for a criterion, this SFS per se can be viewed as a measure of proximity to the aspired level. On the other hand, the conjugate of the SFS can be viewed as a measure of proximity to the ineffectual level. Two practical applications are presented to demonstrate the proposed techniques. The first example handles a warehouse location selection problem. The second example evaluates hydrogen storage systems for automobiles with different types of data (crisp, linguistic variables, type 1 fuzzy sets). These data are transformed to SFSs to provide a more comprehensive analysis. A comparative study is conducted with earlier versions of TOPSIS and VIKOR to explicate the adequacy of the proposed methods and the consistency of the results.

Research on Intellectualized Location of Coal Gangue Logistics Nodes Based on Particle Swarm Optimization and Quasi-Newton Algorithm

The optimization of an integrated coal gangue system of mining, dressing, and backfilling in deep underground mining is a multi-objective and complex decision-making process, and the factors such as spatial layout, node location, and transportation equipment need to be considered comprehensively. In order to realize the intellectualized location of the nodes for the logistics and transportation system of underground mining and dressing coal and gangue, this paper establishes the model of the logistics and transportation system of underground mining and dressing coal gangue, and analyzes the key factors of the intellectualized location for the logistics and transportation system of coal and gangue, and the objective function of the node transportation model is deduced. The PSO–QNMs algorithm is proposed for the solution of the objective function, which improves the accuracy and stability of the location selection and effectively avoids the shortcomings of the PSO algorithm with its poor local detailed search ability and the quasi-Newton algorithm with its sensitivity to the initial value. Comparison of the particle swarm and PSO–QNMs algorithm outputs for the specific conditions of the New Julong coal mine, as an example, shows that the PSO–QNMs algorithm reduces the complexity of the calculation, increases the calculation efficiency by eight times, saves 42.8% of the cost value, and improves the efficiency of the node selection of mining–dressing–backfilling systems in a complex underground mining environment. The results confirm that the method has high convergence speed and solution accuracy, and provides a fundamental basis for optimizing the underground coal mine logistics system. Based on the research results, a node siting system for an integrated underground mining, dressing, and backfilling system in coal mines (referred to as MSBPS) was developed.

Rating Risk Factors Related to Dangerous Goods Transportation and Selecting an Ideal Warehouse Location

Considering the environment and human life, the importance of dangerous goods transportation should be carefully considered. Preventing damages during this transportation, anticipating the dangers, and minimizing the risks are vital components for businesses, human life, and the environment. Therefore, reducing/minimizing risks in dangerous goods transportation is a critical element of vital importance. This chapter is aimed to rate the risk factors related to dangerous goods transportation and select the most ideal warehouse locations due to the their importance for human and environmental health. There are a number of factors for that purpose. There are six provinces in the Eastern Black Sea region having the strategic function and structure. According to the decision makers' views and judgments, three provinces are determined in terms of dangerous goods transportation. Picture fuzzy sets-based AHP-TOPSIS methodology was used to analyze the problem of dangerous goods transportation and the most ideal warehouse location selection.

A Methodological Approach to Inner-city Location Selection of Universities

Emerging as urban institutions in the medieval Europe, universities began to offer education in college buildings in the center of the cities where they were originally established. Over time, with the effect of the American campus model, they have become independent settlements that can grow and develop in large areas outside of cities. Today, however, many university campuses are functionally, economically, and socially obsolete and in need of restructuring. This study aims to develop a systematic decision-making process for the evaluation of urban settlement of universities in accordance with some parameters. Thus, based on the national and international research on the location selection of universities, ‘25 subparameters under four main parameter groups affecting the urban location selection’ were identified. The analysis of these parameters was performed by applying the AHP method, the evaluation of alternative decisions was carried out by applying the TOPSIS method, and a decision-making methodology was developed for the location selection of universities within the city. To test this methodology, ‘Selçuk University’ was determined as the sampling site. With the method developed in the study, it was determined that the interaction between the university and the city and the accessibility of the university were critical in the urban settlement of the universities. Although the establishment of a university campus has become easier with the growth and development of higher education today, the fact that universities exist for the society and cannot be isolated from it should not be forgotten. Therefore, the return of the university to the city must be ensured and the university and the city must be reconciliated.

Towards Sustainable Management of Anchoring on Mediterranean Islands—Concession Support Concept

The focus of this paper is to define anchorage management model for concession planning purposes to provide quality support to experts in spatial planning when developing maritime spatial plans. The research aim is to develop an anchorage management model that includes decision and concession support concept. Decision support concept is defined in order to support the processes of identifying potential anchorage locations, their evaluation and comparison, and finally, the priority ranking and selection of locations for their construction. The final step is modelling the concession support concept that includes financial analysis to concession parameters definition. The problem of decision making and concession of the anchorage location selection is complex and ill-structured because of the unsystematic and ad-hoc decisions by all included stakeholders. Additionally, the involvement of several stakeholders’ groups with different preferences and background knowledge, a large amount of conflicting and seemingly incomparable information and data, and numerous conflicting goals and criteria impact final decisions. The proposed concepts overcome the above obstacles in order to enable the construction of anchorages in a way of optimal use of maritime space. The model is tested on the island of Brač, Croatia. The methods used to solve the task are SWARA (The Stepwise Weight Assessment Ratio Analysis) for defining the criteria weights and ELECTRE (Elimination and Choice Expressing Reality) for ranking anchorage locations.

MODAL SOSIAL KELOMPOK TANI BUDI MARGOMULYO II DALAM PEMENUHAN KEBUTUHAN SUMBERDAYA EKONOMI USAHATANI PADI (Studi Kasus Di Desa Pontang Kecamatan Ambulu Kabupaten Jember)

The Budi Margomulyo II Farmer Group is a farmer group located in Pontang Village, Ambulu District, Jember Regency who has problems related to the availability of economic resources in rice farming. This study was aimed to determine existing social capital in the Budi Margomulyo II Farmer Group in meeting economic resources needs in terms of resource components, social structure, and actions at the micro and meso levels. The location selection is determined purposively (purposive method), on the reasoning that there is a good potential in the agricultural sector and that Budi Margomulyo Farmer Group is an active farmer group with various achievements and has succeeded in becoming one of the pioneers in establishing a union. This research is qualitative research with purposive sampling used while choosing the informants. Data analysis of this research employed the Interactive Method of Miles and Huberman. The results showed that the economic resource needs of group members can be met with the existence of social capital in the farmer group both at the micro and meso levels

Efficient Sample Location Selection for Query Zone in Geo-Social Networks

While promoting a business or activity in geo-social networks, the geographical distance between its location and users is critical. Therefore, the problem of Distance-Aware Influence Maximization (DAIM) has been investigated recently. The efficiency of DAIM heavily relies on the sample location selection. Specifically, the online seeding performance is sensitive to the distance between the promoted location and its nearest sample location, and the offline precomputation performance is sensitive to the number of sample locations. However, there is no work to fully study the problem of sample location selection for DAIM in geo-social networks. To do this, we first formalize the problem under a reasonable assumption that a promoted location always adheres to the distribution of users (query zone). Then, we propose two efficient location sampling approaches based on facility location analysis, which is one of the most well-studied areas of operations research, and these two approaches are denoted by Facility Location based Sampling (FLS) and Conditional Facility Location Based Sampling (CFLS), respectively. FLS conducts one-time sample location selection, and CFLS extends the one-time sample location selection to a continuous process, so that an online advertising service can be started immediately without sampling a lot of locations. Our experimental results on two real datasets demonstrate the effectiveness and efficiency of the proposed methods. Specifically, both FLS and CFLS can achieve better performance than the existing sampling methods for the DAIM problem, and CFLS can initialize the online advertising service in a matter of seconds and achieve better objective distance than FLS after sampling a large number of sample locations.