Decision Theory Methods Research Articles

Short-term operation of microgrids with thermal and electrical loads under different uncertainties using information gap decision theory

The utilization of an Energy Management System (EMS) for the optimum scheduling of generation units, as well as demand side resources is essential due to the high penetration of Distributed Energy Resources (DERs) in microgrids (MGs), to achieve the desired objectives. As a result of the restructuring of the power systems and increasing the electricity prices during some periods in a day, demand side programs have been highly valuable by electricity customers. In this paper, a Demand Response (DR) model has been proposed to present the behavior of responsive controllable loads in response to the DR calls. Moreover, optimal scheduling of energy resources is developed for a typical MG by considering the presence of both electrical and thermal demands. Combined Heat and Power (CHP) units, boilers, wind turbines, storage devices, demand response resources (DRRs), as well as the power exchange possibility with the upstream wholesale market are the energy resources that have been considered as the portfolio of the decision maker. Furthermore, the uncertainty resources of the wind speeds and electrical load are handled by the Information Gap Decision Theory (IGDT) method. The performance of the proposed framework is comprehensively analyzed on the IEEE 33-bus test system. The advantage of the proposed methodology under the uncertainty conditions is analyzed by the Monte-Carlo simulation method when the different realization of the wind power and electrical load are considered.

Optimal Operation of Multi-Carrier Energy Networks Considering Uncertain Parameters and Thermal Energy Storage

The coordination of energy carriers in energy systems has significant benefits in enhancing the flexibility, efficiency, and sustainability characteristics of energy networks. These benefits are of great importance for multi-carrier energy networks due to the complexity of obtaining optimal dispatch, considering the non-convex nature of their energy conversion. The current study proposes a robust operation model for the coordination of multi-carrier systems, including electricity, gas, heat, and water carriers concerning thermal energy storage technology. Thermal energy storage is for storing extra heat generated by combined heat and power (CHP) plants and boilers in time intervals with low heat demand on the system and discharging it when required. Energy network operators should have the capability to manage uncertain energy loads to study the impact of load variation on the decision-making process in network operation. Accordingly, this study employs an information gap decision theory (IGDT) method to model the uncertainty of the power demand in optimal system operation. By applying the IGDT approach, the operator of the energy system can use the appropriate methodology to obtain a robust optimal operation. Such a modeling approach helps the operator to make suitable decisions about probable variations in power load. The introduced model is applied in a test system for evaluating the performance and effectiveness of the introduced scheme.

Концепция оптимального освещения и моделирование осветительных систем

The paper aims to determine in the most General form the optimal lighting system of a given object. Optimality of the system is understood as its closest compliance with regulatory requirements in combination with the lowest cost of ownership. The specified task is formalized and as strictly as possible put from the point of view of the system analysis. An algorithm is constructed for modeling and designing an optimal lighting system based on the solution of the problem by the methods of decision theory, as well as using the Digital Twin technology. With the help of the created algorithm, the lighting system of an office space is considered as an example, optimized and compared with the current one, then the economic efficiency of the optimization is considered. Application of results of work is possible at creation of expert systems of design of optimum lighting, the analysis of efficiency of the available lighting systems, and also at design of new lighting systems.

Науково-методичний апарат управління системою геопросторової розвідки із застосуванням системно-когнітивного аналізу

На практиці постійно виникає проблема поєднання даних від різних видів розвідки, щоб отримати максимально повну, точну та достовірну інформацію. Дану проблему вирішує геопросторова розвідка. Це в свою чергу вимагає відповідного рівня автоматизації процесів управління, добування та обробки даних. У статті розроблено науково-методичний апарат з використанням системно-когнітивного аналізу для визначення векторного критерію при розв’язанні задачі стійкого управління, визначення цінності і впливу вхідних параметрів на функціонування та вибору стратегії управління системою геопросторової розвідки.

Methodological approach to digitalization of management processes in automobile and road complex

In order to successfully accomplish the tasks of digitalizing control processes in the road complex integrated into a focused process, new generations of control systems — intelligent control systems – are being actively developed today. Intelligent control systems should be able to independently develop a goal, implement the decision-making process for an action, provide the necessary set of functions to achieve a goal, predict the values of system indicators as a result of actions and compare them with real data, providing feedback in the system and adjusting the control procedure. Currently, the methodological basis for making management decisions in control systems is the concept of scenarios based on the theory of expert assessments. The main disadvantage of this approach is the inability of the system to gradually adapt to changes in input information without completely reworking the structure of the initial requirements. For effective implementation of this task, it is necessary to develop a decision-making methodology in control systems based on formal logical methods of decision theory, namely, analytical methods for obtaining many effective plans, which should allow us to build algorithms that provide optimal solutions when implementing applied management tasks while having minimal information about the conditions of the research object.

ОПТИМИЗАЦИЯ ПРОФИЛАКТИЧЕСКИХ ДОПУСКОВ В СЛОЖНЫХ ТЕХНИЧЕСКИХ СИСТЕМАХ

Currently, monitoring the technical condition of complex technical systems, such as electrical equipment of communication equipment, is a long and non-automated process that is carried out by operators directly at the control objects themselves. This circumstance has a negative impact on the timely detection of failures of the controlled object. One of the most difficult to detect is phasing out. For timely detection of the fact of its occurrence, it is necessary to create a control system that works in a permanent mode with pre-entered preventive tolerances. The purpose of the work is to develop a proposal for the formation of the optimal value of the preventive tolerance of the controlled parameter for detecting the fact of gradual failure and determining its probabilistic characteristics, taking into account the reservation of measurement channels. Methods used: detection of gradual failures is random and the best results are obtained using methods of statistical decision theory, the use of which assumes the presence of complete a priori information about the probability distributions of the output values of the controlled parameters. The novelty of the work is to increase the reliability and accuracy of monitoring the technical condition of complex technical objects to ensure their reliability by reserving measurement channels, which allows you to increase the accuracy of detecting gradual failure of the controlled object by optimizing the value of preventive tolerances. Result: the use of cost-effective redundancy of measurement channels, as well as the use of preventive tolerances, allows more accurate assessment of the technical condition of the control object and make a conclusion about the probability of gradual failure. Optimization of the threshold of preventive admission allows you to minimize the probability of making an erroneous decision. Practical significance: the results of the work can be used in the process of monitoring the technical condition of complex technical systems, which will avoid accidents.

Application of organizational and technological modeling approaches in the construction of buildings with green roofs

The predominance of green spaces on the coatings of buildings and structures contributes to the formation and development of a new urban space, improves the environment, reducing greenhouse gas emissions into the atmosphere. The aim of the research is to study the various types of greening systems form a variable base of organizational and technological modelling, which allow to adopt the rational organizational and technological decisions in the construction. The research methodology and research methods are based on the theory and practice of constructing organizational and technological models and methods of rational planning in construction, decision theory, expert assessments, and comparison methods. As the results of streamlining the technological processes and operations of the roofing device with modular greening systems, the organizational and technological sequence of the roofing device with the modular greening system is formed. Application of the approaches of organizational-technological modeling in the construction of buildings with green roofs will allow verification with a limited set of experimental data.

Some Aspects of Systems’ Development of Tourist Routes Formation and Optimization

The purpose of the article is to investigate and consider common problems of automation and informatization of activities in the tourism sphere, review and describe the author’s information system for the generation, formation and optimization of tourist routes.Research methods are methods of decision theory, methods of optimization, methods of semantic analysis of the subject area’s basic concepts (tourism sphere). The article deals with the approaches to the generation and formation of optimal tourist routes, implemented in the corresponding author’s system.The novelty of the research is the approaches proposed by the authors to formulate optimal tourist routes, which are based on minimizing parameters (such as risks and costs of tourism enterprises and their clients) and maximizing parameters due to customer requirements (such as route comfort, number of tourist sites). These approaches are implemented in the author’s system of formation and optimization of tourist routes. The proposed approach provides a new level of efficiency in tourism.The conclusion of the research conducted in the article is that the formation and optimization of tourist routes using the author’s information system helps to reduce risks and additional costs for both tourist enterprises and their customers. Therefore, the search for ways of information and technological support for the processes occurring in the tourism sector (in the form of an author’s information system) is an important factor in ensuring the efficient formation of optimal tourist routes.

DER Aggregator’s Data-Driven Bidding Strategy Using the Information Gap Decision Theory in a Non-Cooperative Electricity Market

When multiple distributed energy resource (DER) aggregators exist in a non-cooperative power market, the calculation of individual aggregator’s bidding strategies could encounter significant uncertainties for considering DERs and competing market participants’ bidding strategies. In this paper, a bi-level bidding strategy optimization model is proposed for a DER aggregator which utilizes wind power, energy storage system (ESS), and curtailable load. At the upper level, the designated aggregator’s bidding strategy is optimized considering the wind power uncertainty. The wind forecast error is modeled by an ambiguity set using the data-driven approach. The information gap decision theory (IGDT) method is employed in this paper to maximize the risk level the designated aggregator can bear for a certain level of expected payoff. By detecting the worst case in wind power generation, the upper-level model is linearized as an MILP. The designated aggregator submits its bids to the market using the linear utility function acquired from linear regression. At the lower level, the market clearing is carried out using competing market participants’ bidding strategy scenarios. The scenarios and the corresponding probability are modeled through a data-driven approach. The market clearing problem is linearized using Taylor series. The price signal is iterated between the two levels as the proposed bi-level model is solved. Numerical results prove the validity and effectiveness of the proposed IGDT-based method. It is shown that the aggregator can adjust either the bidding quantities or coefficients to reach an expected payoff level. The bidding strategies are affected by uncertainties of wind power and competing bidding strategies. For an expected payoff level, when the designated aggregator is posed to consider a higher risk of wind power uncertainty, the aggregator can only bear a lower risk level from competing bidding strategies and vice versa.

A survey of decision making and optimization under uncertainty

Recent advances in decision making have incorporated both risk and ambiguity in decision theory and optimization methods. These methods implement a variety of uncertainty representations from probabilistic and non-probabilistic foundations, including traditional probability theory, sets of probability measures, uncertainty sets, ambiguity sets, possibility theory, evidence theory, fuzzy measures, and imprecise probability. The choice of uncertainty representation impacts the expressiveness and tractability of the decision models. We survey recent approaches for representing uncertainty in both decision making and optimization to clarify the trade-offs among the alternative representations. Robust and distributionally robust optimization are surveyed, with particular attention to standard form ambiguity sets. Applications of uncertainty and decision models are also reviewed, with a focus on recent optimization applications. These applications highlight common practices and potential research gaps. The intersection of behavioral decision making and robust optimization is a promising area for future research and there is also opportunity for further advances in distributionally robust optimization in sequential and multi-agent settings.

Application of decision theory and bee-inspired method to railway system route optimization

ABSTRACTRoute planning for multiple destinations via a railway system (RS) is challenging, especially in a complex network with hundreds of stations and interchanges, resulting in a railway traveling salesman problem (RTSP), which is a variant of the traveling salesman problem (TSP). Limited attention has been devoted to solving the RTSP, despite the increase in the number of people using RSs and the added complexity of network expansions. An optimization algorithm and mathematical model based on the foraging behavior of bees and decision theory were used in this paper to identify the optimum RS route to multiple destinations before returning to the first station. Data collected from RSs in Japan and Malaysia were used to create 200 test cases (100 cases with each dataset), and the results were compared to specific solutions and the official optimum route planner to prove that the model is a promising approximation method. The solutions were evaluated and verified by comparing results from another 200 brute-force cases generated by the Wiley TSP Solver. The results obtained from the experiments prove the reliability and capability of the route planning and optimization solutions for RSs with different complexities and in different environments without the assistance of information technology.

A Review of Case-Based Decision Theory

Case-Based Decision Theory (CBDT) is a method that achieves the tasks of making decisions by imitating the thinking mode of human beings and achieving relatively satisfying decisions with extremely limited information. It is one of the most representative methods of behavioral decision theory. In order to sort out CBDT systematically, this thesis presents the CBDT model and its evolution systematically, and perfectly reveals the current application fields of CBDT. This thesis also proposes the application prospect of CBDT in the field of venture capital on the basis of summarizing the current evaluation methods of venture capital projects.

Integration of Smart Energy Hubs in Distribution Networks Under Uncertainties and Demand Response Concept

Multienergy systems are flexible energy systems that can benefit from energy resources to supply different energy demands. Due to the capabilities of multienergy systems in generating different energy carriers, these systems have been rapidly expanded in power systems. After restructuring in power system in recent years and appearance of competent energy markets, energy systems operated within such environments have been usually exposed to uncertainties of various parameters, such as price, demand, etc. In this paper, a novel optimization framework based on hybrid scenario-based/interval/information gap decision theory method is developed to investigate the optimal operation of smart energy hubs (S. E. Hubs) subject to economic priorities, technical constraints of the distribution network and uncertainties. Considering energy hubs equipped to smart facilities, demand-side management programs including price response and load response services have been available to motivate electrical consumers to revise their consumption pattern in order to satisfy economic priorities of energy hubs. By using the results of employed hybrid uncertainty modeling approach, the operator of S. E. Hubs can decide either to take risk-averse or risk-seeking strategy against the uncertainties. Uncertainty based integration of S. E. Hubs into distribution network is evaluated regarding the IEEE 33-bus test system and the results obtained from simulations are presented for comparison.

TO THE QUESTION ABOUT THE ASSESSMENT OF THE CONSTRUCTION OF RAILWAY STATIONS

The purpose of the work is to develop methods for the integrated assessment of design options for railroad track development and their comparative analysis to select the most rational design solution based on modern mathematical methods. Methodology. To solve the problem, the methods of statistical analysis, graph theory and decision theory are used. Findings. The constructive characteristics and quality indicators of various schemes of the station track development were obtained. As a result of a comparative analysis of the considered variants of design decisions, their numerical estimates (priorities) were determined, on the basis of which the most rational scheme of track development of the railway station was chosen. The originality lies in the fact that the procedure for choosing a rational scheme for the track development of a railway station from a variety of options is formalized as a multi-criteria task, for solving which the hierarchy analysis method is used. The practical value of the presented methodology will allow expanding the range of considered competitive options for railroad track development schemes and increasing the objectivity of their comparative analysis not only taking into account design features, but also taking into account quality indicators.

Multi-Objective Optimization of Resilient Design of the Multipurpose Reservoir in Conditions of Uncertain Climate Change

This paper presents and assesses a new approach to decision-making methods for the design of new reservoirs due in times of decreasing water resources. The methods used in this case are decision theory, Resilience and Robustness method. The methods have been selected primarily to analyze different design parameters of a new dam, mainly dam heights leading to different reservoir volumes. The study presents a novel approach to the optimal design of a multipurpose reservoir that would provide enough water for downstream environmental flow, residential and industrial water supply, agricultural water supply, and hydropower generation in the current conditions of climate uncertainty. Uncertainties are interpreted as possible future changes in the climate system using outputs from regional climatic models. In the case study, a simulation model was developed which is able to quantify long-term water balance and use this data to quantify resilience and robustness of its water supply. The simulation model was correlated to the GANetXL software in order to perform Genetic Algorithms based optimization of the reservoir’s operation. The simulation–optimization model was then applied to a real-life case study in the Czech Republic, in the Morava River Basin where a new dam with the multipurpose reservoir is planned to be built in the future. The results obtained in this way were analyzed in detail to identify the overall best solution consist of dam height and the total reservoir monthly outflow and new operational rules for the analyzed multipurpose reservoir.

Comprehensive Assessment of Highway Construction Based on Extension Engineering Method

The extension engineering method is introduced in detail. Comprehensive assessment indexes for highway construction are established by means of extension decision theory and main item analysis method. With a project as an example, application of extension engineering method to comprehensive evaluation of highway construction is discussed. It is showed that the present method is reasonable and has vastly applicable prospect compared with other methods.

Information gap decision theory to deal with long-term wind energy planning considering voltage stability

This paper proposes a novel approach for long-term planning of wind energy considering its inherent uncertainty. The uncertainty of wind energy is handled via information gap decision theory (IGDT) method. Additionally, due to the importance of security considerations, loading margin is employed as an index of voltage stability to guarantee the security of power system. The operational constraints (such as power flow equations) in initial operation point considered along with those at the voltage collapse point, simultaneously. Accordingly, the IGDT-based voltage stability constrained wind energy-planning model is proposed that can be used for ensuring the safe operation of power networks. The main feature of this model is to handle the uncertainty of wind energy in the long-term wind energy planning via IGDT technique, by considering voltage stability constraints. In order to evaluate the capability of the IGDT technique for uncertainty handling of wind energy, the obtained results are compared with Monte Carlo simulations. To demonstrate the effectiveness of proposed model, it is applied to the New-England 39-bus test system. The obtained results validated the applicability of the proposed model for optimal wind energy planning. The proposed methodology could help wind farm investors to make optimal large-scale wind energy investment decisions.

INCREASING THE EFFECTIVENESS OF THE UNIVERSITY BASED ON ECONOMIC MODELING

The article is the research paper, with case elements and illustration of specific calculations based on the developed model using the data of a pilot university. Its goal is to form a model for decision support system for the effective use of the institution’s property, investigate the model for specific university’s data and propose recommendations for improving the effectiveness of the university as a whole. The problem of analyzing the budget sufficiency for maintaining the university’s assets and ensuring its current activities is examined in the paper, as well as the opportunity of increasing the efficiency of the use of property. The model is proposed for decision support system for the property of the institution. This model is formed from several submodels: «educational activity», «scientific activity», «living activity», «expenses», «development of the property», and «budget». The model can be used for simulation «what if» analysis of different scenarios of the external and internal parameters (in particular, to estimate the achievement of the strategic goals of the university) and forecasting the results of activities. The methodological basis of the research included general scientific methods, such as analysis and synthesis, modeling and classification, as well as methods of decision theory. Simulation calculations allow us to identify the most significant factors in the impact on the financial result of the university. In particular, for the scenario of high degree of occupancy of premises, the growth in the number of students (admission control indicators) requires the construction of new buildings under current operating conditions and is possible only with the support of the state. The scenario of increasing the efficiency of the use of property makes it possible to achieve the growth of the target indicators of the university without additional investments from the state. For the scenario of a decrease in the contingent of students, the model allows the estimation of the necessary amount of optimization of the specific economic parameters for the formation of a no-deficit budget. The complex covers the educational and scientific activities of the university, the formation of a timetable for students and the occupancy of audiences, maintenance of rooms and hostels, as well as the budget of the university making the developed model new. It is expected that this approach is applicable for different institutions of higher education. The application of the model for the conditions of specific universities will allow their management to set the parameters for the development of the university for the goal-targeted approach for the development. In the future, researchers can develop the model under detailed empirical data, taking into account the variety of internal and external factors. The results of this study van be of practical importance for vice-rectors on economics, administrative affairs, heads of financial and economic departments as well as university executives responsible for taking decisions on strategy development in the context of limited budget taking into account risks.

Optimal Robust Unit Commitment of CHP Plants in Electricity Markets Using Information Gap Decision Theory

This paper proposes a novel method based on information gap decision theory to evaluate a profitable operation strategy for combined heat and power units in a liberalized electricity market. Risk levels can be assessed using this technique, taking into consideration whether the generation company is either risk-taking or risk averse. The test system used in this paper comprises conventional thermal, cogeneration, and heat-only units. The pool price is considered to be uncertain while an information gap decision theory method is employed to model its volatility around the estimated value. Profits lower than the expected value are optimized using the proposed method and the related strategy is determined. The presented method optimizes the opportunities to make use of high profits or high pool prices. To verify the performance of the proposed method, the model has been implemented on a case study.

The Permanent Residential Housing: Geographic Information System-Based Evaluation Considering the Legislation

The paper deals with the conception of multi-criteria analysis geographic information system (GIS). The set of criteria has great influence on the whole project in GIS. This fact is described in chapter “materials and methods” where a new model is discussed. In these model is included influence of legislative which restrict the set of criteria. The selected criteria have also determine the input dataset. It leads to proper and optimal selecting of set of input data in GIS. The advantage is the optimization of input data and selects the best variant in combination with strategies in spatial decision making. The article proposes the evaluation process which is user oriented and consists of several multi-criteria methods. In this paper the authors proposed a mathematical model which includes input data containing hypothesis of the stakeholders (input criteria) and output data representing proposed variants for different solutions. Experimental results are focused on GIS based evaluation of permanent residential housing. As main method of multi-criterial analysis is used sensitive analysis. A team of experts and stakeholders sett importance of the various criteria and thus determine the values of weights for their quantification. These parameters are determined in the model as the main criteria for strategic planning in the real estate engineering. The weights are also numerically quantified using different methods of decision theory. Selected and restricted criteria (by legislative) determine the set of spatial analytical functions. Spatial analyses create an important part of this method. Spatial analyses serve as an attractive cartographic presentation of the project to users appearing in the real estate market using static and of interactive maps. Graphically and numerically multi-criteria analyses are presented as the final result which report analyzing the effectiveness of various factors. These factors affect the real estate market and the price of real estate. From an economic point of view, it is possible to determine these factors by the supply and demand for a particular type of property. The proposed method is a new approach to comprehensive evaluation criteria for the purposes of the real estate market. The existing MCDA methods are integrated into one unit and evaluated through an optimal variant.