Modeling of Electrical Grid Systems to Evaluate Sustainable Electricity Generation in Pakistan

Pakistan has always had a history of severe energy shortfalls, which rose up to an alarming 33% in 2013. This situation was countered by investments in the energy sector through the China Pakistan Economic Corridor (CPEC), which were unfortunately largely based on brown fuels. Although beneficial in the short term, these investments do not bode well for the climate scenario of Pakistan, with various parts of the country already having experienced temperatures rise of 1-3°C. To ensure that the current situation doesn’t exacerbate and is tackled in a timely manner, this research aims to examine how the untapped potential of renewable energy in Pakistan can be better utilized by modelling the entire electrical grid system for multi-portfolio based sustainable electricity generation, in line with the sustainable development goals chalked out by Pakistan with the United Nations (UN). Delving further into the matter, a gap is observed that demands coalescence between sustainability and portfolio-based generation in the context of Pakistan, since the prevalent narrative is of Business As Usual (BAU). The research methodology implemented is a cross sectional case study employing qualitative and quantitative data collection methods and outcomes, in which the entire grid system of Pakistan is studied and sustainability metrics are defined; followed by a comprehensive use of Multi-Criteria Decision Methodology in decision making process. Portfolios defined are a combination of different generation technologies, each simulating a possible avenue of policy, and are then evaluated for a range of sustainability metrics to understand the tradeoffs involved to arrive at a set goal. The process decision framework developed shall enable the Pakistani energy sector in meeting the energy demands by providing the decision-makers with various routes to do so, while informing on the sustainability impact of their decisions

A taxonomy for emergency service station location problem

The emergency service station (ESS) location problem has been widely studied in the literature since 1970s. There has been a growing interest in the subject especially after 1990s. Various models with different objective functions and constraints have been proposed in the academic literature and efficient solution techniques have been developed to provide good solutions in reasonable times. However, there is not any study that systematically classifies different problem types and methodologies to address them. This paper presents a taxonomic framework for the ESS location problem using an operations research perspective. In this framework, we basically consider the type of the emergency, the objective function, constraints, model assumptions, modeling, and solution techniques. We also analyze a variety of papers related to the literature in order to demonstrate the effectiveness of the taxonomy and to get insights for possible research directions

Applications of gravitational search algorithm in engineering

Gravitational search algorithm (GSA) is a nature-inspired conceptual framework with roots in gravitational kinematics, a branch of physics that models the motion of masses moving under the influence of gravity. In a recent article the authors reviewed the principles of GSA. This article presents a review of applications of GSA in engineering including combinatorial optimization problems, economic load dispatch problem, economic and emission dispatch problem, optimal power flow problem, optimal reactive power dispatch problem, energy management system problem, clustering and classification problem, feature subset selection problem, parameter identification, training neural networks, traveling salesman problem, filter design and communication systems, unit commitment problem and multiobjective optimization problems

Sustainability as a Multi-criteria Concept

Sustainability is a fairly old concept, born in the 18th century in the field of forestry, within a mono-functionality perspective. The concept has considerably evolved in the last few years towards a multi-functionality context, with applications reported in practically all areas of economic interest. On the other hand, modern sustainability is a complex problem, for two reasons: a) The multiplicity of functions of a very different nature involved in the process and b) The manner in which different segments of the society or stakeholders perceive the relative importance of these functions. For the above reasons, a realistic approach for dealing with the sustainability issue requires taking into consideration multiple criteria of different nature (economic, environmental and social), and in many cases within a participatory decision making framework. This book presents a collection of papers, dealing with different theoretical and applied issues of sustainability, with the help of a modern multi-criteria decision-making theory, with a single as well as several stakeholders involved in the decision-making process. Hopefully, this material will encourage academics and practitioners to alter their research in this hot and vital topic. After all, the sustainable management of the environment and its embedded resources is one of the most important, if not the major challenge of the 21st century

Multi-Objective Dynamic Economic Dispatch with Demand Side Management of Residential Loads and Electric Vehicles

In this paper, a multi-objective optimization method based on the normal boundary intersection is proposed to solve the dynamic economic dispatch with demand side management of individual residential loads and electric vehicles. The proposed approach specifically addresses consumer comfort through acceptable appliance deferral times and electric vehicle charging requirements. The multi-objectives of minimizing generation costs, emissions, and energy loss in the system are balanced in a Pareto front approach in which a fuzzy decision making method has been implemented to find the best compromise solution based on desired system operating conditions. The normal boundary intersection method is described and validated

Collaborative planning in non-hierarchical networks - an intelligent negotiation-based framework

In today’s competing business market, companies are constantly challenged to dynamically adapt to customer expectations by diminishing the time response that goes from the beginning of the business opportunity to the satisfaction of the customer need. Simultaneously, there is increased recognition of the advantages that companies obtain in focusing on their core business and seeking other competencies through partnerships with other partners by forming collaborative networks. These new collaborative organizational structures require a new set of methods and tools to support the management of manufacturing processes across the entire supply chain. The present paper addresses the collaborative production planning problem in networks of non-hierarchical, decentralized, and independent companies. By proposing a collaborative planning intelligent framework composed of a web-based set of methods, tools, and technologies, the present study intends to provide network stakeholders with the necessary means to responsively and efficiently address each one of the market business opportunities. Through this new holistic framework, the managers of the networked companies can address the challenges posed during collaborative network formation and supply chain production planning.The research leading to these results received funding from the European Union’s Seventh Framework Program (FP7/2007-2013) under grant agreement No. 260169. This work was also financed by national funds through the Portuguese funding agency, FCT—Fundação para a Ciência e a Tecnologia, within project LA/P/0063/2020

Multicriteria power engineering problems and fuzzy set based methods of their solution

The results of research into the use of models and methods of multicriteria decision making in a fuzzy environment for solving power engineering problems are presented. Two general classes of models related to multiobjective ( models) and multiattribute ( models) problems as well as methods of their analysis based on the application of the Bellman-Zadeh approach to decision making in a fuzzy environment and techniques of fuzzy preference modeling, respectively, are briefly considered. A review of the authors’ results associated with the application of these models and methods for solving diverse types of problems of power system and subsystems planning, operation, and control is presented. The recent results on the use of and models and methods of their analysis for the allocation of reactive power sources in distribution systems and for the prioritization in maintenance planning in distribution systems, respectively, are considered.Наведено результати щодо досліджень використання моделей та методів багатокритеріального прийняття рішень в нечіткому середовищі при розв'язанні задач електроенергетичного спрямування. Розглянуто два класи моделей, які належать до багатоцільових ( модель) та багатоатрибутних ( модель) задач, а також методи їхнього аналізу, що засновані як на використанні підхода Беллмана-Заде до прийняття рішень у нечіткому середовищі, так і на техніці, пов'язаній з визначенням нечітких переваг. Представлено огляд результатів, які отримано авторами при використанні вказаних моделей та методів для вирішення задач проектування та управління роботою енергетичних систем і підсистем. Останні результати, пов'язані з використанням і моделей та методів їхнього аналізу, належать до задач роз- поділу джерел реактивної потужності у розподільних мережах та визначення пріоритетів при плануванні їхнього обслуговування.Представлены результаты исследований по использованию моделей и методов многокритериального принятия решений в нечеткой среде при решении задач электроэнергетического характера. При этом рассматривается два класса моделей, относящихся к многоцелевым (модель) и многоатрибутным (модель) задачам, а также методы их анализа, основанные как на использовании подхода Беллмана-Заде к принятию решений в нечеткой среде, так и технике, связанной с определением нечетких предпочтений. Представлен обзор результатов, полученных авторами при использовании указанных моделей и методов для решения различных задач, связанных с проектированием и управлением работой энергетических систем и подсистем. Последние результаты, связанные с применением и моделей и методов их анализа, относятся к задачам распределения источников реактивной мощности в распределительных сетях и определения приоритетов при планировании их обслуживания

Application of Multicriteria Decision-Making Methods in Railway Engineering: A Case Study of Train Control Information Systems (TCIS)

In order to improve its position in the transport market railway, as a complex system, it has to fulfill a number of objectives such as increased capacity and asset utilization, improved reliability and safety, higher customer service levels, better energy efficiency and fewer emissions, along with increased economic viability and profits. Some of these objectives call for the implementation of maximum values, while some of them require minimum values. Additionally, some can be expressed quantitatively, while some, for example, customer service, can be described qualitatively through a descriptive scale of points. The application of MCDM in railway engineering can play a significant role. Therefore, the major objective of this chapter is the review of the application of MCDM methods in railway engineering. As one of the means in achieving the objectives of railways and above all the utilization of capacity are Train Control Information Systems (TCIS). Based on that, the aim of this chapter is the evaluation of the efficiency of TCIS in the improvement of railway capacity utilization through defined technical-technological indicators. The non-radial Data Envelopment Analysis (DEA) model for the evaluation of TCIS efficiency in improvement of utilization of railway capacity using the selected indicators is proposed. The proposed non-radial DEA model for TCIS efficiency evaluation in using railway capacity could be applied to an overall network or for separate parts of railway lines

An Algorithmic Framework for Multiobjective Optimization

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization