Econometric framework for electricity infrastructure modernization in Saudi Arabia, An

2017 Summer.Includes bibliographical references.The electricity infrastructure in Saudi Arabia is facing several challenges represented by demand growth, high peak demand, high level of government subsidies, and system losses. This dissertation aims at addressing these challenges and proposing a multi-dimensional framework to modernize the electricity infrastructure in Saudi Arabia. The framework proposes four different scenarios—identified by two dimensions—for the future electric grid. The first and second dimensions are characterized by electricity market deregulation and Smart Grid technologies (SGTs) penetration, respectively. The framework analysis estimates global welfare (GW) and economic feasibility of the two dimensions. The first dimension quantifies the impact of deregulating the electricity market in Saudi Arabia. A non-linear programming (NLP) algorithm optimizes consumers surplus, producers surplus, and GW. The model indicates that deregulating the electricity market in Saudi Arabia will improve market efficiency. The second dimension proposes that allowing the penetration of SGTs in the Saudi electricity infrastructure is expected to mitigate the technical challenges faced by the grid. The dissertation examines the priorities of technologies for penetration by considering some key performance indicators (KPIs) identified by the Saudi National Transformation Program, and Saudi Vision 2030. A multi-criteria decision making (MCDM) algorithm—using the fuzzy Analytic Hierarchy Process (AHP)—evaluates the prioritization of SGTs to the Saudi grid. The algorithm demonstrates the use of triangular fuzzy numbers to model uncertainty in planning decisions. The results show that advanced metering infrastructure (AMI) technologies are the top priority for modernizing the Saudi electricity infrastructure; this is followed by advanced assets management (AAM) technologies, advanced transmission operations (ATO) technologies, and advanced distribution operations (ADO) technologies. SGTs prioritization is followed by a detailed cost benefit analysis (CBA) conducted for each technology. The framework analysis aims at computing the economic feasibility of SGTs and estimating their outcomes and impacts in monetary values. The framework maps Smart Grid assets to their functions and benefits to estimate the feasibility of each Smart Grid technology and infrastructure. Discounted cash flow (DCF) and net present value (NPV) models, benefit/cost ratio, and minimum total cost are included in the analysis. The results show that AAM technologies are the most profitable technologies of Smart Grid to the Saudi electricity infrastructure, followed by ADO technologies, ATO technologies, and AMI technologies. Considering the weights resulting from the fuzzy AHP and the economic analysis models for each infrastructure, the overall ranking places AAM technologies as the top priority of SGTs to the Saudi electricity infrastructure, followed by AMI technologies, ADO technologies, and ATO technologies. This dissertation has contributed to the existing body of knowledge in the following areas: • Proposing an econometric framework for electricity infrastructure modernization. The framework takes into account technical, economic, environmental, societal, and policy factors. • Building an NLP algorithm to optimize a counterfactual deregulation of a regulated electricity market. The algorithm comprises short run price elasticity of electricity demand (ε), level of technical efficiency improvement, and discount rate (r). • Proposing an MCDM model using AHP and fuzzy set theory to prioritize SGTs to electricity infrastructures. • Adapting a Smart Grid asset-function-benefit linkage model that maps SGTs to their respected benefits. • Conducting a detailed CBA to estimate the economic feasibility of SGTs to the Saudi electricity infrastructure, This work opens avenues for more analysis on electricity infrastructure modernization. Measuring risk impact and likelihood is one area for future research. In fact, risk assessment is an important factor in determining the economic feasibility of the modernization. Probabilistic economic analysis can be applied to assess the risk associated with the implantation of the previously mentioned dimensions. The parameters used for the economic analysis, such as economic life of a project, and the discount rate, are usually deterministic. However, a probabilistic method can be applied to capture the uncertainty of the parameters. Another area for future research is the integration of both dimensions into one model in which GW resulted from market deregulation and SGTs insertion are summed

Entry mode selection for internationalization of giant Chinese state owned companies: The case of entrance in Africa of China communications construction company

Enterprise internationalization is an inevitable choice as open economies develop to a certain level. According to the direct investment development path theory of John Dunning, when the GNP Per Capita exceeds $3000, the net foreign investment will be positive. With rapid development over the past three decades, China’s international economic position and influence have significantly improved and its GNP Per Capita has surpassed$ 4000, it has entered the rapid growth stage for investment development as described in Dunning’s theory. At this stage, the market entry mode selection is the first issue to tackle for enterprise internationalization. This thesis takes China’s giant state owned construction companies as research object and the author analyzes the internal and external environments and the strategic selection for internationalization operation, and describes the conceptions, categories, internal attributes and factors of market entry mode selection for internationalization of construction companies. This thesis focuses on China Communications Construction Company Ltd (hereinafter referred to as CCCC), representative of giant Chinese state owned construction companies, sets up the SWOT analysis and weight system and conducts strategic positioning. Based on the above strategic positioning, the author takes into consideration the national background of these companies and puts forward three assumptions and their theoretical framework. The thesis takes CCCC’s entry into the market of Kenya and Angola as an example, verifies the effectiveness and application of the theoretical framework, and makes up the deficiency of the theory on market entry mode selection for enterprise internationalization, providing reference for enterprises’ market entry practice.Quando as economias abertas atingem um determinado nível de desenvolvimento a internacionalização das empresas torna-se uma escolha inevitável. De acordo com a teoria de investiemnto directo de John Dunning, quando o rendimento per capita excede $3000, o investimento estrangeiro liquido será positivo. Com um crescimento económico rápido nas últimas três décadas, a posição económica internacional da China e influência melhoraram significativamente e o seu rendimento per capita ultrapassou os$4000. Atingiu, deste modo, o estágio defendido por Dunning. Esta tese tem como objecto de pesquisa as empresas “gigantes” estatais Chinesas do ramo das obras públicas e o autor analisa a envolvente interna e externa e a escolha estratégica dos modos de internacionalização das mesmas. Esta tese foca-se na empresa chinesa – China Communications Construction Company Ltd (CCCC), representante das empresas gigantes estatais chinesas de obras públicas, descrevendo o processo de realização da análise SWOT. Tendo por base o posicionamento estratégico da empresa, o autor analisa o contexto em que esta empresa se desenvolveu e avança com três pressupostos no que concerne à sua internacionalização. A tese compara também os processos de entrada da CCCC em Angola e no Quénia

Driving Sustainability through Engineering Management and Systems Engineering

Despite the ongoing impact of the COVID-19 pandemic, the challenge of realizing sustainability across the triple bottom line of social, environmental, and economic development remains an urgent priority. If anything, it is now imperative that we work towards achieving the United Nations Sustainable Development Goals (SDGs). However, the global challenges are significant. Many of the societal challenges represent complex problems that require multifaceted solutions drawing on multidisciplinary approaches. Engineering management involves the management of people and projects related to technological or engineering systems—this includes project management, engineering economy, and technology management, as well as the management and leadership of teams. Systems engineering involves the design, integration, and management of complex systems over the full life cycle—this includes requirements capture, integrated system design, as well as modelling and simulation. In addition to the theoretical underpinnings of both disciplines, they also provide a range of tools and techniques that can be used to address technological and organisational complexity. The disciplines of engineering management and systems engineering are therefore ideally suited to help tackle both the challenges and opportunities associated with realising a sustainable future for all. This book provides new insights on how engineering management and systems engineering can be utilised as part of the journey towards sustainability. The book includes discussion of a broad range of different approaches to investigate sustainability through utilising quantitative, qualitative and conceptual methodologies. The book will be of interest to researchers and students focused on the field of sustainability as well as practitioners concerned with devising strategies for sustainable development

Driving Sustainability through Engineering Management and Systems Engineering

Despite the ongoing impact of the COVID-19 pandemic, the challenge of realizing sustainability across the triple bottom line of social, environmental, and economic development remains an urgent priority. If anything, it is now imperative that we work towards achieving the United Nations Sustainable Development Goals (SDGs). However, the global challenges are significant. Many of the societal challenges represent complex problems that require multifaceted solutions drawing on multidisciplinary approaches.Engineering management involves the management of people and projects related to technological or engineering systems—this includes project management, engineering economy and technology management, as well as the management and leadership of teams. Systems engineering involves the design, integration and management of complex systems over the full life cycle—this includes requirements capture and integrated system design, as well as modelling and simulation. In addition to the theoretical underpinnings of both disciplines, they also provide a range of tools and techniques that can be used to address technological and organisational complexity. The disciplines of engineering management and systems engineering are therefore ideally suited to help tackle both the challenges and the opportunities associated with realising a sustainable future for all.This book provides new insights on how engineering management and systems engineering can be utilised as part of the journey towards sustainability. The book includes a discussion of a broad range of different approaches to investigate sustainability through utilising quantitative, qualitative and conceptual methodologies. The book will be of interest to researchers and students focused on the field of sustainability as well as practitioners concerned with devising strategies for sustainable development

Capturing Risk in Capital Budgeting

NPS NRP Technical ReportThis proposed research has the goal of proposing novel, reusable, extensible, adaptable, and comprehensive advanced analytical process and Integrated Risk Management to help the (DOD) with risk-based capital budgeting, Monte Carlo risk-simulation, predictive analytics, and stochastic optimization of acquisitions and programs portfolios with multiple competing stakeholders while subject to budgetary, risk, schedule, and strategic constraints. The research covers topics of traditional capital budgeting methodologies used in industry, including the market, cost, and income approaches, and explains how some of these traditional methods can be applied in the DOD by using DOD-centric non-economic, logistic, readiness, capabilities, and requirements variables. Stochastic portfolio optimization with dynamic simulations and investment efficient frontiers will be run for the purposes of selecting the best combination of programs and capabilities is also addressed, as are other alternative methods such as average ranking, risk metrics, lexicographic methods, PROMETHEE, ELECTRE, and others. The results include actionable intelligence developed from an analytically robust case study that senior leadership at the DOD may utilize to make optimal decisions. The main deliverables will be a detailed written research report and presentation brief on the approach of capturing risk and uncertainty in capital budgeting analysis. The report will detail the proposed methodology and applications, as well as a summary case study and examples of how the methodology can be applied.N8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Decision support for lifecycle planning and risk management of small-scale biomass combined heat and power (bCHP) projects in the UK

Biomass is projected to account for approximately half of the new energy production required to achieve the 2020 primary energy target in the UK. Combined heat and power (CHP) bioenergy systems are not only a highly efficient method of energy conversion, at smaller-scales a significant proportion of the heat produced can be effectively utilised for hot water, space heating or industrial heating purposes. However, there are many barriers to project development and this has greatly inhibited deployment in the UK. Project viability is highly subjective to changes in policy, regulation, the finance market and the low cost incumbent; a high carbon centralised energy system. Unidentified or unmitigated barriers occurring during the project lifecycle may not only negatively impact on the project but could ultimately lead to project failure. The research develops a decision support system (DSS) for small-scale (500 kWe to 10 MWe) biomass combustion CHP project development and risk management in the early stages of a potential project’s lifecycle. By supporting developers in the early stages of project development with financial, scheduling and risk management analysis, the research aims to reduce the barriers identified and streamline decision-making. A fuzzy methodology is also applied throughout the developed DSS to support developers in handling the uncertain or approximate information often held at the early stages of the project lifecycle. The DSS is applied to a case study of a recently failed (2011) small-scale biomass CHP project to demonstrate its applicability and benefits. The application highlights that the proposed development within the case study was not viable. Moreover, further analysis of the possible barriers with the DSS confirmed that some possible modifications to be project could have improved this, such as a possible change of feedstock to a waste or residue, addressing the unnecessary land lease cost or by increasing heat utilisation onsite. This analysis is further supported by a practitioner evaluation survey that confirms the research contribution and objectives are achieved

New Progress of Grey System Theory in The New Millennium

Purpose – The purpose of this paper is to summarize the progress in grey system research during 2000- 2015, so as to present some important new concepts, models, methods and a new framework of grey system theory. Design/methodology/approach –The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “Kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of GM(1,1), such as Even Grey Model(EGM), Original Difference Grey Model(ODGM), Even Difference Grey Model(EDGM), Discrete Grey Model(DGM) and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well. Findings –The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper. Practical implications – A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science, and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate. Originality/value –The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section. Keywords Grey systems theory, Operations of grey numbers, Buffer operators, Grey forecasting models, Grey incidence analysis models, Grey cluster evaluation models, Grey decision models, Combined grey models, Grey contro

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

Sustainable Supply Chain Management

The book is a collection of studies dedicated to different perspectives of three dimensions or pillars of the sustainability of supply chain and supply chain management - economic, environmental, and social - and other aspects related to performance evaluation, optimization, and modelling of and for sustainable supply chain management, and thus presents another valuable contribution to sustainable development and sustainable way of life

Pythagorean fuzzy combinative distance-based assessment with pure linguistic information and its application to financial strategies of multi-national companies

This article addresses the issue of selecting Financial Strategies in Multi-National companies (F.S.M.). The F.S.M. typically has to consider multiple factors involving multiple stakeholders and, hence, can be handled by applying an appropriate Multi-Criteria Group Decision-Making (M.C.G.D.M.) approach. To address this issue, we develop an M.C.G.D.M. framework to tackle the F.S.M. problem. To handle inherent uncertainty in business decisions as reflected by linguistic reasoning, we embark on constructing a Linguistic Pythagorean Fuzzy (L.P.F.) M.C.G.D.M. framework that is capable of tackling both uncertain decision information and linguistic variables. The proposed approach extends the combinative distancebased assessment (C.O.D.A.S.) method into the L.P.F. environment, and processes decision input expressed as Pythagorean fuzzy sets (P.F.S.) and pure linguistic variables (rather than converting linguistic information into fuzzy numbers). The developed L.P.F.- C.O.D.A.S. technique aggregates the L.P.F. information and is applied to the F.S.M. problem with uncertain linguistic information. A comparative analysis is carried out to compare the results obtained from the proposed L.P.F.-C.O.D.A.S. approach with those from other extensions of C.O.D.A.S. Furthermore, a sensitivity analysis is conducted to check the impact of changes in a distance threshold parameter on the ranking results