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

Reference electric distribution network modelling and integration of electric vehicle charging stations

Smartcities,withprosumersatthecentre,areatthefrontlineoftheenergytransition. The national and international policies should encourage then this transition by promoting, among many aspects, energy digitalization, massive penetration of renewable energies and electrification of the transport sector. To embrace all these changes, a holistic view, covering not only the distribution system, is necessary to plan, design and reorganize in particular urban areas. The radical distribution networks transformation is monitored and presented, both considering technical and non-technical aspects, which aims at encouraging potential directions that distribution system operators can pursue. The thesis work has three main objectives. From the distribution system operator (DSO) perspective, the main objective is to investigate how the technical and non-technical features vary among distribution system networks in Europe. From the modelling perspective, the second main objective is firstly to define a method which incorporates the previous findings to properly design a tool able to reproduce representative urban networks and secondly to validate the results through a statistical methodology. From the electric vehicle’s infrastructure perspective, the thirdmainobjectiveisfirstlytounderstandtheelectricvehiclesdemandbehaviour and develop models capable of reproducing them, and secondly to assess, through a dedicated methodology, the electric vehicles charging infrastructure features and performance. Theresultsfromthisthesisindicatesthattheincreasingattentiontowardthedistribution sector should not be underestimated by the main actor, distribution system operator, which appears to have different approaches in smartening and digitalizing their network especially concerning electric mobility, demand response and data management between distribution and transmission system operators (TSO). It is urgent for policy makers and stakeholders involved to align distribution system operators to a common strategy to tackle the introduction in the distribution network grids of new players. Tools like DiNeMo platform applied in this thesis may be used to perform preliminary research studies concerning the installation of newcharginginfrastructure, renewableenergygeneratorsornetworkreinforcement analysis. Indeed, it is crucial for regulators to take into account the physical layer of distribution grids when designing new policies and incentives in order to address challenges of tomorrow’s cities

Informing U.S. Electricity Policy: Independent Data-Driven Policy Tools to Support Regulators, Policy Makers, and Utilities

Electric grids are undergoing unprecedented changes to accommodate increased social demand for sustainability, better economics, improved reliability and greater efficiency. These transformed grids, or grids in transformation, are often referred to as “Smart Grids”. Achieving the objectives of the Smart Grid will allow the grid to be more flexible and autonomous; enabling it to better use current resources and respond to the needs of consumers. The objective of this dissertation is to study and understand U.S. Smart Grid progress, identify problems in Smart Grid development, and propose data-driven tools to help utilities and regulators address those problems. Three tools are proposed in this research (1) a Smart Grid development metric and (2) an electric utility business model framework and (3) an electric utility business model financial tool. The dissertation is split into three segments. The first segment of the dissertation assesses U.S. Smart Grid progress based on information gathered directly from industry stakeholders. In that assessment eight areas were studied in depth and seven key recommendations were made. The second segment of the dissertation addresses the first recommendation identified in the Smart Grid assessment; a lack of specific Smart Grid goals and success metrics. This dissertation presents the Smart Grid development metric as a potential solution to this problem. The development metric solution is composed of twelve indicators that comprehensively measure Smart Grid progress either over time or in comparison to other nations/states. The third segment of the dissertation addresses the second problem identified; determining the appropriate way to calculate the costs and benefits of renewable generation and Smart Grid technology. The changes prompted by the Smart Grid challenge many of the traditional electric utility methods for conducting business. This dissertation work creates an electric utility business model framework as a potential solution to this problem. The electric utility business model framework is intended to help utilities determine new ways to create value around Smart Grid technology and opportunities. The electric utility business financial tool is intended to assist utilities in understanding the possible financial implications of the new value streams generated from the electric utility business model framework.Ph.D

Avaliação do desempenho de projetos de smart grids utilizando métodos multicritério de apoio à tomada de decisão

Orientador : Prof. Dr. Robson SelemeDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia de Produção. Defesa: Curitiba, 17/12/2015Inclui referências : f. 109-116Resumo: Os sistemas elétricos não sofreram grandes alterações em sua topologia, soluções e métricas desde sua concepção. Entretanto, a utilização de sensores, comunicações, capacidade computacional e controle para aumentar e melhorar as funcionalidades do sistema de fornecimento de energia elétrica tem grande potencial para revolucionar o setor elétrico. A instalação e operação adequadas dessas chamadas redes inteligentes (Smart Grids - SG) tornará os sistemas elétricos mais eficientes, seguros, dinâmicos e funcionais. Porém, inúmeras dificuldades surgem quando da implementação em larga escala de SG nos sistemas elétricos existentes, que podem ser técnicas, financeiras, ambientais e regulatórias, entre outras. Com o intuito de auxiliar neste processo, optou-se pela construção de um modelo para avaliar o desempenho de projetos de implementação de SG. Para tal, identificaram-se, com uma revisão sistemática da literatura, fatores chave e motivadores estratégicos para implementação de SG. Posteriormente foram utilizados três métodos multicritério de apoio à tomada de decisão: o método Delphi, para confirmar com especialistas os parâmetros que compõem o modelo; e os métodos do Analytic Hierarchy Process (AHP) e do Multicriteria Decision Aid Constructive Approach (MCDA-C) para modelar, no que se refere às suas estruturas lógicas e de tratamento de dados, a avaliação de projetos de SG. Avaliou-se o modelo proposto através de um estudo de caso de um projeto piloto da COPEL na região de Curitiba - PR, obtendo-se resultados com essa nova abordagem que permitiram identificar e hierarquizar os fatores chave e motivadores mais relevantes para o projeto estudado, além de construir uma estrutura quantitativo para monitorar e melhorar o desempenho do projeto. A principal contribuição deste trabalho é a nova abordagem proposta, um modelo adaptativo e amplo o suficiente para avaliar qualquer projeto de SG. Palavras-chave: Smart Grids. Gestão de projetos. Analytic Hierarchy Process (AHP). Multicriteria Decision Aid Constructive Approach (MCDA-C).Abstract: Since their conception, electric systems have not been through large modifications regarding their topology, solutions and metrics. However, the use of sensors, communications, computational capacity and control to increase and improve the power system functionalities has great potential to revolutionize the electric sector. The proper installation and operation of these so-called Smart Grids (SG) will make electric systems more efficient, safe, dynamic and functional. Nonetheless, many difficulties emerge when implementing SG technologies in a large scale. These difficulties may be technical, financial, environmental, regulatory, etc. In order to aid in this process, the proposition of a model to assess SG implementation projects performance was chosen. For this purpose, SG implementation key-factors and strategic driving factors were searched in the literature through a systematic review. Later, three multicriteria decision aid methods were used to consolidate the model being proposed: the Delphi method, to validate with experts the chosen model parameters; and the Analytic Hierarchy Process (AHP), along with the Multicriteria Decision Aid Constructive Approach (MCDA-C), to model, in relation to their logical and data treatment structures, the SG project assessment. A case study to evaluate the model was conducted, in which a local utility SG pilot-project was assessed. It was possible to, using this novel approach, identify and rank the driving and key-factors that were more relevant to the project being assessed. Also, to build a quantitative roadmap to monitor and improve the project performance. The main contribution of this work is the novel approach proposed, an adaptive model that can comprehensively assess any SG project. Key-words: Smart Grids. Project management. Analytic Hierarchy Process (AHP). Multicriteria Decision Aid Constructive Approach (MCDA-C)