A fuzzy Analytic Hierarchy Process algorithm to prioritize Smart Grid technologies for the Saudi electricity infrastructure

https://doi.org/10.1016/j.segan.2017.12.010Get rights and content

Highlights

  • Saudi Transformation Program is adapted to develop a systematic framework for technology prioritization.

  • The framework proposes a transitional roadmap of grid modernization for policy makers.

  • A Fuzzy Analytic Hierarchy Process algorithm is used to prioritize Smart Grid technologies.

  • Triangular fuzzy numbers are used to model planning uncertainty.

  • Advanced metering infrastructure is the most important alternative for the modernization of the Saudi grid.

Abstract

Uncertainty is an inherent feature in grid modernization planning decisions. The paper presents a decision analysis framework to integrate Smart Grid technologies and applications for the modernization of the Saudi electricity infrastructure. The analysis applies a fuzzy set theory accompanied by the Analytic Hierarchy Process. Imprecision in decision making – particularly those arising from human subjectivity in input – is explicitly modeled using fuzzy sets. This paper demonstrates the use of triangular fuzzy numbers to model uncertainty in planning decisions. The Saudi electricity infrastructure aims at meeting certain goals stated in the Saudi Vision 2030 and the National Transformation Program. We propose an algorithm for prioritizing candidate Smart Grid technologies for grid modernization. This is intended as a tool for charting a transitional modernization plan for policy makers and for meeting specific targets in the transformation program.

Introduction

The modernization of electricity grid infrastructure occurs in several stages of improvement and upgrades as evidenced in multiple electricity infrastructures across the world. In some grid systems, the focus has been on upgrading the infrastructure of assets and renewing the devices and machines, which are the backbone of the grid. In some other grid systems, the focus has been on improving the level and depth of inter-communication and control among grid sectors, namely generation, transmission, distribution, and consumers. In other electricity infrastructures, electricity markets were given much more attention by liberalizing the market and enabling two-way communication means between service providers and consumers.

Grid modernization is an essential goal towards an efficient, reliable, economic, and stable grid. Smart Grid plays an important role in grid modernization. Smart Grid, differing from the traditional grid, establishes an infrastructure that makes the grid capable of achieving certain goals such as increased observability and controllability of assets for enhanced performance and security. Smart Grid also holds the potential for reduced costs of operations, maintenance, and system planning. Ultimately, the grid would acquire the capabilities of self-correction, reconfiguration and restoration, and handling randomness of loads and uncertainty of renewable sourced generators, and real-time market participants [1].

This paper addresses the penetration of SGTs for improving the performance of the electric grid. Many studies conducted to measure the benefit-to-cost ratio of technical aspects of the Smart Grid concluded that the ratio is about 4:1 to 6:1 [2]. However, the concern is which technologies should be given the priority for implementation considering the current status and challenges facing an electricity infrastructure.

From a planning perspective, designing policies that establish a pathway for transitional modernization for the electricity infrastructure is not straightforward. Decision making in electric power systems is faced with multiple quantitative and qualitative elements. In such environments, decision makers deal with several policies that should be examined and investigated using multiple attributes. This paper proposes an MCDM framework using fuzzy AHP to prioritize the relative importance of candidate SGTs for electricity infrastructures. The framework is demonstrated on the Saudi Arabian electricity infrastructure through a case study presented in this paper. One reason for choosing the Saudi electricity infrastructure is that the energy sector in the country is expected to encounter major reforms. The Saudi Council of Economic and Development Affairs has introduced the Saudi Vision 2030 [3]. It is an ambitious and comprehensive blueprint that expresses the country’s long-term goals and expectations until the year 2030 for reinforcing and diversifying the capabilities of the country’s economy. To achieve these aspirations, the Council has already launched many transformative programs that have paved the way for the Saudi Vision 2030. One of these programs is the National Transformation Program [3], introduced in April 2016, which is established to examine the role of the government agencies in implementing the policies required for delivering on national priorities. The National Transformation Program aims at establishing initiatives that have clear performance indicators to track the implementation of the Vision 2030. This program outlines the policies required for electricity infrastructure modernization, addresses challenges, and sets the targets to transform the grid from its status quo to a modernized version. In line with the implementation of the National Transformation Program, this paper aims to provide policy makers with an econometric framework and analysis for a future transitional modernization of the Saudi electricity infrastructure.

Another reason for choosing the Saudi electricity infrastructure as a case study is that the infrastructure is facing several challenges in delivering reliable, continuous, and economic electricity to its consumers. Further details about these challenges are discussed in Section 4 of this paper. The paper proposes a prioritized penetration of SGTs to enhance the reliability and stability of the electricity infrastructure, and mitigate the impact of the technical and economic challenges.

Initially, we introduced a framework to modernize the Saudi electricity grid. The framework proposes that grid modernization is to be achieved through two dimensions. The first dimension is to deregulate the electricity market. The second dimension is to allow the penetration of SGTs. A complete overview of the framework proposed by the authors can be found in [4]. The framework takes into consideration technical, societal, and economic aspects related to such modernization effort. The approach offers a comparison between different scenarios by employing cost–benefit analysis and risk assessment. The framework introduces a tool to chart a roadmap for transitional modernization of the grid for policy makers. While the case study presented in this paper is on the Saudi Arabian electricity grid, we believe the framework and analysis are generic enough for use by policy makers of other infrastructures, albeit with appropriately changed inputs.

The first dimension is modeled by building a non-linear programming algorithm. The algorithm models the mechanism of deregulating the electricity market and estimating global welfare. The efficiency of the electric network is considered in an ex ante setup. The study shows that deregulating the market is expected to increase producers’ profits because the selling price is expected to be higher than the cost of production after the government subsidies are cut. Level of electricity output sold is expected to remain unchanged since we consider a short-run timeframe that does not allow consumers relatively much time to switch to another source of energy or adapt new conservation program. Global welfare is expected to turn out positive, meaning that the deregulation is recommended under the certain conditions and assumptions. The complete work relating to the first dimension can be found in [5]. This paper analyzes the second dimension. The rest of the paper is organized as follows: Section 2 defines grid modernization and discusses the implications of the term, Smart Grid. Section 3 provides literature review on previous studies addressing electric grid modernization in Saudi Arabia. Section 4 provides an overview about the current status of the electricity infrastructure in Saudi Arabia. Sections 5 AHP, 6 Fuzzy set theory provide overviews of AHP, and fuzzy set theory and its use with AHP, respectively. Section 7 presents the problem framework, and discusses the application of the model through a case study for the Saudi electricity grid. Section 8 shows the analysis. Section 9 presents the results. And, Section 10 concludes and discusses the policy implications of the study findings.

Section snippets

Grid modernization and Smart Grid

The electric grid infrastructure in many countries across the world suffers several challenges such as aggravated grid congestion driven by uncertainty in supply, especially after the introduction of renewable energy sources [6]. Power transfer over interconnected regions can lead to propagating events of service interruptions. The increasing trend for grid interconnection creates a large footprint with a more complex system that gives rise to the importance of grid control and monitoring. From

Literature review

While literature research addressing SGTs insertion from technical and economic perspectives in Saudi Arabia are limited, several studies discuss the challenges facing the Saudi electric grid and the proposed solutions of introducing SGTs and addressing policy implications. Refs. [[17], [18]] discuss the importance of SGTs in harnessing the benefits of untapped renewable energy resources, and optimally integrating them into the grid. They also describe the attributes of Smart Grid and how these

Current status of the Saudi electricity infrastructure

The electricity infrastructure in Saudi Arabia is faced with several challenges resulting from the impressive growth of the national economy since the 1980s. The country is a high consumer for oil. Saudi Arabia is the largest oil-consuming nation in the Middle East and, was the world’s 12th largest consumer of total primary energy in 2013 at 9 quadrillion British thermal units [25]. Domestic consumption represented 2.9 million barrels per day of oil in 2013, almost double its consumption in

AHP

AHP is a popular MCDM method that can handle unstructured or semi-structured decisions with multi-criteria inputs. AHP is used in making decisions that involve ranking, selection, evaluation, optimization, and prediction. AHP can organize objectives, criteria, and alternatives into a hierarchal structure. AHP derives ratio scales from deductive and inductive inputs through multiple pairwise comparisons. Moreover, AHP is one of the few methods that can assess the consistency of the judgment of

Fuzzy set theory

As mentioned earlier, judgments of decision makers involve uncertainty and imprecision. Fuzzy set theory is introduced to AHP to deal with the uncertainty and imprecision. These uncertainties are transformed into fuzzy sets and integrated into the AHP model. Fuzzy set theory postulates that an element has a degree of membership in a fuzzy set, which is represented by a membership function. The membership values of an element vary in the interval [0,1]. The variation in the linguistic variable

Problem framework

The authors propose an econometric analysis that examines prospect scenarios for a modernized Saudi electricity infrastructure with regards to two dimensions. The first dimension is the deregulation of the electricity market. The second dimension is the penetration of SGTs. While the model framework of the econometric analysis is described in [4], the first dimension is described and analyzed in [5]. This paper analyzes the second dimension. Allowing the penetration of SGTs and applications is,

Analysis

Considering the criteria and alternatives identified in the previous section, a pairwise comparison process is followed to construct the judgment matrix for the criteria using objective data available in the National Transformational Program [3]. According to the program, the baseline, i.e., the status quo, and the 2020 targeted values for all KPIs are stated. These values are used to obtain the pairwise comparisons. For each criterion, its KPI targeted value is subtracted from its baseline

Results

In this study, the alternative, AMI, is the most important alternative followed by AAM, ATO, and ADO. It is noticed that the second and third alternatives in the rank are very close with regard to their weight value. Policy makers may consider AMI as the one with the highest priority with regards to the electricity infrastructure modernization program in Saudi Arabia considering the attributes (criteria) discussed earlier.

To examine the performance of fuzzy AHP approach, a comparison is

Conclusion and policy implications

The paper presents a framework for multi-criteria decision making method to analyze and prioritize the importance of Smart Grid technologies to the Saudi electricity infrastructure. A fuzzy AHP model is built to construct pairwise comparisons among attributes and alternatives. The results suggest that AMI technologies are the most important in order to achieve the 2020 targets stated in the National Transformation Program and the Saudi Vision 2030. The framework offers a tool to chart a roadmap

Acknowledgment

T.A. Alaqeel gratefully acknowledges the financial contribution of King Abdullah Scholarship Program, The Ministry of Higher Education, Saudi Arabia .

Turki A. Alaqeel received the B.Sc. in electrical engineering from King Saud University. He received the Master’s Degree in business administration (MBA), and the PhD in electrical engineering from Colorado State University. His employment experience included Saudi Electricity Company, ABB, Woodward and the Advanced Power Engineering Laboratory at Colorado State University where he pursued his PhD degree. Currently, he is a research associate at King Abdullah Petroleum Studies and Research

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    Turki A. Alaqeel received the B.Sc. in electrical engineering from King Saud University. He received the Master’s Degree in business administration (MBA), and the PhD in electrical engineering from Colorado State University. His employment experience included Saudi Electricity Company, ABB, Woodward and the Advanced Power Engineering Laboratory at Colorado State University where he pursued his PhD degree. Currently, he is a research associate at King Abdullah Petroleum Studies and Research Center (KAPSARC) in Riyadh, Saudi Arabia.His special fields of interests include grid modernization, Smart Grid, and the economics of electric power systems.

    Siddharth Suryanarayanan is the Lisa and Desi Rhoden Endowed Chair Associate Professor in the Department of Electrical and Computer Engineering at Colorado State University, where he supervises sponsored research and teaches in the area of electric power systems engineering. He received the Ph.D. degree in electrical engineering from Arizona State University in 2004.

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