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The Impact of Smart Grid Implementation & Investment On Toward a Sustainable Modern Electricity Grid: The Effects of Smart Metering and Program Investments on Demand-Side Management Performance in the US Electricity Sector 2009-2012 Jacqueline Corbett Université Laval Kathrine Wardle Canadian Tire Corp Ltd Chialin Chen National Taiwan University [email protected] Published: IEEE Transactions on Engineering Management To cite please consult published version: Corbett, J., Wardle, K. & Chen, C. (2018). Toward a Sustainable Modern Electricity Grid: The Effects of Smart Metering and Program Investments on Demand-Side Management Performance in the US Electricity Sector 2009-2012. IEEE Transactions on Engineering Management, 65(2), 252-263. Acknowledgement: This research was funded in part by Natural Sciences and Engineering Research Council (NSERC) of Canada, Grant RGPGP/328942-2013 1 Toward a Sustainable Modern Electricity Grid: The Effects of Smart Metering and Program Investments on Demand-Side Management Performance in the US Electricity Sector 2009-2012 Abstract Building a sustainable modern electricity sector is a key part of the United Nations’ 2030 Sustainable Development Goals. Smart meters are expected to contribute to the achievement of this goal by providing new demand-side management opportunities for utilities. Attempting to address existing gaps in the extant literature, this paper examines the effects of metering technologies and demand-side management program investments using panel data from 87 American electricity utilities for the period 2009-2012. Our model provides strong explanatory power with respect to energy efficiency, and shows that automated meter reading (AMR) devices, advanced metering infrastructure (AMI) devices, direct program costs and incentive costs all have a positive influence on energy efficiency effects. In contrast, the results for load management are largely insignificant, with the exception of incentive costs which has a small, but significant, negative impact on peak load reductions. We discuss the implications and potential research directions arising from these findings, in particular the need to consider interactions between different demand-side programs and the influence of different types of information technologies that are emerging as part of the smart grid. Managerial Relevance Statement Panel data analysis is performed to investigate the impacts of smart metering and program financial investments on energy demand management by the US electricity sector. Unlike most existing studies on smart grid implementation which utilize cross-sectional data, the use of panel data in this research allow for the identification of impacts of the smart grid technology by observing the performances of the same utilities over time. Decision makers can then input their specific characteristics, such as numbers of different meters types and their level of investment, to understand and determine what benefits could be expected given a certain level of technology implementation or financial investment. Our research also leads to a number of analytical results which are different from those in the existing literature. In particular, we show that automated meter reading devices, advanced metering infrastructure devices, direct program costs and incentive costs all have a positive influence on energy efficiency effects, but not on load reductions. We also discuss the importance for decision makers to consider the interactions between different types of demand-side initiatives in conjunction with transformations occurring on the supply-side as well as the continuing innovation in smart grid technologies in use by intermediary organizations and consumers. Key Words: Smart Grid, Green IT, Energy System Management, Demand-Side Management, Sustainability 2 1. Introduction Much like clean air to breath and water to drink, energy has become an essential resource of our modern society, so much so that the United Nations identified “access to affordable, reliable, sustainable and modern energy for all” as one of the 17 Sustainable Development Goals (SDGs) for 2030 [1]. Electricity is one of the most important energy types and it continues to be the fast- growing form of end-use energy consumption. Global demand for electricity in the residential sector is projected to increase 1.4% annually to 2040 [2]. Beyond simply meeting increasing demands, the electricity sector has much work to do in order to achieve the SDGs, particularly in relation to sustainability and climate change. In 2014, 30% of the United States’ greenhouse gas emissions came from the electricity sector as about 67% of its electricity production was generated primarily from fossil fuels, such as coal and natural gas [3]. Attaining the goal of sustainable electricity depends in part on the achievement a modernized electricity sector, or ‘smart’ grid. The smart grid is the next generation electricity grid that “enables bidirectional flows of energy and uses two-way communication and control capabilities that will lead to an array of new functionalities and applications” [4]. It is estimated that the electricity industry spent $18 billion on deploying smart grid technology in the United States from 2010 to 2013 [5], and the development of the smart grid has raised expectations that the transformation needed to achieve national energy security goals in conjunction with global sustainability goals is possible. Smart grid strategies to improve the sustainability of the electricity sector can target both supply-side (e.g., generation) and demand-side (e.g., consumption) activities, thus allowing the smart grid to play a significant role in a low-carbon future [6]. In regards to the former, the smart grid can support the integration of distributed generation and more variable energy sources, such as wind and solar, while maintaining system reliability. In the case of the latter, information and 3 communications technologies associated with the smart grid can facilitate changes in energy consumption. Recent developments of the smart grid allow demand-side management (DSM) techniques to be implemented more effectively and permit the use of new strategies [7]. These techniques encourage the reduction of the total electricity demand and contribute to smoothing peak load curves, both of which will contribute to lower carbon emissions [8]. Among the different information and communications technologies involved in bringing the smart grid to fruition, smart meters have received a significant amount of attention [e.g., 9, 10-12] as they represent one of the first and most tangible signs of the smart grid. There were 58.5 million smart meters in place in the United States in 2014 [13], and globally, it is estimated that 800 million smart meters will be installed by 2020 [14], making them an important preoccupation for the industry. The relationship between smart meters and improved DSM is complex and multifaceted. In general, the goal is to use smart meters to reduce electricity consumption at an overall level, as well as during critical peak load periods [15], without significantly reducing the service experienced by customers. To these ends, utilities may use a range of DSM strategies, from conservation and energy efficiency programs to more active demand response initiatives. Smart meters are important enabling devices particularly when integrated into broader energy efficiency or DSM programs and policies [16, 17]. For example, smart meters can support utilities’ efforts by providing the technological integration, two-way communications, and analytical and automated decision-making, so-called ‘technology solutions’[15]. In addition, smart meters can also provide more detailed information to consumers regarding their consumption of electricity and allow for more informed decisions. These latter functionalities have been referred to as ‘technology-enabled behavioral solutions’ [15]. With technology-enabled behavioral solutions, the influence of smart meters complements 4 and interacts with other DSM programs put in place by utilities such as education, financial incentives and variable pricing regimes. Despite the perceived benefits of smart meters with respect to DSM, research findings to date are inconclusive. A study based on cross-sectional data from U.S. utilities reveals the presence of both positive and negative relationships between different metering technologies and energy efficiency effects [9]. Lang [15] suggests that technology solutions may provide the largest reductions in peak load and overall consumption because consumers only have one decision to make (e.g., whether or not to participate), rather than having to engage in a series of decisions over time; however, behavioral reactions to technology solutions may offset some of the benefits [15]. Further, Dyson et al. [10] suggest that due to significant customer heterogeneity, demand response programs should be targeted rather than implemented on mass to maximize cost effectiveness. Given this uncertainty and the importance of building a sustainable, modern electricity sector and the equivocality in the extant literature, additional research is warranted. The goal of this paper is to contribute to the continued development of the smart grid by examining the impact of smart metering technologies on utilities’ DSM performance, in relation to both energy efficiency and load management programs. We use panel data econometrics to perform this analysis over the years 2009 to 2012. As compared to cross-sectional analyses, panel data allows for the
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