Establishing a framework of a watershed-wide screening tool to support the development of watershed-based flood protection plans for low-lying coastal communities

Flood risk analysis is the instrument by which floodplain and stormwater utility managers create strategic adaptation plans to reduce the likelihood of flood damages in their communities, but there is a need to develop a screening tool to analyze watersheds and identify areas that should be targeted and prioritized for mitigation measures. The authors developed a screening tool that combines readily available data on topography, groundwater, surface water, tidal information for coastal communities, soils, land use, and precipitation data. Using the outputs of the screening tool for various design storms, a means to identify and prioritize improvements to be funded with scarce capital funds was developed, which combines the likelihood of flooding from the screening tool with a consequence of flooding assessment based on land use and parcel size. This framework appears to be viable across cities that may be inundated with water due to sea-level rise, rainfall, runoff upstream, and other natural events. The framework was applied to two communities using the 1-day 100-year storm event: one in southeast Broward County with an existing capital plan and one inland community with no capital plan.

Evaluating the policy of listening to customer claims in a drinking water utility using fuzzy-AHP approach and WASPAS method

The objective of this work is to develop a decision support methodology intended for drinking water utility managers in order to support them in the challenge of achieving better performance in the management of the customer area. This methodology requires the prior collection of data for the identification of registered claims. Subsequently, an evaluation of the performance of the customer area defined by the objective ‘Better listening to customer claims’ will be carried out; this requires the structuring of the objective in a hierarchy based on indicators and the adoption of two adequate decision support tools, a fuzzy-AHP for weighting the elements and WASPAS for calculating the performance of the objective. An application is carried out on the water utility of the Wilaya of Bejaia (Algeria). The data collection enabled the identification of 19 types of claims divided into three aspects. The combination of fuzzy-AHP and WASPAS allowed assessment of the performance of the objective during the period 2014–2018 and to make a judgment on the national policy established. The results are satisfactory. Progress has been made in claims management, but the major difficulty lies in the claims processing relating to the quantitative aspect.

An empirical analysis of residential meter degradation in Gauteng Province, South Africa

Understanding the degradation rates of water meters assists utilities in making informed management decisions regarding meter replacement programmes and meter technology selection. This research evaluated the performance of 200 residential meters of two different technologies commonly used in Gauteng, South Africa, namely velocity meters and volumetric meters. This was done by conducting empirical meter testing in a verification laboratory and evaluating the degradation accuracy of each meter technology based on age and volume. Results indicate that velocity meters experience an accuracy degradation rate of approximately −1.13% per 1 000 kL of volume passed through the meter and an inferred initial error of −10.80%. Meter accuracy was not strongly related to age of the velocity meters tested. Volumetric meters did not exhibit a strong link with either age or accumulated volume, indicated by a loose grouping of results. These results indicate that accumulated volume of a velocity meter is a more reliable predictor of accuracy than age, and should be used when planning replacement strategies for velocity meters. Additionally, the lack of predictable degradation rates related to either age or accumulated volume for volumetric meters indicates that the accuracy of volumetric meters is primarily affected by other external factors, such as particulates or entrained air in the water network. These findings will assist utility managers in predicting the accuracy of their meter fleet and in making informed decisions regarding meter replacement.

Are Regulators Effective at Unraveling Accounting Manipulation? Evidence from Public Utility Commissions

Prior research proposes that a monopolist with private information inflates its reported costs under rate regulation to extract an informational rent. Using a sample of U.S. electric utilities from 1990–2011, we first confirm an unexpected increase in operating expense during rate review periods, then decompose operating expense into its cash and accrual components, and find the cash component accounts for 89% of this increase. The observed pattern is consistent with some combination of real activities management and utility managers misrepresenting transitory expense shocks as permanent. We then focus on identifying regulators’ effectiveness at unraveling this manipulation and minimizing the rent. We estimate that, on average, regulators allow 17¢ out of every dollar of abnormal cash expense to be recovered in future annual revenue, a statistically significant amount. Next, we study the effects of regulators’ ability (proxied by experience) and motivation (proxied by whether they were elected) to unravel accounting manipulation. We find that whereas inexperienced and politically appointed regulators allow a significant portion of abnormal cash expense to be recovered (41¢ and 24¢ out of every dollar, respectively), experienced and elected regulators do not (although the difference between appointed and elected regulators is not statistically significant). Our findings suggest that regulators differ in their ability to identify manipulation—with experience enhancing this ability—and that, on average, state regulators effectively unravel most of the effect of accounting manipulation. This paper was accepted by Suraj Srinivasan, accounting.

Fundamentals of Energy Regulation

Fundamentals of Energy Regulation provides an insight to the wide range of topics necessary for energy regulators. Is a complete introduction to the world of energy regulation and provides the fundamental aspects of each energy regulation topic. Introduces important regulatory topics and features explanations of key economic and regulatory concepts.Fundamentals of Energy Regulation covers emerging issues associated with restructured electric energy and capacity markets as well as international practises affecting the natural gas and electric industries. Provides the various aspects and steps of managing the transition to energy market competition and for the development of energy tariffs.Fundamentals of Energy Regulation, also, provides an insight to the wide range of electricity generating technologies including renewable energy sources available today or under development, an overview of the future sustainable energy systems and environmental issues. Fundamentals of Energy Regulation is partly based on lecture notes pro- vided in two different courses for a number of years and is intended as an introductory textbook for courses in the field of energy regulation and energy markets. It is not by any means exhaustive, nor is it intended to be. In the more than two decades I’ve worked with the energy industry, the field has grown so vast that it’s no longer possible to confine all aspects within the covers of one book, even after limiting it to the most important issues.Fundamentals of Energy Regulation can serve as a reference text for energy regulators, power and natural gas market planners, utility managers, transmission system operators, distribution system operators, consultants, policy makers and economists.

Performance analysis of electricity distribution sector post the implementation of electricity act 2003: empirical evidence from India

PurposeThe objective of the present study is to evaluate and analyse the performance of Indian electricity distribution utilities post the implementation of landmark Electricity Act 2003.Design/methodology/approachStochastic frontier analysis (SFA) that incorporates exogenous influences on operational efficiency is adopted in the present study. Specifically, a stochastic frontier production function model with a technical inefficiency effects model (Battese and Coelli, 1995) is chosen as a preferred model. In this model, the function that explains the inefficiency scores is estimated in a single stage with the production technology. This avoids the problem of inconsistency which is possible in the two-stage approach.FindingsThe sample involved 52 Indian electricity distribution utilities for seven-year period from 2006 to 2013. Major findings of SFA show that Indian electricity distribution utilities post the implementation of Electricity Act (2003) had, on average, experienced efficiency improvement during the observed period. The overall mean technical effciency score is estimated as 78.5% which indicates that there exist wide scope for effciency improvement in the sector. Further, the empirical findings also indicate that publicly owned distribution utilities obtain average technical efficiencies of 71.3%, which is lower than privately owned distribution utilities, which achieve average technical efficiencies of 85.7%.Research limitations/implicationsPower supply quality indicators such as SAIFI, SAIDI, CAIFI, etc. and unobserved heterogeneity also influence the efficiency analysis of electricity distribution utilities. Hence, these parameters as explanatory variables can be incorporated in the future work.Practical implicationsThe results obtained from this empirical study would likely be helpful for utility managers and policymakers to know how well they are performing, and how a better corporate strategy a particular utility can formulate to improve its operational efficiency and also its position in the marketplace.Originality/valueThis paper is amongst the first significant attempts that implement SFA approach to the panel dataset over a longer period of time – 2006 to 2013, so, as to evaluate and analyse the operational efficiency of Indian electricity distribution utilities in a single framework after the enactment of Electricity Act (2003). Unlike previous studies, this study investigates the degree to which various exogenous (or environmental) factors influence efficiency levels in these utilities.

Municipal Utilities and COVID-19: Challenges, Responses, and Collaboration

The COVID-19 pandemic has put pressure on essential public services. While much of the economy has been shut down, essential public services have continued. Using professional experience, publicly available information, and interviews with two municipal utility managers, we evaluate the challenges presented to municipal utility services by the COVID-19 pandemic and explore some of the responses by utilities to the pandemic. Specifically, we focus on the strategies utilities have used to keep employees safe from the virus and plans for workforce shortages. One important strategy we identify is reliance on mutual aid agreements, where utilities agree to send staff and equipment to other utilities in times of crisis. We also explore the role of a municipal utility association in coordinating response. The case of utility response to COVID-19 carries important potential implications for both public administration practice and research.

Sewer Pipes Condition Prediction Models: A State-of-the-Art Review

Wastewater infrastructure systems deteriorate over time due to a combination of aging, physical, and chemical factors, among others. Failure of these critical structures cause social, environmental, and economic impacts. To avoid such problems, infrastructure condition assessment methodologies are developing to maintain sewer pipe network at desired condition. However, currently utility managers and other authorities have challenges when addressing appropriate intervals for inspection of sewer pipelines. Frequent inspection of sewer network is not cost-effective due to limited time and high cost of assessment technologies and large inventory of pipes. Therefore, it would be more beneficial to first predict critical sewers most likely to fail and then perform inspection to maximize rehabilitation or renewal projects. Sewer condition prediction models are developed to provide a framework to forecast future condition of pipes and to schedule inspection frequencies. The objective of this study is to present a state-of-the-art review on progress acquired over years in development of statistical condition prediction models for sewer pipes. Published papers for prediction models over a period from 2001 through 2019 are identified. The literature review suggests that deterioration models are capable to predict future condition of sewer pipes and they can be used in industry to improve the inspection timeline and maintenance planning. A comparison between logistic regression models, Markov Chain models, and linear regression models are provided in this paper. Artificial intelligence techniques can further improve higher accuracy and reduce uncertainty in current condition prediction models.