Power Interruption Cost Research Articles

Interruption Cost Estimation for Value-Based Reliability Investment in Emerging Smart Grid Resources

Growing uncertainty in supply and demand in power systems causes significant challenges in maintaining supply reliability at affordable costs. Power grids are expected to undergo substantial transformations to address these challenges with upgrades and integration of emerging smart technologies that require significant investment costs. A value-based reliability assessment of these grid technologies is necessary to justify the worth of these investments. A key parameter required in such an assessment is the cost of power interruptions originating from transmission system failures. The interruption cost data available in published reports and past surveys relate to generation inadequacy since generation facilities comprise the most capital-intensive investment of an electric utility. Customer interruptions due to a lack of generation mainly occur due to generation failures during the peak demand period, whereas interruptions due to transmission component failures can occur at other periods with specific probabilities. This paper presents a methodology to estimate the cost of outages originating from transmission asset failures, which proposes a sector period model for each customer sector to obtain associated demand-normalized interruption costs. The proposed method can also be used to decide investment in grid resiliency enhancement against extreme weather that mainly impacts the grid network facilities.

Measuring the economic and societal value of reliability/resilience investments: case studies of islanded communities

ABSTRACT Large-scale disasters have exposed vulnerabilities in energy systems and interdependent infrastructure, underscoring the importance of proactively mitigating risks to critical infrastructure. This paper focuses on strengthening power system planning by incorporating the costs associated with prolonged and extensive power interruptions to bolster resilience. To achieve this, duration-dependent customer damage functions are developed, capturing the direct, indirect, and societal impacts of power interruptions, ranging from short, localized events to widespread and long-duration ones. The research methodology is applied to three islanded communities facing substantial resilience challenges with limited data availability. Three customer interruption cost surveys are conducted with local electricity customers, yielding valuable insights into duration-dependent customer damage functions for direct, indirect, and monetizable societal costs. Significantly, the power interruption cost estimates derived from these functions vary considerably from those in the contiguous U.S. and even between the different islanded communities, reflecting their distinct hazard profiles and geographical characteristics. In conclusion, this study demonstrates the potential of duration-dependent customer damage functions to enhance power system resilience. It also identifies several areas for further research, paving the way for a more robust and resilient power infrastructure.

An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk

Shared energy storage systems (SESS) have been gradually developed and applied to distribution networks (DN). There are electrical connections between SESSs and multiple DN nodes; SESSs could significantly improve the power restoration potential and reduce the power interruption cost during fault periods. Currently, a major challenge exists in terms of how to consider both the efficiency of the operation and the reliability cost when formulating the SESS scheduling scheme. A SESS optimal scheduling method that considers the DN operation risk is proposed in this paper. First, a multi-objective day-ahead scheduling model for SESS is developed, where the user’s interruption cost is regarded as the reliability cost and it is the product of the occurrence probability of the expected accident and the loss of power outage. Then, an island partition model with SESS was established in order to accurately calculate the reliability cost. Via the maximum island partition and island optimal rectification, the SESS was carefully integrated into the power restoration system. Furthermore, in order to minimize the comprehensive operation cost, an improved genetic algorithm for the island partition was designed to solve the complex SESS optimal scheduling model. Finally, a case study on the improved PG&E 69 bus system was analyzed. Moreover, we found that the DN’s comprehensive operation cost decreased by 6.6% using the proposed method.

Optimal layout model of feeder automation equipment oriented to the type of fault detection and local action

In feeder automation transformation there are difficulties in equipment and location selection. To help with this, an optimal layout model of feeder automation equipment oriented to the type of fault detection and local action is proposed. It analyzes the coordination relationship of the three most common types of automation equipment, i.e., fault indicator, over-current trip switch and non-voltage trip switch in the fault handling process, and the explicit expressions of power outage time caused by a fault on different layouts of the above three types of equipment are given. Given constraints of power supply reliability and the goal of minimizing the sum of equipment-related capital investment and power interruption cost, a mixed-integer quadratic programming model for optimal layout is established, in which the functional failure probability of equipment is linearized using the 3delta principle in statistics. Finally, the basic characteristics of the proposed model are illustrated by different scenarios on the IEEE RBTS-BUS6 system. It can not only take into account fault location and fault isolation to enhance user power consumption perception, but also can guide precise investment to improve the operational quality and efficiency of a power company.

A hybrid approach to estimating the economic value of power system resilience

The costs that power interruptions impose on customers and society have emerged as essential considerations for decision-making about power system reliability and resilience. While the direct costs of localized and relatively short-duration power interruptions are well-understood, little is known about the full impact of widespread and long-duration power interruptions, especially the indirect costs and related economy-wide impacts of these events. As a result, the costs of widespread and long-duration power interruptions are generally not or only incompletely considered in utility planning activities. This paper describes a new approach for estimating the economic costs of widespread and long-duration power interruptions. This method involves using survey responses from utility customers to calibrate a regional economic model that can estimate both the direct and indirect costs of these events. Including better estimates of these costs will enhance both the comprehensiveness and completeness of the considerations relied on to support utility planning decisions, especially on grid-hardening strategies and other capital-intensive investments in electricity sector resilience.

Power Interruption Cost Calculation based on Value-based Methodology

Power Interruption Cost Calculation based on Value-based Methodology

Interactive Robust Model for Energy Service Providers Integrating Demand Response Programs in Wholesale Markets

Demand response (DR) has become a key player in energy efficiency programs of current electric power systems. This paper presents an effective decision-making model for energy service providers with a focus on day-ahead electricity market participation and demand allocation in the distribution network. A two-step iterative framework is proposed to consider the mutual effects of the DR and market prices, in which unit commitment and economic dispatch problems are solved in the first step to determine the locational marginal prices, and successively DR program is applied in the second step to minimize the total cost of providing energy for distribution network customers. This total cost includes the cost of power purchase from the market and distributed generation units, incentive cost paid to customers, and compensation cost of power interruptions. To consider the unexpected behaviors of other market participants, prices are modeled as uncertainty parameters using the robust optimization technique. Simulation results demonstrate the significant benefits of the proposed framework for the strategic performance of energy service providers.

Improving the estimated cost of sustained power interruptions to electricity customers

Electricity reliability and resiliency have become a topic of heightened interest in recent years in the United States. As utilities, regulators, and policymakers determine how to achieve optimal levels of electricity reliability while considering how best to prepare for future disruptions in power, the related issue of how much it costs when customers lose power remains a largely unanswered question. In 2006, Lawrence Berkeley National Laboratory developed an end-use based framework that estimates the cost of power interruptions in the U.S that has served as a foundational paper using the best available, yet far from perfect, information at that time. Since then, an abundance of work has been done to improve the quality and availability of information that now allow us to make a much more robust assessment of the cost of power interruptions to U.S. customers. In this work, we find that the total U.S. cost of sustained power interruptions is $44 billion per year (2015-$) −25% more than the $26 billion per year in 2002-$ (or $35 billion per year in 2015-$) estimated in our 2006 study.

Optimal Reconstruction of Power Distribution Network based on Reliability and Economy

Great significance shall be attached to the research on how to improve reliability of user-end power supply with limited expense by coordinating reliability and economic efficiency of power grid, so that to meet the increasing demand on reliability of electric power, and achieve considerable economic effectiveness. In this paper, process of power distribution network reliability calculation based on minimum-path failure mode and effect analysis mode is expounded, and a demonstration on calculation of power distribution network reliability is provided. Furthermore, cost-benefit analysis, which includes calculations of cost and benefit of reliability, is introduced to reflect reliability efficiency through power interruption cost calculation. At the end of this paper the cost-benefit Analyses is applied on the optimal reconstructed power distribution network.

Research on solving the optimal sizing and siting of distributed generation

In this paper, a distributed network planning model is proposed with the goal of minimizing the sum of distributed power investment cost, network loss and interruption cost. In order to compare the performance of differential evolution algorithm (DE) and genetic algorithm (GA) in solving the optimal sizing and siting of distributed generation in distribution networks, the two algorithms were adopted to optimize the capacities and positions of DGs. Through analysis on a 10-bus test system, the study results show that the proposed model and algorithm can get reasonable planning scheme. And in solving simple optimization problems, both GA and DE Algorithms can get good results, but compare to DE, GA is of slow convergence speed and the convergence process is not quite stable.

Reliability constrained decision model for energy service provider incorporating demand response programs

Demand response (DR) programs are becoming a critical concept for the efficiency of current electric power industries. Therefore, its various capabilities and barriers have to be investigated. In this paper, an effective decision model is presented for the strategic behavior of energy service providers (ESPs) to demonstrate how to participate in the day-ahead electricity market and how to allocate demand in the smart distribution network. Since market price affects DR and vice versa, a new two-step sequential framework is proposed, in which unit commitment problem (UC) is solved to forecast the expected locational marginal prices (LMPs), and successively DR program is applied to optimize the total cost of providing energy for the distribution network customers. This total cost includes the cost of purchased power from the market and distributed generation (DG) units, incentive cost paid to the customers, and compensation cost of power interruptions. To obtain compensation cost, the reliability evaluation of the distribution network is embedded into the framework using some innovative constraints. Furthermore, to consider the unexpected behaviors of the other market participants, the LMP prices are modeled as the uncertainty parameters using the robust optimization technique, which is more practical compared to the conventional stochastic approach. The simulation results demonstrate the significant benefits of the presented framework for the strategic performance of ESPs.

The Lebanese Electricity Woes: An Estimation of the Economical Costs of Power Interruptions

This paper contributes to the political and scientific debate surrounding the economic costs entailed by the regular power cuts in Lebanon. Examining the data on electricity consumption that was produced by onshore and offshore power plants, this paper estimates the economical costs of power interruptions in Lebanon over the period 2009–2014. Based on 700 USD/MWh, representing the average value of lost load (VOLL) in that period, results indicate that electricity shortages continue to render significant transfers of wealth to the detriment of economy and society as a whole. Over the period 2009–2014, the total losses for the Lebanese economy reached 23.23 billion USD. Just as importantly, some evidence suggests a sharp decline in the economical costs of power interruptions with the inception of the two floating power plants in 2013. The results are crucial for the decision makers to identify the economic efficiency of alternative measures to enhance the security of the Lebanese electricity supply.

The Value of Lost Load for Sectoral Load Shedding Measures: The German Case with 51 Sectors

The transition of the German electricity system towards a renewable, nuclear free and increasingly fluctuating power generation raises concerns about supply security. A possible contribution to solve this issue might lie in demand response or load shedding measures. The goal of our work is to monetarily quantify the consequences of power interruptions. The focus lies on power interruption costs in 51 economic sectors. Two input-output models are proposed to estimate the Value of Lost Load for each sector. The first does not take inter-linkages of the sectors and possible cascading effects on interruption costs into account. The second model is a new and innovative approach which is based on the Ghosh Input-Output model and which accounts for these effects. We assume that the first model is adequate to assess shorter power interruptions, whereas the second model might be more appropriate when estimating costs of longer interruptions.

The Costs of Power Interruptions in Germany: A Regional and Sectoral Analysis

Abstract A high standard of security of electricity supply comes at serious electricity system costs. However, these system costs have to be balanced with the economic costs induced by an insecure supply of electricity. Following a macroeconomic approach, we analyze the economic costs imposed by potential power interruptions in Germany. Using an extensive dataset on industries and households, we estimate both Values of Lost Load and the associated hourly costs of power interruptions for different German regions and sectors. We find that interruption costs vary significantly over time, between sectors and regions. Peaking at midday on a Monday in December at 750 Mio € per hour, the average total national outage costs amount to approximately 430 Mio € per hour. A missing gigawatt hour creates average outage costs of about 7.6 Mio €.

Power Interruption Costs to Commercial Customers of Electricity in Korea

This paper presents the result of the estimation of the power interruption costs of Korean commercial customers. Commercial customers are usually located in urban areas and considered very important because a power interruption on them can expand to additional damage to related users. Their power interruption costs were calculated through a survey with the process of data selection. Also, the power interruption cost for each customer's business type was calculated and compared with that of foreign cases.

Stated preferences based estimation of power interruption costs in private households: An example from Germany

Concerns regarding supply security are increasingly raised in reaction to the transition of the German energy system toward a renewable and nuclear-free system called “Energiewende”. The goal of this work is to contribute to a measurability of supply security by quantifying the consequences of power interruptions monetarily. The focus lies within the investigation of power interruption costs in private households. An online survey with 859 participants in 2011 is used to gather the necessary data. Based on this data, a two-staged bottom-up regression model was estimated to describe interruption costs for durations of 15 min, 1 h, 4 h, 1 day and 4 days. Finally, micro-data from 55,000 households were used to perform Monte Carlo simulations to increase the representativeness of the estimations. The frequency distributions of the estimated interruption costs indicate potentials for load-shedding measures. Such measures could be an economically viable contribution to a successful integration of large shares of renewable fluctuating generation like wind or solar power.

Power interruption costs to industries in Cameroon

This study focusses on the estimation of power interruption costs to industries in Cameroon. Those interruptions are the result of perturbations sustained by the power network. A normalised direct worth (NDW) approach was used as a direct method for assessment, while the compensatory estimation method (CEM) was used for indirect assessment. A survey was conducted with a representative sample of industries in Cameroon using a questionnaire as the main research instrument. The results show that power interruption losses are very significant. Using the direct method for assessment, the average outage cost varies from €3.62/kWh to €5.42/kWh for a 1-h interruption and from 1.96/kWh to €2.46/kWh for a 4-h outage. The study finds that advance suspension notices could help in reducing outage costs by 19.83–33%. With the indirect method, the total capital costs and total running costs of generators are approximately €180,040,180.08 and €4,305,510.6, respectively, while the average cost per unused kWh of electricity stands at €3.37/kWh. The study concludes that power interruptions have a significant negative effect on industries in Cameroon.

A Novel Hybrid Approach to Estimate Customer Interruption Costs for Industry Sectors

The power system infrastructure, operations and market have gone through radical changes for the last couple of decades. The society has become more dependent to the continuous electric power supply and hence the concept of electric power reliability has become more significant. At this point, understanding the economic outcomes of power outages is vital and imperative for both utilities and the customers. There are certain methodologies to understand the costs of power interruptions. This paper suggests a novel hybrid method that comprises of customer surveys and direct analytical methods to reach customer specific, objective and reliable results for the industry sector customers. The paper also brings a statistical approach to censor the zero and extreme responses given via the surveys.

An Optimal Pricing Policy for Interruptible Load Contracts in Power Markets: A Case Study for Iran

The electricity market restructuring has created new opportunities for customers to partner with utilities to alter their demand in response to electric system reliability needs or high prices. The consumer participation in wholesale energy markets tends to increase the electricity system reliability, reduce the electricity price volatility, and lower the average electricity prices paid by the consumers. This paper presents a new demand management program for the electric distribution companies (Dist Co.). It models and solves a profit maximization mathematical program for a Dist Co. subject to some constraints related to the customersГўВҖВҷ costs of power interruptions, market price of electricity, and maximum amounts of interruptible loads by different consumers. The outputs of the mathematical program are the optimal load curtailments and optimal price tariffs for different customers that maximize the Dist CoГўВҖВҷs profit function. The particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used to solve the non-linear mathematical program. A case study, for managing the power consumptions of some industrial firms in Iran, is presented and analyzed to show the applicability of the proposed demand management algorithm.

Assessing energy supply security: Outage costs in private households

The objective of this paper is to contribute to the topic of energy supply security by proposing a Monte Carlo-based and a survey based model to analyze the costs of power interruptions. Outage cost estimations are particularly important when deciding on investments to improve supply security (e.g. additional transmission lines) in order to compare costs to benefits. But also other policy decisions on measures that have direct or indirect consequences for the supply security (e.g. a phasing out of nuclear energy) need to be based on results from outage cost estimations. The main focus of this paper lies with residential consumers, but the model is applied to commercial, industrial and governmental consumers as well. There are limited studies that have approached the problem of evaluating outage cost. When comparing the results of these studies, they often display a high degree of diversification. As consumers have different needs and dependencies towards the supply of electricity because of varying circumstances and preferences, a great diversity in outage cost is a logical consequence. To take the high degree of uncertainties into account, a Monte Carlo simulation was conducted in this study for the case of private households in Germany.