Customer attitudes regarding electric outage costs and back-up generation

Generators and the cost of electricity outages

Outage costs quantification for benefit–cost analysis of distribution automation systems

The electric utilities in the developing countries lack sufficient data required for long-term electricity supply system planning which have resulted in wide gap between demand and supply in these countries. Also, there is lack of coordination among different constituents of electric utilities generation, transmission and distribution. Vital data for system planning are often unavailable and planning is done in some arbitrary manner causing long-term financial and economical impact on the whole nation. Customers’ electricity supply outages data and supply outage costs are very important for financial and economical analysis of an electricity supply system. Quantifying the losses to customers will enable us to check whether a proposed system expansion plan will be economically viable or not. Industrial customers form the backbone of any country’s economy. Hence, the supply outage cost to the industrial customers deserves close attention. After quantifying cost incurred by industrial customers because of nonsupply of electricity, the planners and policy makers will be forced to seriously consider about the ways of minimizing these outages and their adverse impact on the customers. In this paper, we will describe an industrial customer survey carried out in Nepal to determine their outage cost. Results of the survey can be used as reference electricity supply outage cost values in other developing countries with similar socio-economic profile.

Quantifying the costs of radar outages allows value to be attributed to the alternate datasets that help mitigate outages. When radars are offline, forecasters rely more heavily on nearby radars, surface reports, numerical weather prediction models, and satellite observations. Monetized radar benefit models allow value to be attributed to individual radars for mitigating the threat to life from tornadoes, flash floods, and severe winds. Eighteen radars exceed $20 million in annual benefits for mitigating the threat to life from these convective hazards. The Jackson, Mississippi, radar (KDGX) provides the most value ($41.4 million), with the vast majority related to tornado risk mitigation ($29.4 million). During 2020–23, the average radar is offline for 2.57% of minutes or 9.27 days per year and experiences an average of 58.9 outages per year lasting 4.32 h on average. Radar outage cost estimates vary by location and convective hazard. Outage cost estimates concentrate at the top, with 8, 2, 4, and 5 radars exceeding $1 million in outage costs during 2020, 2021, 2022, and 2023, respectively. The KDGX radar experiences outage frequencies of 4.92% and 5.50% during 2020 and 2023, resulting in outage cost estimates > $2 million in both years. Combining outage cost estimates for all radars suggests that approximately $29.1 million in annual radar outage costs may be attributable as value to alternative datasets for helping mitigate radar outage impacts. Significance Statement This study combines information on radar status and monetized radar benefit models to attribute value to individual radars, estimate radar outage costs, and quantify the potential value of alternative datasets during outage-induced gaps in coverage. Eighteen radars exceed $20 million in annual benefits for mitigating the combined threat to life from tornadoes, flash floods, and severe winds. The first and third most valuable radars, both in Mississippi, experience outage frequencies twice the national average, accounting for a disproportionate share of the overall outage costs. Our findings suggest that characterizing and mitigating these outages might provide a near-term solution to better protect these communities from convective hazards. Combining outage cost estimates for all radars suggests that approximately $29.1 million in annual radar outage costs may be attributable as value to alternative datasets for helping mitigate the impacts of radar outages.

This study empirically examined the impact of electricity power outages on Nigeria’s capital and labour productivity. The emphasis is on how frequent electricity outage reduces labour and capital effectiveness and other factors of production. To achieve the above objective, annual time series data on Total Factor Productivity - a proxy for Nigeria’s factors productivity, Power Outage (electric power transmission and distribution losses as % of output), and other controlled variables were used to estimate the relationship and all data were from World Bank Development Indicators (WDI). The Fully Modified Ordinary Least Square (FOLS) technique was adopted for analysis. The empirical results showed a negative relationship between power outages and factor productivity. The result also reveals that electricity pricing has a significant negative impact on the factor productivity while both electricity generation and population have a significant positive impact on Nigeria’s total factor productivity. The implication is that the substitution effect between labour and capital is positive, meaning that Nigeria exhibits a labour-intensive production function. In conclusion, the study is of the opinion that power outage and electricity pricing negatively impact factors productivity while electricity generation and population have a positive relationship with factors productivity in Nigeria.

This study discusses the optimal specification analysis of reserve generation to provide back-up on the plywood industry during a power outage, the loss of the plywood industry due to power outage is enormous. The first thing to do is look for a loss formula during outage and then determine the specification of the backup generation. The plywood industry plays an important role in the development of the national economy and also contributes to the increase of Gross Domestic Product (GDP). The problem is often felt that the occurrence of blackouts so as not to get maximum production. Among industries, power outages have a major impact on the decline in output resulting in the company's turnover. The more frequent power outages, the more the production decreases and the turnover that the company gets will be smaller. Another impact is the need for energy use to reheat the water vapor that has experienced a temperature drop to cool again when there is a power outage. Therefore, it is necessary to make a formulation to calculate the losses suffered by the plywood plant due to power outages. With this calculation we will get the value of specification of hybrid PV-battery diesel optimal backup generation as a backup power provider during power outage.

This paper presents the generation and transmission expansion planning (GTEP) in electricity and gas networks by considering their resilience against floods and earthquakes. These networks supply electricity, heat, and gas consumption energies as a multi‐carrier microgrid. The scheme is expressed in the form of bi‐level optimization, the upper level of which is the minimization of generation and transmission planning cost (total investment cost and expected operating cost) in the mentioned networks constrained to the investment budget and the planning model of the mentioned elements. Lower‐level formulation minimizes the total expected annual operating cost of these networks and the expected outage cost of electricity, heat, and gas consumers in the event of floods and earthquakes. This formulation is bound by the power flow equations of electricity and gas networks, the operation and resilience constraints of the networks, and the limitation on generation capability. In this problem, the expected energy not‐supplied and the outage cost during natural disasters are considered resilience indicators. Next, a single‐level model for the proposed design is extracted from the Karush–Kuhn–Tucker (KKT) method. The basic requirement of this method is the convexity of the lower‐level constraints. For this purpose, first, a linear approximation model is obtained for the lower‐level constraints of the problem. Furthermore, stochastic optimization is adopted to model the uncertainty of load, renewable power, and network equipment availability during floods and earthquakes. Finally, the extracted numerical results confirm the capability of the proposed scheme in improving the operation and resilience of the mentioned networks using optimal generation and transmission planning.

The growing emphasis on electrification has heightened the importance of reliable electricity supply. In South Korea, the government is advancing market reforms, including the introduction of capacity and ancillary service markets, to enhance electricity system reliability. Within this context, this study aims to estimate the willingness to pay (WTP) of residential electricity consumers to avoid power outages using the contingent valuation method (CVM). The resulting WTP values are used to derive the value of lost load, which serves as a key indicator for reliability investment. Based on a dataset of 1000 South Korean households, we employed both CVM and choice experiments as empirical approaches. The results indicate a WTP of 8.16% and a willingness to accept of 18.08% of the monthly electricity bill, which correspond to outage costs of USD 2.76 and USD 6.11 per kWh, respectively. Choice experiment results show that WTP varies from 0% to 26.6% depending on outage scenarios, highlighting the significant seasonal sensitivity of residential outage costs. These findings provide critical insights for policymakers seeking to design a more reliable electricity market aligned with net-zero objectives. By incorporating residential Value of Lost Load into electricity market planning, governments can better incentivize investments in flexibility and resilience, thereby mitigating outage risks in future low-carbon power systems.

Quantifying the social costs of power outages and restoration disparities across four U.S. hurricanes

Residential outage cost estimation: Hong Kong

Effects of shading and blocking in linear Fresnel reflector field

Regardless of who carries out the work involved in a market research project, it is important that a clear brief is produced against which the subsequent work will be undertaken and judged. The research brief, which should be produced in both written and verbal form, is a key document and the starting-point. In its preparation it is important that the following questions are to the fore: What do we want to know? What will we do with the information when we get it? In this way clearly defined objectives can be set and adhered to.

In this paper, we develop a causal model to measure expected electricity outage costs in the industrial sector. Here, two popular econometric techniques, namely, unit root test and cointegration model was derived for modeling the production function. Cointegration was established between output (here sales value) and, respectively, electrical energy consumption, labors, and raw materials worth. Then by estimating the marginal energy production, outage cost is estimated. The model is applied to two industrial branches in Iran.

The costs of a power outage to a business can be substantial, so there is a growing interest in generators for reliable backup power. Businesses are either considering installing backup generators or redundant backup systems for added resilience against grid outages. This report discusses the costs and benefits of backup generator configurations, and compares the relative merits of grid-connected backup systems that enable financial benefits when the grid is functioning, versus backup-only systems that only generate energy for critical services when the primary grid is down. This report discusses how to assign value to the reliability of each system and the revenue streams related to backup generators.

Preface to the Second Edition. Acknowledgments. CHAPTER 1 Benefits of Electric Power and a History of theElectric Power Industry. 1.1 Societal Benefits of Electricity. 1.2 Origin of the Industry. 1.3 Development of the National Electric Power Grid. 1.4 The Golden Age. 1.5 Global Warming Crisis and Concerns about CarbonEmissions. 1.6 Restructuring, Competition, and the Industry OwnershipStructure. CHAPTER 2 Electric Power System. 2.1 Customers. 2.2 Sources of the Electric Energy Generation. 2.3 Delivery System. CHAPTER 3 Basic Electric Power Concepts. 3.1 Electric Energy. 3.2 Concepts Relating to the Flow of Electricity. 3.3 Characteristics of AC Systems. 3.4 Ohm's Law for Alternating Current. 3.5 Power in Alternating Current Circuits. 3.6 Power Flow. 3.7 Stability. CHAPTER 4 Electric Energy Consumption. 4.1 End Uses for Electricity. 4.2 Customer Classes. 4.3 Rate Classes. 4.4 Demand and Energy. 4.5 System Load. 4.6 Reactive Load. 4.7 Losses and Unaccounted-For Energy in the DeliverySystem. 4.8 Forecasts. CHAPTER 5 Electric Power Generation and Concerns AboutGreenhouse Gases. 5.1 Generation's Role. 5.2 Types of Generation. 5.3 Thermal Conversion: Using Fuel as the Energy Resource. 5.4 Thermal Conversion: Nonfuel Heat Sources. 5.5 Mechanical Energy Conversion. 5.6 Renewable Technologies and Greenhouse Gas Emissions. 5.7 Characteristics of Generating Plants. 5.8 Capital Cost of Generation. 5.9 Generator Life Extension. 5.10 Technology of Generation. 5.11 System Needs and Evaluation of Intermittent Resources. CHAPTER 6 Technology of the Electric TransmissionSystem. 6.1 Components. 6.2 HVAC. 6.3 Substations. 6.4 HVDC. 6.5 Advantages of AC over DC Operation. 6.5 Knowledge Required of Transmission Systems. CHAPTER 7 Distribution. 7.1 Function of Distribution. 7.2 Primary Distribution Feeders. 7.3 Distribution Capacity. 7.4 Losses. 7.5 Distribution Facility Ratings. 7.6 Metering. 7.7 Control of Distribution Voltages. 7.8 Distribution System Reliability. 7.10 Quality of Service. 7.11 Design of Distribution Systems. 7.12 Distributed Generation. 7.13 Operation of Distribution Systems. 7.14 Smart Grids and Microgrids. CHAPTER 8 Energy Storage and Other New Technologies. 8.1 Energy Storage. 8.2 Energy Storage Concepts and Technologies. 8.3 Smart Grid. 8.4 New Nuclear Plant Designs. 8.5 Carbon Sequestration and Clean Coal Technologies. 8.6 Superconductors. CHAPTER 9 Reliability. 9.1 Causes of Outages. 9.2 Costs of Power Outages. 9.3 Ways to Measure Reliability. 9.4 Planning and Operating a Reliable and Adequate PowerSystem. 9.5 Summary. CHAPTER 10 Physical Network: North American ElectricReliability Corporation (NERC) and Its Standards. 10.1 NERC as Electric Reliability Organization. 10.2 NERC Standards. 10.3 Development of Standards. CHAPTER 11 Physical Network: Operation of the ElectricBulk Power. 11.1 Balancing Authorities. 11.2 Reliability Coordinators. 11.3 Transmission Operators. 11.4 Voltage and Reactive Control. 11.5 Emergencies. 11.6 Information Exchange. CHAPTER 12 Physical Network: Planning of the ElectricBulk Power System. 12.1 Planning Standards. 12.2 Generation Planning. 12.3 Transmission Planning. 12.4 Least Cost Planning. 12.5 New Planning Environment. CHAPTER 13 Regulatory Network: Legislation. 13.1 Pricing and Regulation. 13.2 Federal Legislation. 13.3 Federal Utility Holding Company Act (PUHCA). 13.4 Federal Power Act. 13.5 Other 1930 Federal Laws. 13.6 Department of Energy Organization Act. 13.7 Public Utility Regulatory Policies Act (PURPA). 13.8 Energy Policy Act of 1992 (EPAct02). 13.9 Energy Policy Act of 2005 (EPAct05). 13.10 Energy Independence and Security Act of 2007. 13.11 Environmental Laws. 13.12 2009 American Recovery and Reinvestment Act. CHAPTER 14 Regulatory Network: Regulators. 14.1 Regulators. CHAPTER 15 Information, Communication, and ControlNetwork and Security. 15.1 Smart Grid. 15.2 Financial and Business Operations. 15.3 System Operations. 15.4 Distribution Operations. 15.5 Cyber Security. 15.6 Nuclear Plant Security. CHAPTER 16 Fuel and Energy Network. 16.1 Resource Procurement. 16.2 Fuel Transportation. 16.3 Fuel Diversity. 16.4 Fossil Fuels Used. 16.5 Renewable Energy. 16.6 Fuel Purchasing. 16.7 Emission Rights. CHAPTER 17 Business Network: Market Participants. 17.1 Investment and Cost Recovery. 17.2 Changing Industry Structure. 17.3 New Structures. 17.4 New Corporate Ownership. CHAPTER 18 Money Network: Wholesale Markets. 18.1 Energy Markets. 18.2 Transmission. 18.3 Customer Late Issues. 18.4 Market versus Operational Control. 18.5 Market Power Issues. 18.6 Future. CHAPTER 19 Professional and IndustryOrganizations. 19.1 Professional Organizations. 19.2 Industry Associations. 19.3 Public Interest Groups. 19.4 Research Organizations. Index.