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Electric and Gas Utility Rates for Commercial and Industrial Customers
Published in Stephen A. Roosa, Steve Doty, Wayne C. Turner, Energy Management Handbook, 2020
R. Scott Frazier, Lynda J. White, Richard A. Wakefield, Jairo A. Gutierrez
As described above, electric utilities must be able to meet the peak demand—the period when the greatest number of customers and large loads are simultaneously demanding service. Gas utilities must also be responsive to daily or hourly peak use of gas. In either case, the utility will need to generate or purchase enough power to cover its firm customers’ needs at all times. Demand-related costs are dependent upon overall system requirements. Demand costs can be allocated in many different ways, but utilities tend to allocate on-peak load. Included in these costs are the capital and operating costs for production, transmission, equipment (e.g., transformers) and storage (in the case of gas utilities) that vary with demand requirements. Essentially, equipment must be oversized and operated for the peak demand scenarios.
An Overview of Smart Grid in Protection Perspective
Published in Ramesh Bansal, Power System Protection in Smart Grid Environment, 2019
The application of smart meters and communication facilities can be deliberately used by the utilities to inform numerous customers that connect to their networks how to utilize electricity economically. This allows peak curtailment when the tariff of electricity is high during the peak demand periods and encourages a high power demand during the off-peak periods [26]. It motivates consumers to consume less electricity during peak load demand periods by communicating directly to them about the high price premium of consuming a large quantity of electricity at peak periods [18]. The objective of smart grid is accomplished by reducing the power consumption of customers, thus preventing the power system from being overloaded. Apart from this, it also notifies the customers when to charge their electric vehicles at the charging stations and adjusts the temperature setting of air conditioning based on the tariff regimes introduced by the utilities [22]. The application of smart grid also reduces the spanning reserve that utilities use as a standby unit with the application of central control, power management services and the free market mechanism.
Instruments and Meters
Published in Joseph E. Fleckenstein, Three-Phase Electrical Power, 2017
Although smart meters present a means whereby a utility can induce customers to shift usage to off-peak times, the meters alone cannot accomplish this end. The reductions can take place only if a utility combines a program of incentives in combination with the measurement capabilities of the smart meters. The most common method used by utilities to reduce peak load is to offer reduced rates for electric consumption during off-peak times. This feature of the smart meters simulates to some extent the earlier TOU (time-of-use) programs offered by utilities. The TOU programs were used by utilities to provide reduced energy rates during off-peak periods.
Novel Metaheuristic Optimizers Based Load Shifting and Flexible Load Curve Techniques for Demand-side Load Management
Published in Smart Science, 2023
Ashokkumar Parmar, Pranav Darji
In this analysis, demand-side load management has been performed in the deregulated environment using load-shifting and flexible load curve demand-side load management techniques. The primary objectives are to limit consumers’ electricity costs and achieve peak load reduction (i.e. PAR) by incentivizing customers to change their energy consumption patterns during peak hours. System efficiency can be increased by achieving these objectives. A target load curve is constructed according to the market prices to achieve the aforementioned objectives. The target curve load has been set inversely proportional to the market price to reduce the overall cost. The day-ahead predicted consumption curve is shifted toward the target curve by using the aforementioned two demand-side load management techniques. Furthermore, demand-side load management flattens the load curve to improve the system’s reliability.
Examination of optimum benefits of customer and LSE by incentive and dynamic price-based demand response
Published in Energy Sources, Part B: Economics, Planning, and Policy, 2020
Muhammad Hussain, Yan Gao, Sherehe Semba, Mehmooda Irshad, Faluk Shair
To match the peak demand and the seasonal power availability, utilities are forced to maintain a substantial amount of underutilized power capacity (Kirschen 2003a). The power fluctuation from renewable sources could cause a rapid jump in the electricity price . As a result, utilities may suffer financial losses when they are forced buying the electricity at higher prices and sell at lower prices in order to maintain the system security . From the discussion above, it can be seen that peak load puts more pressure on network infrastructure, which consequently boosts the electricity price at retail market. Moreover, the renewable generations such as wind and solar are intermittent sources of energy and may not be available at peak demand. . The intermittent energy may further expose the utilities with financial risk and jeopardize the power system.
Mitigating peak load and heat stress under heatwaves by optimizing adjustments of fan speed and thermostat setpoint
Published in Journal of Building Performance Simulation, 2023
Zhujing Zhang, Kevin J. Kircher, Yuan Cai, Jonathon G. Brearley, David P. Birge, Leslie K. Norford
As an alternative to building renovations, optimizing the operation of air conditioning systems can reduce peak load (Celik et al. 2017; Jeddi, Mishra, and Ledwich 2021). Scheduling, a form of energy management, could reduce renovation costs and efforts, but generally requires some investment in sensing, communication, and controls. Corbin, Henze, and May-Ostendorp (2013) describe a model predictive control method that generates hourly cooling setpoints to minimize the daily energy cost of a commercial building. Price-based energy management can reduce peak load (Xu et al. 2015; Torriti 2012). However, these approaches often under-emphasize the thermal comfort of building occupants, a critical metric under heatwaves.