The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a new modeling framework for analysis of impact and scheduling of price-responsive as well as controllable loads in a three-phase unbalanced distribution system. The price-responsive loads are assumed to be linearly or exponentially dependent on price, i.e., demand reduces as price increases and vice versa. The effect of such uncontrolled price-responsive loads on the distribution...
Demand response is a key solution in smart grid to address the ever-increasing peak energy consumption. With multiple utility companies, users will decide from which utility company to buy electricity and how much to buy. Consequently, how to devise distributed real-time demand response in the multiseller̈Cmultibuyer environment emerges as a critical problem in future smart grid. In this paper, we...
Time-shiftable loads have recently received an increasing attention due to their role in creating load flexibility and enhancing demand response and peak-load shaving programs. In this paper, we seek to answer the following question: How can a time-shiftable load, that itself may comprise of several smaller time-shiftable subloads, submit its demand bids to the day-ahead and real-time markets so as...
Paying for load reductions results in a market, where the amount of resources sold is less than the amount of resources bought. To resolve this imbalance, ISOs must allocate the cost of compensating demand response to those who benefit from reduced LMPs. Current cost allocation methods are based on each energy buyer's load share. In an uncongested network, this results in a “fair” allocation of costs,...
This work describes a methodology for informing targeted Demand-Response (DR) and marketing programs that focus on the temperature-sensitive part of residential electricity demand. Our methodology uses data that is becoming readily available at utility companies - hourly energy consumption readings collected from “smart” electricity meters, as well as hourly temperature readings. To decompose individual...
Demand response (DR) has proved to be an inevitable part of the future grid. Much research works have been reported in the literature on the benefits and implementation of DR. However, little works have been reported on the impacts of DR on dynamic performance of power systems, specifically on the load frequency control (LFC) problem. This paper makes an attempt to fill this gap by introducing a DR...
This paper presents a hierarchical demand response (DR) bidding framework in the day-ahead energy markets which integrates customer DR preferences and characteristics in the ISO's market clearing process. In the proposed framework, load aggregators submit aggregated DR offers to the ISO which would centrally optimize final decisions on aggregators' DR contributions in wholesale markets. The hourly...
The objective of this paper is to propose a human expert-based approach to electrical peak demand management. The proposed approach helps to allocate demand curtailments (MW) among distribution substations (DS) or feeders in an electric utility service area based on requirements of the central load dispatch center. Demand curtailment allocation is quantified by taking into account demand response...
The presence of high levels of Renewable Energy Resources (RES) and especially wind power production poses technical and economic challenges to System Operators, which under this fact have to procure more Ancillary Services (AS) through various balancing mechanisms, in order to maintain the generation-consumption balance and to guarantee the security of the grid. Traditionally, these critical services...
The demand of electricity keeps increasing in this modern society and the behavior of customers vary greatly from time to time, city to city, type to type, etc. Generally, buildings are classified into residential, commercial and industrial. This study is aimed to distinguish the types of residential buildings in Singapore and establish a mathematical model to represent and model the load profile...
Distribution microgrids are being challenged by reverse power flows and voltage fluctuations due to renewable generation, demand response, and electric vehicles. Advances in photovoltaic (PV) inverters offer new opportunities for reactive power management provided PV owners have the right investment incentives. In this context, reactive power compensation is considered here as an ancillary service...
California has adopted numerous policies to achieve a transition to reliance on sustainable, renewable energy sources. Ongoing changes in the supply resources and demand characteristics that are supported by the grid present both challenges and opportunities for meeting the challenges. However, certain barriers may currently inhibit these resources from achieving their potential.
The smart grid vision has resulted in many demand side innovations such as nonintrusive load monitoring techniques, residential micro-grids, and demand response programs. Many of these techniques need a detailed residential network model for their research, evaluation, and validation. In response to such a need, this paper presents a sequential Monte Carlo (SMC) simulation platform for modeling and...
Integration of renewable energy sources and demand response poses new challenges to system operators as they increase the uncertainty of the power supply and demand. Recently, robust optimization techniques are applied to the unit commitment problem with uncertainty as an alternative to the stochastic programming approaches. However, it remains challenging to solve the robust unit commitment model...
The objective of this paper is to present some discussions about data treatment in the new environment existing in the power systems and smart-grids. The paper presents some aspects of the data acquisition, communication, and security, and data amount, management, and mining. In this paper, some ideas are proposed to inspire discussions about the above themes. The goal of these discussions is to provide...
In view of China's national conditions, this paper put forward a novel strategy for the maximization of renewable energy consumption, with collaborative controlling between the transmission network and the distribution network. This strategy took the local distribution network as a flexible and adjustable electric source, which played an active role in the consumption activity of the large-scale renewable...
Data centers are becoming a significant energy consumer. Server workload, cooling, and supporting infrastructure represents large loads for the grid. This paper intends to present a comprehensive literature review that account for generation, loads, storage, and topology of data centers. It is shown that green data centers are emerging which incorporate renewable energy sources to cap their carbon...
This paper aims to develop a management method considering load demand for electric vehicle charging. The method developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes have proposed to determine optimal demand shifting so that charging costs and demands can possibly be managed. The time of use electricity rate has been put into...
Demand response aims at utilizing flexible loads to operate power systems in an economically efficient way. A fundamental question in demand response is how to conduct a baseline estimation to deal with increasing uncertainties in power systems. Unfortunately, traditional baseline estimation lacks the ability to characterize uncertainties due to their deterministic modeling. This deficiency often...
Charging control strategies can significantly alleviate the impact of electric vehicles (EVs) to power systems, as well as utilize the flexibility of EV charging to achieve extra benefits. This paper proposes an EV charging control strategy to achieve valley-filling using EV charging load. The strategy consists of system-level control and supporting control for the charging of individual EVs. The...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.