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To improve forecasting accuracy for baseline load and load impact from demand response resources, this paper develops three innovative statistical models. These models are regression spline fixed effect model, fixed effect change point model and mixed effect change point model. The models developed are applied to forecast baseline load and load impact from air conditioning cycling demand response...
A microgrid (MG) is a secondary (low voltage) network capable of supplying part or all the power needed by the connected users. It is composed by solar panels, energy storage devices, diesel plants, microturbines, and all other distributed generation technologies available for connecting to the low voltage grid. In this paper, a MG model is presented to minimize operation cost during a 24-hour period...
This paper proposes a distributed control system for flexible loads using a recommendation mechanism. The recommendation mechanism is implemented at the aggregator level and coordinates the flexible loads through smart controllers based on a ranking algorithm. In the existing demand response system, the aggregator broadcasts control sequences to flexible loads and collect schedules from them. The...
The variation of power consumption on the demand side is a challenging issue for the real time balancing of power systems. To tackle this problem, various demand response programs have been introduced to help the Independent System Operator (ISO) in mitigating the demand fluctuation. Typically, they include demand curtailment programs and price responsive demand programs. This paper presents a scheduling...
The Intermittent Renewable Management Pilot - Phase 2 was designed to study the feasibility of distributed demand-side resources to participate into the California Independent System Operator (CAISO) wholesale market as proxy demand resources. The pilot study focused on understanding the issues related with direct participation of third-parties and customers including customer acceptance; market transformation...
In this paper, the problem of energy resource trading in an Energy Internet context is studied. By collecting information about energy bidding of multiple microgrids, an aggregator aims to maximize each microgrids' profit while minimizing the risk of overbidding for renewable energy resources trading-based microgrids. A novel stochastic game-theoretic model and the conditional value-at-risk (CVaR)...
This paper presents a comprehensive low-voltage residential load model of price-based demand response (DR). High-resolution load models are developed by combing Monte Carlo Markov chain bottom-up demand models, hot water demand models, discrete state space representation of thermal appliances, and composite time-variant electrical load models. Price-based DR is then modeled through control algorithms...
The supply of electrical energy is being increasingly sourced from renewable generation. The variability and uncertainty of renewable generation, compared to a dispatchable plant, is a significant dissimilarity of concern to the traditionally reliable and robust power system. This change is driving the power system towards a more flexible entity that carries greater amounts of reserve. For congestion...
Demand side attracts large attention in smart grid for energy efficiency and demand response, and thermostatically controlled appliances (TCAs) are the most potential resources. TCAs scheduling is a basic tool to utilize the flexibility of TCAs to achieve payment savings or peak reduction for users. Current research usually models the users' comfort a hard constraint in TCAs scheduling, which may...
This paper proposes an oligopolistic model for a wind power producer (WPP) with a market power to compete with other Gencos and take part in day-ahead, intraday and balancing markets. In order to model the mentioned oligopoly markets from WPP's viewpoint, a bi-level optimization framework is proposed based on multi-agent system and incomplete information game theory. In this context, the WPP participates...
Many existing issues pertaining to power sector such as-demand response management, theft detection, outage management etc. can be solved efficiently with grid modernization. Out of these, demand response is one such issue which affects the overall grid stability. One way of managing demand response is to balance the load in smart grid (SG). In this paper, a novel scheme for handling the demand response...
Multiple-voltage-region control, in which the bus voltage range is divided into several regions, is usually implemented for DC microgrid operation in distributed manner. Voltage/power droop relationships are imposed for active power sharing among slack terminals. Conventionally, threshold voltages for voltage region partition are determined with fixed percentage of variation around the nominal value,...
The problem of centralized scheduling of large scale charging of electric vehicles (EVs) with demand response options is considered. A stochastic dynamic programming model is introduced in which the EV charging service provider faces stochastic demand, convex non-completion penalties, and random demand response requirements. Formulated as a restless multi-armed bandit problem, the EV charging problem...
To fulfill demand response to a grid's control command, electric vehicles (EVs) are usually managed via a virtual power plant (VPP), and how to manage the EVs for optimal response is a key issue. Such a problem is defined as an optimal tracking problem (OTP) in the literature, and an improved OTP model considering network constraints is studied in this paper. In order to circumvent the computational...
In this paper we consider an active distribution network (ADN) that performs primary voltage control using real-time demand response via a broadcast low-rate communication signal. The ADN also owns distributed electrical energy storage. We show that it is possible to use the same broadcast signal deployed for controlling loads to manage the distributed storage. To this end, we propose an appropriate...
This paper investigates the fundamental issue of revenue adequacy in wholesale day-ahead electricity markets with the presence of standalone demand response providers (DRPs). In recent years, with the increasing need for flexibility to provide sustainable electricity services, standalone DRPs have emerged as a new form of market participants. Such providers serve as intermediate between ISOs and end-users,...
This paper presents a two-stage stochastic programming model for provision of flexible demand response (DR) based on thermal energy storage in the form of hot water storage and/or storage in building material. Aggregated residential electro-thermal technologies (ETTs), such as electric heat pumps and (micro-) combined heat and power, are modeled in a unified nontechnology specific way. Day-ahead optimization...
This paper proposes a real-time demand response potential evaluation (RTDRPE) method that is purely driven by smart meter data. Probabilistic behaviors of electricity consumers are learned from historical data based on Gaussian Mixture Model (GMM). Then, with GMM of each consumer, RTDRPE is conducted on both the individual level and the aggregated level, which facilitates DR-related and market-related...
As aging coal-fired capacity retires following EPA rules, some RTO/ISOs are facing tightening supply margins, and seldom-used emergency only resources such as Load Modifying Resource may have to be deployed. The injection of emergency capacity, however, can result in price depression, and the uneconomic price signals may further lead to participant actions that endanger reliable grid operations. It...
Smart Electrical Utilization System (SEUS) is one of the most important components of smart grid (SG). It's crucial to evaluate the efficiency, safety and demand response capability of power users in SEUS. Three categories of power user evaluation (PUE) indices are presented from the aspects of energy efficiency, safety monitoring and demand response. Taking into account the uncertainty of the user...
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