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Energy management through Demand Response (DR) is one of the effective techniques, which can be implemented in a way beneficial to both the consumer and the utility in a smart grid environment. Generally, the maximum demand allowed by the utility and the penalty imposed, if used above the allowed limit, are taken as major parameters for the energy management in DR programs. This paper proposes a time...
In future smart grids, large-scale deployment of distributed energy resources (DERs) and renewable energy sources (RES) is expected. In order to integrate a high penetration level of DERs and RES in the grid while operating the system safely and efficiently, new control methods for power system operations are in demand so that the flexibility of the responsive assets in the grid can be further explored...
In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identified to be hosting capacity improvement, high reliable operation and cost effective network management. Based...
The smart grid is the solution for the outdated current state of the power grid. An Energy Provider (EP) and Energy User (EU) are both looking to achieve savings. A Real-Time (RT) Demand Response (DR) pricing mechanism can reduce an EUs' bill and at the same time reduce the overall peak demand and Peak to Average Ratio (PAR) so that EP save their cost. In this paper, we will provide a model that uses...
Flexibility is a key enabler for the smart grid, required to facilitate Demand Side Management (DSM) programs, managing electrical consumption to reduce peaks, balance renewable generation and provide ancillary services to the grid. Flexibility analysis is required to identify and quantify the available electrical load of a site or building which can be shed or increased in response to a DSM signal...
This paper proposes a robust demand-side control algorithm in a smart grid environment for heating, ventilation and air conditioning (HVAC) systems. A robust model predictive control (RMPC) scheme in a receding horizon fashion is deployed, which optimizes electricity cost and capacity market participation of the HVAC system, while satisfying comfort and operational constraints of the building and...
This paper discusses using signal processing to assist in processing of information for the smart grid. This consists of getting information about the electrical grid and environment via sensor networks, interpreting information received via signal processing and machine learning, and then using the information to make intelligent decisions about the grid using control and optimization algorithms...
The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval....
Traditional power grids lack an appropriate infrastructure to link the involved stakeholders and domains for balancing energy demand and supply. The transmission infrastructure is hierarchically oriented with active bulk generators and passive consumers. Therefore, a bidirectional communication system is needed, which is an essential component of the future smart grid. However, a set of requirements...
Smart grids offer an indisputable business opportunity for system operators and energy traders to engage in demand response programs. Hereby these actors may profit from trading flexibility provided at the prosumer side on the energy markets. This paper discusses the system design challenges for an information and communication technology system infrastructure facilitating DR for residential prosumers...
This paper proposes a Mixed Integer Linear Programming (MILP) framework to accommodate more Building Integrated Photovoltaic (BIPV) System in distribution networks. The proposed framework is introduced to efficiently manage energy consumption of building equipped with a Battery Energy Storage System (BESS) and BIPV system. Models of distributed energy resources (DERs) in a building are investigated...
Mixed integer programming (MIP) problems are formulated in this paper to model the operation of residential Heating Ventilation and Air-Conditioning Systems (HVAC). The objective is to minimize the total cost of the HVAC energy consumption under varying electricity prices. A simplified model of a space cooling system considering thermal dynamics is adopted. The optimization problems consider 24 hour...
We propose an enhancement of OpenADR (Automated Demand Response) communication for flexible and fast ADR aggregation using the TRAP mechanism of newly developed IEEE1888 facility information access protocol. The TRAP mechanism makes it possible for an OpenADR server to push an occurrence of specific event for which the "TRAP" has been previously set by each client. Each client such as an...
We develop a mathematical programming approach to schedule meetings in an organization over a fixed period of time, while minimizing the wasted energy and possibly achieving more balanced demand distribution. The problem is formulated as a mixed integer linear program subject to a set of realistic constraints including people's available time slots and energy consumption characteristics of the meeting...
Estimation of end-use load impacts plays an important role in effective power distribution in a smart grid. This paper describes a framework for estimating end-use based demand side management (DSM) impacts of a commercial building. A hybrid combination of actual measurements (for a period of few months, on five minute basis) and estimation of operation schedules is used for segregating the load profile...
The paper focuses on modeling and simulation of the stochastic nature of a city that has implemented the smart grid and demand response paradigm. A stochastic model has been developed in Anylogic using agent based and system dynamics modeling. The city model consists of over 1000 smart building agents with controllable loads, local energy storage and local renewable energy source (photovoltaic). After...
This paper evaluates the performance of a demand response (DR) system, installed in the remote community of Hartley Bay, British Columbia, which is used to reduce fuel consumption during periods of peak loads and poor fuel efficiency. The DR system, installed to shed load during these periods, is capable of shedding up to 15 per cent of maximum demand by adjusting wireless variable thermostats and...
The promise and hype surrounding the Smart Grid far exceeds its current capabilities. In no area is this truer than with Demand Response (DR) programs for the commercial building sector, which is responsible for 20 percent of energy demand and emissions in the United States. These concentrated pools of demand are a nightmare for ever-more strained utility grids, especially in major cities. As a result,...
In this paper we present the Active House industrial demonstrator, exhibited at the ELFACK fair (May 2011), which demonstrates the role of home/building automation systems in energy management at home. Moreover, we introduce the Active House deployment architecture in the smart grid that provides the basis for the industrial demonstrator. We discuss the demonstrator as the proof-of-concept that allows...
The increased focus on reduction of greenhouse gas emissions can be achieved in part by interactively integrating residential electricity production from renewable resources while giving customers incentives to shift and reduce electricity consumption during times of production with high CO2 emissions. In this paper we present the Active House deployment architecture in the smart grid, which has been...
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