Providing frequency regulation reserve services using demand response scheduling

Motalleb, Mahdi; Thornton, Matsu; Reihani, Ehsan; Ghorbani, Reza

doi:10.1016/j.enconman.2016.07.049

Cited by 83 publications

(46 citation statements)

References 38 publications

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“…Water heating is an energy-intensive load for households, which is shiftable in time without influencing the comfort levels. EWHs represent a significant load demand in modern grids and have a capacity for energy storage in form of heat [40]. The controllable residential EWH loads are used in this paper to model the implementation of DR programs through HEMS.…”

Section: Energy Storagementioning

confidence: 99%

Demand response implementation in smart households

Ghazvini

Soares

Abrishambaf

et al. 2017

Energy and Buildings

136

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Home energy management system (HEMS) is essential for residential electricity consumers to participate actively in demand response (DR) programs. Dynamic pricing schemes are not sufficiently effective for endusers without utilizing a HEMS for consumption management. In this paper, an intelligent HEMS algorithm is proposed to schedule the consumption of controllable appliances in a smart household. Electric vehicle (EV) and electric water heater (EWH) are incorporated in the HEMS. They are controllable appliances with storage capability. EVs are flexible energy-intensive loads, which can provide advantages of a dispatchable source. It is expected that the penetration of EVs will grow considerably in future. This algorithm is designed for a smart household with a rooftop photovoltaic (PV) system integrated with an energy storage system (ESS). Simulation results are presented under different pricing and DR programs to demonstrate the application of the HEMS and to verify its' effectiveness. Case studies are conducted using real measurements. They consider the household load, the rooftop PV generation forecast and the built-in parameters of controllable appliances as inputs. The results exhibit that the daily household energy cost reduces 29.5%-31.5% by using the proposed optimizationbased algorithm in the HEMS instead of a simple rule-based algorithm under different pricing schemes.

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Section: Energy Storagementioning

confidence: 99%

Demand response implementation in smart households

Ghazvini

Soares

Abrishambaf

et al. 2017

Energy and Buildings

136

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“…It has been proposed that the Cournot model may have several limitations. The amount of power produced by each aggregator in the Cournot model is very sensitive to the bidding price ( ) and small changes in the cost coefficient lead to sharp changes in the amount of demand repose quantities [8]. Some claim that market behavior would be better predicted by a SFE model, however this is more computationally intensive because both supply and cost functions must be determined.…”

Section: Supply Function Equilibriummentioning

confidence: 99%

“…The potential of DRs are studied in [4] in Hawaii in balancing supply and demand on an hourly basis. Much research has been completed concerning various energy market creation strategies employing DR resources [5,6,7,8] . In [9] effects of optimal DR resource reserve scheduling, on the system pollution cost were analyzed.…”

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confidence: 99%

A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture

et al. 2016

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With the increasing presence of intermittent renewable energy generation sources, variable control over loads and energy storage devices on the grid become even more important to maintain this balance. Increasing renewable energy penetration depends on both technical and economic factors. Distribution system consumers can contribute to grid stability by controlling residential electrical device power consumed by water heaters and battery storage systems. Coupled with dynamic supply pricing strategies, a comprehensive system for demand response (DR) exist. Proper DR management will allow greater integration of renewable energy sources partially replacing energy demand currently met by the combustion of fossil-fuels. An enticing economic framework providing increased value to consumers compensates them for reduced control of devices placed under a DR aggregator. Much work has already been done to develop more effective ways to implement DR control systems. Utilizing an integrated approach that combines consumer requirements into aggregate pools, and provides a dynamic response to market and grid conditions, we have developed a mathematical model that can quantify control parameters for optimum demand response and decide which resources to switch and when. In this model, optimization is achieved as a function of cost savings vs. customer comfort using systematic mathematical market analysis. Two market modeling approaches-the Cournot and SFEare presented and compared. A quadratic function is used for presenting the cost function of each DRA (Demand Response Aggregator) which will be used for settling down the DR market. Contribution of each aggregator and the final price are presented. Finally, we have also performed sensitivity analysis on the house cost function's coefficients for one of the aggregators. Index Terms-Demand response market, demand response schedulingAn experimental study was performed in [3] to analyze the effects of DLC-induced temperature cycles on university students' thermal sensation and thermal acceptability in lecture theatres as a worst case setting for DLC-induced thermal environments. The results show that operative temperature, vapor pressure, and the rate of temperature change are the three most important predictors during DLC events. DLC has been implemented successfully in several areas including Hawaii, where Hawaiian Electric has a total of 34,000 DLC customers, collectively providing 15 megawatts of controllable peak demand power. The potential of DRs are studied in [4] in Hawaii in balancing supply and demand on an hourly basis. Much research has been completed concerning various energy market creation strategies employing DR resources [5,6,7,8] . In [9] effects of optimal DR resource reserve scheduling, on the system pollution cost were analyzed. Shen et al. [10] provided an overview of how electricity market policy and regulation reforms have allowed DR to become a viable demand-side resource to address the energy and environmental challenges.Incentive-based control is implement...

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“…Along with environmental benefits of renewable energies, the advent of new technologies in the operation and control of renewable energy sources and the increasing demand for high quality and consistent supply result in more attentions to this type of energy sources [1][2][3][4]. Besides optimal operation of a power system in normal condition, controlling the system in faulty condition is one of the most challenging concerns [5][6][7]. Power quality is one of the most significant subjects in utilizing the distributed generation (DG) [8][9].…”

Section: Introductionmentioning

confidence: 99%

Back-to-back converter control of grid-connected wind turbine to mitigate voltage drop caused by faults

Hassanzadeh

Sangrody

Hajizadeh

et al. 2017

2017 North American Power Symposium (NAPS)

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Abstract-Power electronic converters enable wind turbines, operating at variable speed, to generate electricity more efficiently. Among variable speed operating turbine generators, permanent magnetic synchronous generator (PMSG) has got more attentions due to low cost and maintenance requirements. In addition, the converter in a wind turbine with PMSG decouples the turbine from the power grid, which favors them for grid codes. In this paper, the performance of back-to-back (B2B) converter control of a wind turbine system with PMSG is investigated on a faulty grid. The switching strategy of the grid side converter is designed to improve voltage drop caused by the fault in the grid while maximum available active power of wind turbine system is injected to the grid and the DC link voltage in the converter is regulated. The methodology of the converter control is elaborated in details and its performance on a sample faulty grid is assessed through simulation.Index Terms--Back-to-back (B2B) converter, direct-in-line wind turbine, permanent magnetic synchronous generator (PMSG), voltage drop, wind turbine control.

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Providing frequency regulation reserve services using demand response scheduling

Cited by 83 publications

References 38 publications

Demand response implementation in smart households

Demand response implementation in smart households

A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture

Back-to-back converter control of grid-connected wind turbine to mitigate voltage drop caused by faults

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