Spinning Reserve From Responsive Loads

Kirby, Brendan

doi:10.2172/885551

Cited by 135 publications

(102 citation statements)

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“…For system parameters not given in the test files, we randomly selected values in the following ranges: 4,5], and P max = 150MW.…”

Section: A Ieee 118 Bus Gridmentioning

confidence: 99%

“…Unlike most generation units, loads can respond to control signals almost instantaneously [5] and the development of advanced metering infrastructure (AMI) [6] has made real-time load control achievable if appropriate control signals are provided. Many control strategies such as [7]- [10] adjust loads based on local frequency, enabling loads to mimic the natural response of synchronous generators.…”

Section: Introductionmentioning

confidence: 99%

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A practical integration of automatic generation control and Demand Response

Shiltz

Annaswamy

2016

2016 American Control Conference (ACC)

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Abstract-For a power grid to operate properly, electrical frequency must be continuously maintained close to its nominal value. Increasing penetration of distributed generation, such as solar and wind generation, introduces fluctuations in active power while also reducing the natural inertial response of the electricity grid, creating reliability concerns. While frequency regulation has traditionally been achieved by controlling generators, the control of Demand Response resources has been recognized in recent smart grid literature as an efficient means for providing additional regulation capability. To this end, several control methodologies have been proposed recently, but various features of these proposals make their practical implementations difficult. In this paper, we propose a new control algorithm that facilitates optimal frequency regulation through direct control of both generators and Demand Response, while addressing several issues that prevent practical implementation of other proposals. In particular, i) our algorithm is ideal for control over a large, low-bandwidth network as communication and measurement is only required every 2 seconds, ii) it enables Demand Response resources to recover energy lost during system transients, and iii) it accommodates both measured disturbances and unmeasured disturbances. We demonstrate the viability of our approach through dynamic simulations on a 118-bus grid model.

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“…For system parameters not given in the test files, we randomly selected values in the following ranges: 4,5], and P max = 150MW.…”

Section: A Ieee 118 Bus Gridmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A practical integration of automatic generation control and Demand Response

Shiltz

Annaswamy

2016

2016 American Control Conference (ACC)

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“…The authors in [9] proposed a stochastic programming approach for reactive power scheduling of a microgrid considering the uncertainty of wind power. In [10], the authors presented that fast/emergency reserve can be provided by responsive loads such as residential and small commercial air conditioners. The control of residential heaters and pumps has been applied for managing daily peak demands in [11].…”

Section: B Literature Reviewmentioning

confidence: 99%

Active distribution networks planning with integration of demand response

Mokryani

2015

Solar Energy

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-This paper proposes a probabilistic method for active distribution networks planning with integration of demand response.Uncertainties related to solar irradiance, load demand and future load growth are modelled by probability density functions. The method simultaneously minimizes the total operational cost and total energy losses of the lines from the point of view of distribution network operators with integration of demand response over the planning horizon considering active management schemes including coordinated voltage control and adaptive power factor control. Monte Carlo simulation method is employed to use the generated probability density functions and the weighting factor method is used to solve the multi-objective optimization problem. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system. Index Terms -

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“…There is however the possibility that the operator would wish to see some acknowledgement of operation coming from the appliances that are providing the demand response. As an example, the LIPAedge demand response system in Long Island, New York, provides a fast reserve service by automatically controlling consumer's air conditioning units using programmable thermostats (Kirby, 2003). A two-way pager system is used to both control the thermostats, and to receive response and monitoring information from them.…”

Section: Fast Demand Responsementioning

confidence: 99%