Potential benefits of implementing load control

Ilić, Marija; Black, Jason; Watz, J.L.

doi:10.1109/pesw.2002.984981

Cited by 62 publications

(34 citation statements)

References 3 publications

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“…The potential for price-responsive demand is large [21], but several factors currently prevent its implementation. The lack of the technical infrastructure (metering and communications) currently prevents demand from participating in real time markets (or even day ahead).…”

Section: Future Industrymentioning

confidence: 99%

Distributed electric power systems of the future: Institutional and technological drivers for near-optimal performance

Ilić

Black

Prica

2007

Electric Power Systems Research

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Section: Future Industrymentioning

confidence: 99%

Distributed electric power systems of the future: Institutional and technological drivers for near-optimal performance

Ilić

Black

Prica

2007

Electric Power Systems Research

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“…Buildings account for 40% of all electricity consumed in the United States, with half that figure attributed to heating, ventilation and air conditioning (HVAC) [11,12]. There is an extensive literature on adjusting the timing of air conditioner operation in commercial buildings to reduce demand during high-cost times and increase it in low-cost times [13][14][15][16][17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

“…This strategy uses the building's thermal mass as a form of thermal storage that has the same effect as an electric battery, without encroaching on the comfort of the occupants [17][18][19][20][21][22][23]. Among these algorithms, one of the most advanced, introduced by Corbin, Henze, and May-Ostendorp [24].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Control of Air Conditioning Improves Cost, Comfort and System Energy Balance

Izawa¹,

Fripp²

2018

Preprint

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A new model predictive control (MPC) algorithm is used to select optimal air conditioning setpoints for a commercial office building, considering variable electricity prices, weather, occupancy and lighting. This algorithm, Cost-Comfort Particle Swarm Optimization (CCPSO), is the first to combine a realistic, smooth representation of occupants' willingness to pay for thermal comfort with a bottom-up, non-linear model of the building and air conditioning system under control. We find that using a quadratic preference function for temperature can yield solutions that are both more comfortable and lower-cost than previous work that used a "brick wall" preference function with no preference for further cooling within an allowed temperature band and infinite aversion to going outside the allowed band. Using historical pricing data for a summer month in Chicago, CCPSO provided a 3% reduction in costs vs. a "brick-wall" MPC approach with similar comfort and 13% reduction in costs vs. a standard night setback strategy. CCPSO also reduced peak-hours demand by 3% vs. the "brick-wall" strategy and 15% vs. standard night-setback. At the same time, the CCPSO strategy increased off-peak energy consumption by 15% vs. the "brick-wall" strategy. This may be valuable for power systems integrating large amounts of renewable power, which can otherwise become uneconomic due to saturation of demand during off-peak hours. Keywords: HVAC model predictive control, demand response, EnergyPlus, particle swarm optimization (PSO), renewable energy, smart grids MSC: 49M37, 65K05, 90-04, 90B35, 90B50, 90C29, 90C56, 90C90, 91B08, 91B10, 91B26, 91B42, 91B74

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“…Many studies have analyzed different control strategies for individual air-conditioning equipments [11][12][13][14]. This paper focuses on the evaluation of different control strategies that can be implemented in the developed ECMS for HVAC split devices installed in premises of the UPV developed in order to get an optimal strategy to apply throughout the whole University.…”

Section: Introductionmentioning

confidence: 99%

Application of an energy management and control system to assess the potential of different control strategies in HVAC systems

Escrivá-Escrivá

Segura-Heras

Alcázar-Ortega

2010

Energy and Buildings

108

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ElsevierEscrivá-Escrivá, G.; Segura Heras, I.; Alcázar-Ortega, M. (2010). Application of an energy management and control system to assess the potential of different control strategies in HVAC systems. Energy and Buildings. 42(11):2258-2267. doi:10.1016/j.enbuild.2010 AbstractThe significant and continuous increment in the global electricity consumption is asking for energy saving strategies. Efficient control for heating, ventilation and air-conditioning systems (HVAC) is the most cost-effective way to minimize the use of energy in buildings. In this framework, an energy management and control system (EMCS) has been developed to schedule electricity end-uses in the campus of the Universidad Politécnica de Valencia (UPV), Spain. This paper presents an evaluation performed by using the EMCS of different control strategies for HVAC split systems. It is analyzed the effect of different schedules for a common air-conditioning device and demand response strategies are tested in several situations. The economic saving is calculated taking into account the electricity contract clauses.Finally, a test is made for the control of a group of similar devices in order to reduce the maximum peak power in consumption and to obtain a flexible load shape with the HVAC loads.The studies are then extrapolated to a larger system, the whole University campus, for which energy and economic savings are quantified.

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Potential benefits of implementing load control

Cited by 62 publications

References 3 publications

Distributed electric power systems of the future: Institutional and technological drivers for near-optimal performance

Distributed electric power systems of the future: Institutional and technological drivers for near-optimal performance

Multi-Objective Control of Air Conditioning Improves Cost, Comfort and System Energy Balance

Application of an energy management and control system to assess the potential of different control strategies in HVAC systems

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