Optimal Coordination of Building Loads and Energy Storage for Power Grid and End User Services

He, Hao; Wu, Di; Lian, Jianming; Yang, Tao

doi:10.1109/tsg.2017.2655083

Cited by 130 publications

(49 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The regulation signal, u(t) acts as an input to the VB and must always lie within the time-varying power limits P − (t) and P + (t). This first-order VB model can be applied to characterize the aggregated flexibility of distributed energy resources (DERs) and many building loads [4,11,12], where the unknown VB parameters are denoted by vector φ = [a, C 1 , C 2 , x 0 , P − (t), P + (t)].…”

Section: Virtual Battery Characterizationmentioning

confidence: 99%

“…(8) and (9) in [15] or Eqs. (11) and (14) in [8]). Hence, we introduce the additional (nonconvex) cost on the optimization variable, s i by forcing it to take either 0 or 1 value which results in the following control design problem.…”

Section: Tracking Regulation Signalsmentioning

confidence: 99%

“…There exists several characterizations of aggregate flexibility using VB models in the literature [4,[11][12][13]. These works include characterizing a VB model for a wide range of systems from small residential TCLs to complex systems such as commercial building heating, ventilating, and air-conditioning (HVAC) loads.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identification and Validation of Virtual Battery Model for Heterogeneous Devices

Nandanoori

Chakraborty

Ramachandran

et al. 2019

2019 IEEE Power &Amp; Energy Society General Meeting (PESGM)

View full text Add to dashboard Cite

The potential of distributed energy resources in providing grid services can be maximized with the recent advancements in demand side control. Effective utilization of this control strategy requires the knowledge of aggregate flexibility of the distributed energy resources (DERs). Recent works have shown that the aggregate flexibility of DERs can be modeled as a virtual battery (VB) whose state evolution is governed by a first order system including self dissipation. The VB parameters (self dissipation rate, energy capacity) are obtained by solving an optimization problem which minimizes the tracking performance of the ensemble and the proposed first order model. For the identified first order model, time varying power limits are calculated using binary search algorithms. Finally, this proposed framework is demonstrated for different homogeneous and heterogeneous ensembles consisting of air conditioners (ACs) and electric water heaters (EWHs).

show abstract

Section: Virtual Battery Characterizationmentioning

confidence: 99%

Section: Tracking Regulation Signalsmentioning

confidence: 99%

See 1 more Smart Citation

Identification and Validation of Virtual Battery Model for Heterogeneous Devices

Nandanoori

Chakraborty

Ramachandran

et al. 2019

2019 IEEE Power &Amp; Energy Society General Meeting (PESGM)

View full text Add to dashboard Cite

show abstract

“…The relationship between room temperature and the power allocated to the appliance is shown in Eqs. (19) and (20). 1 1…”

Section: Air Conditioning Systemmentioning

confidence: 99%

“…Many studies have exploited MILP to solve this problem [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32]. Although these studies add a real contribution to the area, they have not tackled the computation time of the algorithm to solve the large problem efficiently.…”

mentioning

confidence: 99%

Heuristic Algorithm for Minimizing the Electricity Cost of Smart House

Arikiez¹,

Alotaibi²,

Gdhaidh³

et al. 2017

JEPE

View full text Add to dashboard Cite

This framework proposes a heuristic algorithm based on LP (linear programming) for optimizing the electricity cost in large residential buildings, in a smart grid environment. Our heuristic tackles large multi-objective energy allocation problem (large number of appliances and high time resolution). The primary goal is to reduce the electricity bills, and discomfort factor. Also, increase the utilization of domestic renewable energy, and reduce the running time of the optimization algorithm. Our heuristic algorithm uses linear programming relaxation, and two rounding strategies. The first technique, called CR (cumulative rounding), is designed for thermostatic appliances such as air conditioners and electric heaters, and the second approach, called MCR (minimum cost rounding), is designed for other interruptible appliances. The results show that the proposed heuristic algorithm can be used to solve large MILP (mixed integer linear programming) problems and gives a decent suboptimal solution in polynomial time.

show abstract