DER optimization to determine optimum BESS charge/discharge schedule using Linear Programming

Chouhan, Sridhar; Tiwari, Deepak; Inan, Hakan; Khushalani-Solanki, Sarika; Feliachi, A.

doi:10.1109/pesgm.2016.7741576

Cited by 22 publications

(19 citation statements)

References 10 publications

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“…The cost function for only lossy storage operation under NEM would have two-piecewise linear segments and it would be linear for equal buying and selling price of electricity with lossless battery. Authors in [15], [17] present this case in their LP formulation. This case could be obtained by simplifying the more general case depicted as P LP in Fig.…”

Section: Optimal Arbitrage With Linear Programmingmentioning

confidence: 99%

“…Authors in [12] observe that the energy arbitrage problem for storage is convex in nature and under the price-taker assumption the cost function will have a piecewise linear structure [5] and hence LP tools could be used. LP techniques for energy storage arbitrage have been used in several prior works: [13], [14], [15], [16], [17], [18], [19]. Authors in [17], [14], [19] consider storage operation in presence of timevarying electricity price.…”

Section: Introductionmentioning

confidence: 99%

“…However, in these formulations no renewable energy source or consumer load is assumed to be present. Authors in [15], [16] consider optimal scheduling of storage battery for maximizing energy arbitrage revenue in presence of distributed energy resources and variable electricity price. Formulations presented in [18], [13] consider storage performing arbitrage in a residential setting with inelastic load and local generation.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, in these formulations, optimal results cannot be guaranteed. Authors in [15], [17] do not consider energy storage charging and discharging efficiencies in the cost minimization, making it straight forward to apply LP. Authors in [18] consider a special case of optimization with zero-sum aggregate storage power output.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Storage Arbitrage under Net Metering using Linear Programming

Hashmi¹,

Mukhopadhyay²,

Bušíć³

et al. 2019

2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)

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We formulate the optimal energy arbitrage problem for a piecewise linear cost function for energy storage devices using linear programming (LP). The LP formulation is based on the equivalent minimization of the epigraph. This formulation considers ramping and capacity constraints, charging and discharging efficiency losses of the storage, inelastic consumer load and local renewable generation in presence of net-metering which facilitates selling of energy to the grid and incentivizes consumers to install renewable generation and energy storage. We consider the case where the consumer loads, electricity prices, and renewable generations at different instances are uncertain. These uncertain quantities are predicted using an Auto-Regressive Moving Average (ARMA) model and used in a model predictive control (MPC) framework to obtain the arbitrage decision at each instance. In numerical results we present the sensitivity analysis of storage performing arbitrage with varying ramping batteries and different ratio of selling and buying price of electricity.

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Section: Optimal Arbitrage With Linear Programmingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Storage Arbitrage under Net Metering using Linear Programming

Hashmi¹,

Mukhopadhyay²,

Bušíć³

et al. 2019

2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)

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“…First, there are papers that are solely based on simulations, as opposed to on real-world data and experiments as in this paper. They address different goals for energy storage operation, such as peak load shaving [9]- [11] or voltage control [12]. Among them, only [10] is related to customer-side energy storage operation, where the focus is on plug-in electric vehicles.…”

Section: Related Workmentioning

confidence: 99%

Customer-Side SCADA-Assisted Large Battery Operation Optimization for Distribution Feeder Peak Load Shaving

Taylor

Akhavan-Hejazi

Cortez³

et al. 2019

IEEE Trans. Smart Grid

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Abstract-Built upon real-world SCADA and other measurements of a featured utility-scale testbed, this paper addresses the participation of customer side battery energy storage in providing peak load shaving at a 12.47 kV distribution feeder. A stochastic optimization-based battery operation framework is developed that enables feeder load peak shaving under offline (day-ahead) as well as online (close-to-real-time) control settings. Both designs work through establishing a secured communications line to the utility's feeder-level SCADA system. Multiple field experiments are conducted, including a full day test with complete control of a 1 MWh / 200 kW battery system, as well as various numerical assessments based upon one year of real feeder data.

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