Economic feasibility analysis and operational testing of a community energy storage system

Knueven, Ben; Ostrowski, James; Ollis, Ben; Irminger, Philip; Starke, Michael; Herron, Andrew; King, Daniel J.; Xiao, Bailu; Xue, Yaosuo; Karlson, Peter; Labaza, Christine; Maxwell, David; Thamibiappah, Seelan; Valencia, Pablo Pico; Massin, Sebastien

doi:10.1109/ecce.2016.7855063

Cited by 3 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the computational experiments in this article, we use η = 0.9 [29], and values of R t from the Electric Reliability Council of Texas (ERCOT) for the year 2012 [15,56]. Table 1 presents the hourly marginal selling prices.…”

Section: Data Sourcesmentioning

confidence: 99%

Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system

Singh

Knueven

2021

J Glob Optim

View full text Add to dashboard Cite

We develop a stochastic optimization model for scheduling a hybrid solar-battery storage system. Solar power in excess of the promise can be used to charge the battery, while power short of the promise is met by discharging the battery. We ensure reliable operations by using a joint chance constraint. Models with a few hundred scenarios are relatively tractable; for larger models, we demonstrate how a Lagrangian relaxation scheme provides improved results. To further accelerate the Lagrangian scheme, we embed the progressive hedging algorithm within the subgradient iterations of the Lagrangian relaxation. We investigate several enhancements of the progressive hedging algorithm, and find bundling of scenarios results in the best bounds. Finally, we provide a generalization for how our analysis extends to a microgrid with multiple batteries and photovoltaic generators.

show abstract

Section: Data Sourcesmentioning

confidence: 99%

Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system

Singh

Knueven

2021

J Glob Optim

View full text Add to dashboard Cite

show abstract

“…For grid-scale ESS (i.e., megawatt-scale), use cases have focused on energy arbitrage and provisioning of ancillary services [5] with complementary optimization strategies that focus on market bidding strategies. Other use cases under investigation include those that focus more on distributed energy storage technologies, behind the meter (BTM) energy, and community ESSs [6] [7][8]- [9]. For these ESSs, utility time-of-use (TOU) mechanisms have been the primary target value stream in conjunction with reliability and resilience services.…”

Section: Introductionmentioning

confidence: 99%

Optimal Operation of Integrated PV and Energy Storage Considering Multiple Operational Modes With a Real-World Case Study

Zandi,

Starke,

Winstead

et al. 2023

IEEE Access

Self Cite

View full text Add to dashboard Cite

In the past decade, substantial investments have been made in researching and developing concepts and technologies to support the smart grid, renewable integration, and grid-interactive buildings. Adaptation of integrated solar photovoltaics with energy storage is increasing in residential buildings as consumers and utilities are becoming aware of their economic benefits and resilience benefits. Effective integration and control of these systems with other building loads is critical for providing load flexibility to improve building energy efficiency, reduce carbon footprint, and support grid resiliency. In recent years vendors are shifting towards device-level optimization and defining more sophisticated operational modes for controlling energy storage systems rather than charge and discharge power. As a result, optimization techniques must encompass the characteristics of these modes and their interactions with other system disruptions and attributes. This complexity gives rise to a nonlinear optimization problem that cannot be effectively addressed by an open-source solver and is impractical to implement in real-world scenarios. In this paper, we designed and evaluated a linear multi-objective model-predictive control optimization strategy for integrated photovoltaic and energy storage systems in residential buildings by using manufacturer-defined operational modes. The optimization goal is to minimize the power-purchasing cost from the grid and maximize the power selling cost to the grid. We developed a generalized method to keep the optimization linearized, even with operational modes consideration while coupling the modes with the overall system charging and discharging power. Our simulation results were aligned with realworld measurements and validated the linearized optimization formulation for each operational mode and for the economic use-case. The optimization results for the economic use-case demonstrated that the power associated to grid charge is mostly larger than the grid discharge power which means the optimization tried to maximize the power selling to the grid when the price is high and avoid power purchasing from the grid during high price.

show abstract

Residential (Secondary-Use) Energy Storage System with Modular Software and Hardware Power Electronic Interfaces

Starke

Chinthavali

Zheng

et al. 2019

2019 IEEE Energy Conversion Congress and Exposition (ECCE)

View full text Add to dashboard Cite

Economic feasibility analysis and operational testing of a community energy storage system

Cited by 3 publications

References 6 publications

Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system

Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system

Optimal Operation of Integrated PV and Energy Storage Considering Multiple Operational Modes With a Real-World Case Study

Residential (Secondary-Use) Energy Storage System with Modular Software and Hardware Power Electronic Interfaces

Contact Info

Product

Resources

About