Grid-Scale Battery Energy Storage for Arbitrage Purposes: A Colombian Case

Penaranda, Andres F.; Romero-Quete, David; Cortés, Camilo

doi:10.3390/batteries7030059

Cited by 11 publications

(7 citation statements)

References 25 publications

(55 reference statements)

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“…-10 horas (e.g. 1000 MWh / 100 MW): considerando que es una capacidad de almacenamiento con buena relación beneficio/costo para sistemas de baterías en Colombia [22].…”

Section: Cálculo Del Arbitrajeunclassified

“…Varios investigadores han analizado extensamente los efectos de la incursión masiva de renovables en Colombia a largo plazo [16]- [21], pero con una resolución de meses o años, y sin evaluar el arbitraje. Otros han modelado con resolución horaria, pero con un horizonte de corto plazo sobre datos históricos [22]- [24], por lo que no han concluido sobre el arbitraje en el escenario futuro de alta penetración de renovables variables.…”

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Arbitrage in an Electricity Market with a High Share of Renewables

Delgado,

Franco

2024

IEEE Latin Am. Trans.

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“…-10 horas (e.g. 1000 MWh / 100 MW): considerando que es una capacidad de almacenamiento con buena relación beneficio/costo para sistemas de baterías en Colombia [22].…”

Section: Cálculo Del Arbitrajeunclassified

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Arbitrage in an Electricity Market with a High Share of Renewables

Delgado,

Franco

2024

IEEE Latin Am. Trans.

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“…Other models use the relationship between cycle DOD and lifetime cycles, which is usually provided by the manufacturer [8][9][10][11][12][13][14][15][16]. Since that relationship is usually non-linear, these curves are often linearized as piecewise functions, as in [17]. Another strategy consists of using fitting techniques, as in [18].…”

Section: Degradation Modellingmentioning

confidence: 99%

“…Arbitrary cost [17] DOD-based model with a piecewise function. Degradation is used only to calculate capacity loss.…”

Section: Capital Cost [5]mentioning

confidence: 99%

A Review on the Degradation Implementation for the Operation of Battery Energy Storage Systems

et al. 2022

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A naive battery operation optimization attempts to maximize short-term profits. However, it has been shown that this approach does not optimize long-term profitability, as it neglects battery degradation. Since a battery can perform a limited number of cycles during its lifetime, it may be better to operate the battery only when profits are on the high side. Researchers have dealt with this issue using various strategies to restrain battery usage, reducing short-term benefits in exchange for an increase in long-term profits. Determining this operation restraint is a topic scarcely developed in the literature. It is common to arbitrarily quantify degradation impact into short-term operation, which has proven to have an extensive impact on long-term results. This paper carries out a critical review of different methods of degradation control for short-time operation. A classification of different practices found in the literature is presented. Strengths and weaknesses of each approach are pointed out, and future possible contributions to this topic are remarked upon. The most common methodology is implemented in a simulation for demonstration purposes.

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“…Some of these recent advances are discussed below. The authors of [14] presented a grid-scale design for a BESS in the context of the Colombian electricity market. The authors showed a design of the BESS that considered the battery's lifespan and its operating characteristics regarding the state of charge and deep discharge.…”

Section: Introductionmentioning

confidence: 99%

An Energy Management System for the Optimal Operation of BESS in DC Microgrids: A Robust Convex Programming Approach

Gil-González

Montoya

Hernández³

2023

IEEE Access

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This paper uses a convex reformulation to deal with the robust, optimal energy management of battery energy storage systems (BESS) and renewable energies in DC microgrids. This relaxed mathematical model guarantees the global optimum regarding energy management problems, even when including uncertainties in demand and renewable energy. The proposed robust model can reach the best scheduling for energy management in worst-case cost scenarios while satisfying all requirements. Furthermore, a model for power transfer losses in converter devices is added to the proposed model by using a binary polynomial representation, which is convexified. This convexification is performed by transforming the nonlinear non-convex equations of the optimal energy management model into second-order cone constraints. Four scenarios implemented in the modified IEEE 123-bus radial distribution feeder are proposed in order to analyze the robust optimal energy management strategy: the deterministic model, demand uncertainty, uncertainty in solar and wind generators, and uncertainty in demand and solar and wind generators. In all scenarios, the energy management model reduces the total energy costs. Simulation scenario 1 showed daily operating costs of about US$ 4376.82, while simulation scenarios 2, 3, and 4, including demand and generation uncertainties, increased the daily operating costs by about US$ 5243.23 (19.79%), US$ 5072.23 (15.88%), and US$ 5738.75 (31.12%), respectively. Scenario 4 showed the highest costs, as it involves more uncertainty. Hence, the robust optimal energy management strategy dispatches more energy from conventional generators, increasing the operating costs to satisfy those of the worst case. INDEX TERMSBattery energy storage systems, energy management optimal, mixed-integer robust convex model, power transfer losses. Nomenclature Acronyms AC Alternating current. BESS Battery energy storage system. DC-MG Direct current microgrid. EMS Energy management system. MINLP Mixed-integer nonlinear programming. PV Photovoltaic. SoC State of charge (BESS). Parameters ∆t Duration of a single time period (s).dt k Deviation by renewable generation (or demand) from its nominal value at node k and time t. (W) ϕ k Charging efficiency of the BESS connected to node k (1/W). C k,t Conventional generator power purchase costs at node k and time t ($/kWh). c a0 Independent coefficient of the AC-DC converter polynomial loss model (W). c a1 Linear coefficient of the AC-DC converter polynomial loss model. c a2 Quadratic coefficient of the AC-DC converter poly-

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Grid-Scale Battery Energy Storage for Arbitrage Purposes: A Colombian Case

Cited by 11 publications

References 25 publications

Arbitrage in an Electricity Market with a High Share of Renewables

Arbitrage in an Electricity Market with a High Share of Renewables

A Review on the Degradation Implementation for the Operation of Battery Energy Storage Systems

An Energy Management System for the Optimal Operation of BESS in DC Microgrids: A Robust Convex Programming Approach

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