Expansion Planning Studies of Independent-Locally Operated Battery Energy Storage Systems (BESSs): A CVaR-Based Study

Saber, Hossein; Heidarabadi, Houman; Moeini‐Aghtaie, Moein; Farzin, Hossein; Karimi, Mohammad Reza

doi:10.1109/tste.2019.2950591

Cited by 28 publications

(23 citation statements)

References 29 publications

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“…In the presented model, apart from the electric energy storage systems, natural gas storage units are considered, too. According to the storage capacity, charge and discharge limitations, and also charge and discharge efficiency, the equations of electrical and natural gas storage units ∀t ∈ Ψ T can be shown as follows [34].…”

Section: ) Energy Storage Systemsmentioning

confidence: 99%

Network-Constrained Optimal Scheduling of Multi-Carrier Residential Energy Systems: A Chance-Constrained Approach

et al. 2021

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This paper presents a day-ahead scheduling approach for a multi-carrier residential energy system (MRES) including distributed energy resources (DERs). The main objective of the proposed scheduling approach is the minimization of the total costs of an MRES consisting of both electricity and gas energy carriers. The proposed model considers both electrical and natural gas distribution networks, DER technologies including renewable energy resources, energy storage systems (ESSs), and combined heat and power. The uncertainties pertinent to the demand and generated power of renewable resources are modeled using the chance-constrained approach. The proposed model is applied on the IEEE 33-bus distribution system and 14-node gas network, and the results demonstrate the efficacy of the proposed approach in the matters of diminishing the total operation costs and enhancing the reliability of the system.

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Section: ) Energy Storage Systemsmentioning

confidence: 99%

Network-Constrained Optimal Scheduling of Multi-Carrier Residential Energy Systems: A Chance-Constrained Approach

et al. 2021

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“…Faced with uncertainties of regulation income caused by power spot price fluctuations and the prediction difficulty, CVAR is often used to assess market gains under certain risk appetite conditions [29, 30]. Taking a loss cost function

f (x, y)

as an example, the model principle of CVaR is given below.…”

Section: Aggregate Regulation Strategy Under the Power Spot Marketmentioning

confidence: 99%

Aggregate regulation strategy of distributed energy storage under power spot market in China

Chen

et al. 2021

IET Renewable Power Gen

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The reform of power spot market in China provides a new profit mode, determining energy trading strategy based on the power spot prices for distributed energy storages. However, individually accessing every distributed energy storage to the dispatch centre results in a high cost and low efficiency, which needs to be improved by connecting through the aggregator. To this end, this paper proposes a regulation mode and strategy for distributed energy storages participating in energy trading through aggregation. First, the optimal centres of distributed energy storages are searched as the aggregation centres according to the electrical distance distributed by the energy storage, and the model of each distributed energy storage aggregation group is established. On this basis, the conditional value at risk (CVaR) method is introduced to quantify the income risk brought by the fluctuation of power spot prices, following with the optimization model for day‐ahead stage and real‐time stage. Finally, case studies under multiple scenarios of power spot market verify that the regulation mode and strategy can effectively guarantee the economic profits of distributed energy storages by setting aggregation groups and reasonable risk preference coefficients.

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“…Hemmati et al [14] modelled three time-scales of ESS operation: daily, weekly and seasonal, as three levels within the planning model. Several private investors in distributed ESS were considered by Saber et al [139]. The investors were differentiated by their treatment of risk and their zone within the transmission grid.…”

Section: Transmission System-level Essmentioning

confidence: 99%

“…Planning Solving Technique [20,22,23,30,43,46,[49][50][51]53,54,57,59,73,74,78,[88][89][90]105] [ 119,125,130,156] LP [1,16-18,20,25,32,33,35,44,47,50,52, 56-58,60,61,63,65,66,70-72,76,79-83, 86,92,94-96,100-102,104,106,107] [ 14,28,[109][110][111][112][113][114][115]117,121,122,126,127,131,[133][134][135][136][137]139,148,149,155,156,<...>…”

Section: Operationmentioning

confidence: 99%

Operating and Investment Models for Energy Storage Systems

2020

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In the context of climate changes and the rapid growth of energy consumption, intermittent renewable energy sources (RES) are being predominantly installed in power systems. It has been largely elucidated that challenges that RES present to the system can be mitigated with energy storage systems (ESS). However, besides providing flexibility to intermittent RES, ESS have other sources of revenue, such as price arbitrage in the markets, balancing services, and reducing the cost of electricity procurement to end consumers. In order to operate the ESS in the most profitable way, it is often necessary to make optimal siting and sizing decisions, and to determine optimal ways for the ESS to participate in a variety of energy and ancillary service markets. As a result, many publications on ESS models with various goals and operating environments are available. This paper aims at presenting the results of these papers in a structured way. A standard ESS model is first outlined, and that is followed by a literature review on operational and investment ESS models at the transmission and distribution levels. Both the price taking and price making models are elaborated on and presented in detail. Based on the examined body of work, the paper is concluded with recommendations for future research paths in the analysis of ESS.

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Expansion Planning Studies of Independent-Locally Operated Battery Energy Storage Systems (BESSs): A CVaR-Based Study

Cited by 28 publications

References 29 publications

Network-Constrained Optimal Scheduling of Multi-Carrier Residential Energy Systems: A Chance-Constrained Approach

Network-Constrained Optimal Scheduling of Multi-Carrier Residential Energy Systems: A Chance-Constrained Approach

Aggregate regulation strategy of distributed energy storage under power spot market in China

Operating and Investment Models for Energy Storage Systems

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