Estimating benefits of energy storage for aggregate storage applications in electricity distribution networks in Queensland

Abeygunawardana, Anula; Ledwich, Gerard

doi:10.1109/pesmg.2013.6672793

Cited by 11 publications

(4 citation statements)

References 10 publications

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“…State-of-charge equivalent constraints (8) where E i , E total , SOC max , SOC min are the capacity of the i-th DES, the total capacity, the equivalent maximum and minimum state of charge of the DES aggregation group, respectively.…”

Section: 32mentioning

confidence: 99%

“…At present, the real-time arbitrage of DES through the power spot market is mainly concentrated in places such as the USA, Europe and Australia [6]. In [7] and [8], the real-time arbitrage and ancillary service transactions are respectively pro-posed for energy storages (ES) in the California Independent System Operator (CAISO), US and Australian power spot markets, which show that both cases are able to improve the economic profits of DES compared to those in non-power markets. In [9], the authors study the dispatch plan of combining DESs and thermal power plants (TPP) to participate in the power spot market, concluding that the overall power generation profit has increased compared with that of independent power generation.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: 32mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Chen

et al. 2021

IET Renewable Power Gen

View full text Add to dashboard Cite

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“…Thanks to the high computational efficiency, the algorithm can be used to evaluate the optimal operating policy of a BESS in real-time applications, based on the load condition of the user, the energy left in the BESS, and the output of wind turbines. In [18], the authors estimate the benefit of using energy storages for aggregate storage applications, such as energy price arbitrage, TOU energy cost reduction, ancillary services, and transmission upgrade deferral. The maximization of the arbitrage benefit is carried out by maximizing an objective function, under the assumption that the electricity prices are both dependent/independent on the battery operation.…”

Section: Other Bess Management Strategiesmentioning

confidence: 99%

A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs

2015

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Abstract:Price arbitrage involves taking advantage of an electricity price difference, storing electricity during low-prices times, and selling it back to the grid during high-prices periods. This strategy can be exploited by customers in presence of dynamic pricing schemes, such as hourly electricity prices, where the customer electricity cost may vary at any hour of day, and power consumption can be managed in a more flexible and economical manner, taking advantage of the price differential. Instead of modifying their energy consumption, customers can install storage systems to reduce their electricity bill, shifting the energy consumption from on-peak to off-peak hours. This paper develops a detailed storage model linking together technical, economic and electricity market parameters. The proposed operating strategy aims to maximize the profit of the storage owner (electricity customer) under simplifying assumptions, by determining the optimal charge/discharge schedule. The model can be applied to several kinds of storages, although the simulations refer to three kinds of batteries: lead-acid, lithium-ion (Li-ion) and sodium-sulfur (NaS) batteries. Unlike literature reviews, often requiring an estimate of the end-user load profile, the proposed operation strategy is able to properly identify the battery-charging schedule, relying only on the hourly price profile, regardless of the specific facility's consumption, thanks to some simplifying assumptions in the sizing and the operation of the battery. This could be particularly useful when the customer load profile cannot be scheduled with sufficient reliability, because of the uncertainty inherent in load forecasting. The motivation behind this research is that storage devices can help to lower the average electricity prices, increasing flexibility and fostering the integration of renewable sources into the power system.

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“…However, the cost of ES, particularly battery is a major obstacle to its adoption [87]. It is also revealed that the current deployment of ES is still uneconomic as the overall installation cost of ES is higher than the total benefit obtained from its deployment [56], [93]. It is expected that if all ES benefits and its cost reduction in the future are considered in the analysis, ES will be a profitable solution [76].…”

Section: Economic Evaluationmentioning

confidence: 99%

Smart development of community energy storage in power grid with PV units

Sardi¹

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Energy storage (ES) system has become an inevitable element in smart distribution network (DN) due to massive deployment of renewable energy resources (RERs). ES is capable of solving a number of operational problems in distribution network due to intermittent characteristic of the RERs while providing numerous other benefits such as ancillary services, peak reduction, reliability improvement etc. Among various type of RERs, community level distributed photovoltaic (PV) is the fastest-growing power generation system due to its technological advancement; declining price and better fit into consumer area. Thus, impact of intermittent PV output power is more severe in community level where the consumption is happening. Hence, the idea of bringing ES close to the source of the problem has led to the development of concept called community energy storage (CES). Most available studies claimed that the deployment of CES is more effective in alleviating the impact of high PV penetration while offering more benefits than the centrally located substation storage if properly planned and effectively controlled. However, comprehensive review found that very scant analytical evidences were shown to prove the statement. Besides, currently CES allocation is determined based on maximizing specific benefit while neglecting others benefits of its deployment. Very scarce previous works provided a complete allocation

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Estimating benefits of energy storage for aggregate storage applications in electricity distribution networks in Queensland

Cited by 11 publications

References 10 publications

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

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

A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs

Smart development of community energy storage in power grid with PV units

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