Energy Storage on a Distribution Network for Self-Consumption of Wind Energy and Market Value

Ademulegun, Oluwasola O.; Keatley, Patrick; Mustafa, Motasem Bani; Hewitt, Neil

doi:10.3390/en13112688

Cited by 7 publications

(11 citation statements)

References 18 publications

(34 reference statements)

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“…In [25,26], the authors employed the methodology to derive the size of a battery energy storage system (BESS) for self-consumption optimally in windless times, and operated the BESS to maximise its technical and economic benefits. Distributed energy resources for households should consist of as many energy sources as possible [2,27] to improve economic parameters. With the addition of the storage device, the self-consumption of wind energy increased by almost 10% [27].…”

Section: Overview Of Literaturementioning

confidence: 99%

“…Distributed energy resources for households should consist of as many energy sources as possible [2,27] to improve economic parameters. With the addition of the storage device, the self-consumption of wind energy increased by almost 10% [27]. In Spain, different energy generation systems based on solar PV are competitive and profitable without subsidies in self-consumption schemes [28].…”

Section: Overview Of Literaturementioning

confidence: 99%

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Modelling of Consumption Shares for Small Wind Energy Prosumers

et al. 2021

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This article describes a simulation of energy distribution in an average household where electricity is produced with a small wind generator or purchased from the public electricity grid. Numerical experiments conducted within an average of five minutes were performed using annual production and consumption graphs. Virtual storage devices, a water tank and a battery were used to buffer energy inside the household. The energy required for non-shiftable consumption and hot water consumption were taken directly from the utility grid. Surplus energy remaining from wind generator production after providing for consumption and storage needs were redirected there. A cover factor was used as a measure of the efficiency of energy distribution. One of the aims of the article was to determine by simulations the change of the cover factor in a virtually designed situation where the expected energy output of the wind generator was known in advance over one to three hours. The results found that for the configuration of the proposed nanogrid option, the positive results were readily achieved when the expected wind generator production was known an hour ahead. Then, the cover factor increased from 0.593 to 0.645. The side result of using projected/expected production is an increase in asymmetrical energy exchanges bilaterally between nanogrid and utility grid in favour of grid sales. Another finding was that the cover factor depended on the wind generator’s production intensity but less on the intensity of consumption within the household.It is hoped/expected that future research will address the prediction of output using mathematical methods.

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Section: Overview Of Literaturementioning

confidence: 99%

Section: Overview Of Literaturementioning

confidence: 99%

Modelling of Consumption Shares for Small Wind Energy Prosumers

et al. 2021

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“…The total cost charged by the power plant is derived by the equation (18). The first term represents the power plant's transmission cost.…”

Section: B Total Cost Of Power Plantmentioning

confidence: 99%

“…The first term represents the power plant's transmission cost. The costs incurred by the PG1 which consists of setup cost, storage cost, carbon cost, production cost, and investment cost are presented in the second term until the sixth term of equation (18). The seventh term until the eleventh term of equation (18) show setup cost, storage cost, carbon cost, production cost and investment cost of the PG2.…”

Section: B Total Cost Of Power Plantmentioning

confidence: 99%

“…Karimi et al [17] formulated a stochastic mathematical model for determining the optimal allocation of energy storage units in wind integrated distribution networks. Ademulegun et al [18] proposed a mathematical model of the electricity distribution networks consisting of two wind turbines and energy storage device. They showed that the use of energy storage in the distribution networks can increase the local consumption of wind energy and provide certain ancillary services that lead to an increase in total profit.…”

Section: Introductionmentioning

confidence: 99%

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Sustainable Electrical Energy Supply Chain System With Hybrid Power Generation: An Inventory Approach

et al. 2021

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In this paper, we present a sustainable electrical energy supply chain system (SEESCS) where two supply chain parties are involved, namely a power plant and a transmission station. The power plant has two different types of power generation systems. The first power generation system (PG1) is more costly but it generates lower emissions than the second system (PG2). The model is developed based on a lot-sizing inventory problem to decide the load allocation between PG1 and PG2. The objective function is to minimize total costs that consist of energy generation cost and emission cost. The transmission station faces a stochastic demand and employs a continuous review policy to manage the electrical energy storage. An efficient procedure is developed to solve the model and a sensitivity analysis is carried out to explore the impact of changes in some key parameters on the model's behavior. The results show that the allocation of electricity generation is mostly influenced by the change in PG1's production cost parameter and PG2's emissions parameters. In addition, the amount of emissions generated from the system is significantly affected by the variation in PG1's production cost parameter, PG2's emissions parameters, and electricity demand.

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