• Energy Research

This paper develops a two-stage model to site and size a battery energy storage system in a distribution network. The purpose of the battery energy storage system is to provide local flexibility services for the distribution system operator and frequency containment reserve for normal operation (FCR-N) for the transmission system operator. In the first stage, the priority is to fulfil the flexibility needs of the distribution system operator by managing congestions or interruptions of supply in the local network. Thus, the first stage allocates the battery to ensure reliable electricity supply in the local distribution network. The minimum required size of the battery is also determined in the first stage. The second stage optimally sizes the battery energy storage system to boost the profit by providing frequency containment reserve for normal operation. The first and second stages both solve stochastic optimization problems to design the battery energy storage system. However, the first stage considers worst-case scenarios while the second stage utilizes the most probable scenarios derived from the historical data. To validate the proposed model, real-world data from the years 2021 and 2022 in Finland are employed. The battery placement is conducted for both the IEEE 33-bus system and a Finnish case study. The profitability of the model is compared across different cases for the Finnish case study. Finally, the paper assesses the impacts of cycle aging on the battery's total profit. ; © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). ; fi=vertaisarvioitu|en=peerReviewed|

This paper develops a two-stage model to site and size a battery energy storage system in a distribution network. The purpose of the battery energy storage system is to provide local flexibility services for the distribution system operator and frequency containment reserve for normal operation (FCR-N) for the transmission system operator. In the first stage, the priority is to fulfil the flexibility needs of the distribution system operator by managing congestions or interruptions of supply in the local network. Thus, the first stage allocates the battery to ensure reliable electricity supply in the local distribution network. The minimum required size of the battery is also determined in the first stage. The second stage optimally sizes the battery energy storage system to boost the profit by providing frequency containment reserve for normal operation. The first and second stages both solve stochastic optimization problems to design the battery energy storage system. However, the first stage considers worst-case scenarios while the second stage utilizes the most probable scenarios derived from the historical data. To validate the proposed model, real-world data from the years 2021 and 2022 in Finland are employed. The battery placement is conducted for both the IEEE 33-bus system and a Finnish case study. The profitability of the model is compared across different cases for the Finnish case study. Finally, the paper assesses the impacts of cycle aging on the battery's total profit. ; © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). ; fi=vertaisarvioitu|en=peerReviewed|

Lithium-ion battery energy storage systems (BESS) with their present state of technology and economic maturity possess huge potential for catering short-term flexibility requirements in smart grid environment. However, it is essential to model in detail the complexity of non-linear battery system characteristics and control of their adjoining power electronic interfaces. More detailed and accurate modelling of components, enables improved overall power system optimization studies by considering both, component and system level aspects simultaneously. Therefore, this paper develops an equivalent circuit model (ECM) for Lithium-ion battery and Lithium-ion nickel-manganese-cobalt (NMC) battery cell is modelled as a second order equivalent circuit (SOEC), including C-rate, temperature, state-of-charge and age effects. Secondly, detailed controller design methodology for DC/DC- and DC/AC-converter interfaces are developed to enable advanced grid integration studies. Overall, BESS integration design was validated by simulation studies in Simulink Simpowersystems platform.

Lithium-ion battery energy storage systems (BESS) with their present state of technology and economic maturity possess huge potential for catering short-term flexibility requirements in smart grid environment. However, it is essential to model in detail the complexity of non-linear battery system characteristics and control of their adjoining power electronic interfaces. More detailed and accurate modelling of components, enables improved overall power system optimization studies by considering both, component and system level aspects simultaneously. Therefore, this paper develops an equivalent circuit model (ECM) for Lithium-ion battery and Lithium-ion nickel-manganese-cobalt (NMC) battery cell is modelled as a second order equivalent circuit (SOEC), including C-rate, temperature, state-of-charge and age effects. Secondly, detailed controller design methodology for DC/DC- and DC/AC-converter interfaces are developed to enable advanced grid integration studies. Overall, BESS integration design was validated by simulation studies in Simulink Simpowersystems platform.

Fast charging of Lithium-ion battery energy storage systems (Li-ion BESSs) when utilized in the medium voltage (MV) distribution networks may introduce its own stress on the network under certain operating modes, especially when combined with intermittent renewable power generation. In such situations, active network management (ANM) schemes by managing available flexibilities in the MV network is a possible solution to maintain operation limits defined by grid codes. The studies in this paper are related to the utilization ANM schemes for MV distribution network in Sundom Smart Grid, Vaasa, Finland. The aim of this study is to capture the stresses induced by fast charging of Li-ion BESSs during low wind power generation and utilization of ANM schemes to mitigate those arising issues. The effect of such ANM schemes on integration of Li-ion BESS, i.e. control of its grid-side converter (considering operation states and characteristics of the Li-ion BESS) and their coordination with the grid side controllers to enforce network ANM schemes have been analyzed in detail. Particularly, the effect of AC load on the DC characteristics of Li-ion BESSs has been evaluated in this simulation study.

Fast charging of Lithium-ion battery energy storage systems (Li-ion BESSs) when utilized in the medium voltage (MV) distribution networks may introduce its own stress on the network under certain operating modes, especially when combined with intermittent renewable power generation. In such situations, active network management (ANM) schemes by managing available flexibilities in the MV network is a possible solution to maintain operation limits defined by grid codes. The studies in this paper are related to the utilization ANM schemes for MV distribution network in Sundom Smart Grid, Vaasa, Finland. The aim of this study is to capture the stresses induced by fast charging of Li-ion BESSs during low wind power generation and utilization of ANM schemes to mitigate those arising issues. The effect of such ANM schemes on integration of Li-ion BESS, i.e. control of its grid-side converter (considering operation states and characteristics of the Li-ion BESS) and their coordination with the grid side controllers to enforce network ANM schemes have been analyzed in detail. Particularly, the effect of AC load on the DC characteristics of Li-ion BESSs has been evaluated in this simulation study.

The stringent emission rules set by international maritime organisation and European Directives force ships and harbours to constrain their environmental pollution within certain targets and enable them to employ renewable energy sources. To this end, harbour grids are shifting towards renewable energy sources to cope with the growing demand for an onshore power supply and battery-charging stations for modern ships. However, it is necessary to accurately size and locate battery energy storage systems for any operational harbour grid to compensate the fluctuating power supply from renewable energy sources as well as meet the predicted maximum load demand without expanding the power capacities of transmission lines. In this paper, the equivalent circuit battery model of nickel–cobalt–manganese-oxide chemistry has been utilised for the sizing of a lithium-ion battery energy storage system, considering all the parameters affecting its performance. A battery cell model has been developed in the Matlab/Simulink platform, and subsequently an algorithm has been developed for the design of an appropriate size of lithium-ion battery energy storage systems. The developed algorithm has been applied by considering real data of a harbour grid in the Åland Islands, and the simulation results validate that the sizes and locations of battery energy storage systems are accurate enough for the harbour grid in the Åland Islands to meet the predicted maximum load demand of multiple new electric ferry charging stations for the years 2022 and 2030. Moreover, integrating battery energy storage systems with renewables helps to increase the reliability and defer capital cost investments of upgrading the ratings of transmission lines and other electrical equipment in the Åland Islands grid.

The stringent emission rules set by international maritime organisation and European Directives force ships and harbours to constrain their environmental pollution within certain targets and enable them to employ renewable energy sources. To this end, harbour grids are shifting towards renewable energy sources to cope with the growing demand for an onshore power supply and battery-charging stations for modern ships. However, it is necessary to accurately size and locate battery energy storage systems for any operational harbour grid to compensate the fluctuating power supply from renewable energy sources as well as meet the predicted maximum load demand without expanding the power capacities of transmission lines. In this paper, the equivalent circuit battery model of nickel–cobalt–manganese-oxide chemistry has been utilised for the sizing of a lithium-ion battery energy storage system, considering all the parameters affecting its performance. A battery cell model has been developed in the Matlab/Simulink platform, and subsequently an algorithm has been developed for the design of an appropriate size of lithium-ion battery energy storage systems. The developed algorithm has been applied by considering real data of a harbour grid in the Åland Islands, and the simulation results validate that the sizes and locations of battery energy storage systems are accurate enough for the harbour grid in the Åland Islands to meet the predicted maximum load demand of multiple new electric ferry charging stations for the years 2022 and 2030. Moreover, integrating battery energy storage systems with renewables helps to increase the reliability and defer capital cost investments of upgrading the ratings of transmission lines and other electrical equipment in the Åland Islands grid.