Managing Energy Storage in Microgrids: A Multistage Stochastic Programming Approach

Bhattacharya, Arnab; Kharoufeh, Jeffrey P.; Zeng, Bo

doi:10.1109/tsg.2016.2618621

Cited by 91 publications

(31 citation statements)

References 50 publications

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“…Reference [10] suggests a microgrid model minimizing procurement cost under uncertain wind generation where load is balanced in terms of purchase and sale to the utility grid, by using load shifting and micro generators. Reference [11] has a similar formulation also including power loss minimization and uncertain price. In [12], the cost is minimized for a private household with battery storage and uncertain PV generation.…”

Section: B Relevant Literaturementioning

confidence: 99%

Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming

Aaslid

Belsnes

Fosso

2019

2019 International Conference on Smart Energy Systems and Technologies (SEST)

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Intermittent energy sources demand temporal storages to balance generation and load, and batteries stand out as an alternative. However, the lifetime is limited, and cycling depth affects the battery degradation rate. Current stochastic multistage methods lack proper representation of battery degradation. This paper proposes a stochastic multi-stage model for optimizing battery operation in a microgrid considering battery degradation with a piece-wise linear cost function with uncertain wind power production and load. The model is solved using Stochastic Dual Dynamic Programming (SDDP) and is demonstrated on a 4-bus test case with limited import and export capacity to illustrate the battery degradation cost's impacts on the battery cycling strategy. The results show that the importance of a stochastic method is more pronounced when battery degradation is modelled.

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Section: B Relevant Literaturementioning

confidence: 99%

Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming

Aaslid

Belsnes

Fosso

2019

2019 International Conference on Smart Energy Systems and Technologies (SEST)

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“…Furthermore, the cost of ESS incorporation as storage units in service restoration is formulated in (11). Indeed, ESSs in the backup feeding path can be charged in the light load of restoration period and discharged in peak load.…”

Section: Proposed Objective Function For Service Restorationmentioning

confidence: 99%

Reliability improvement in smart grid through incorporating energy storage systems in service restoration

Abniki

Taghvaei²,

Mohammadi‐Hosseininejad

2018

Int Trans Electr Energ Syst

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Summary Smart grid has been developing nowadays as an initiative to operate modern electric distribution systems (EDSs) in a more reliable and efficient manner. With the decreasing price of the energy storage systems (ESSs), ESSs are highly recommended to be exploited in the operation of EDSs. In this manuscript, a comprehensive framework is introduced for ESS incorporation in service restoration process which proposes 2 roles for ESSs in the service restoration. As the first role, ESSs are exploited in the service restoration to re‐energize customers in interrupted zones, as their backup units. As the second role, ESSs are used in the service restoration to increase the number of interrupted customers which transferred to the backup feeders through acting as storage units. The proposed objective function of service restoration consists of customer interruption cost, energy not sold cost, cost of electricity production in combined heat and power units, and cost of ESS incorporation in service restoration. Moreover, the stochastic characteristics of ESS contribution in service restoration are considered in the proposed problem formulation. Further, the impacts of the uncertainties of the service restoration on the proposed approach for ESS incorporation are investigated. The effectiveness of the proposed methodology is deliberated using a standard reliability test system (RBTS‐4). The obtained results show that the incorporating ESSs as storage units will lead to substantially improve the reliability level of EDS through increasing the adequacy of the EDS during service restoration process.

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“…A small number of scenarios is obtained, assuming a normal probability distribution function, and a scenario reduction technique is applied to reduce the combined scenario set. In [5], a customized SDDP algorithm is presented and implemented in a microgrid context, where uncertain wind output, demand and energy price are captured employing a scenario tree model. Nodal values of the scenario tree are derived from a multivariate truncated normal distribution and temporal independence is assumed.…”

Section: A Backgroundmentioning

confidence: 99%

“…Constraints (3) - (4) impose limits for both electrical power and energy levels of the battery, while energy neutrality for the entire planning horizon is preserved through (5).…”

Section: Problem Definitionmentioning

confidence: 99%

“…More specifically, upper and lower bounds of the optimal solution are defined and calculated at each iteration, and the algorithm terminates when the distance between these bounds is within a tolerance value. The upper and lower are bounds are given by (21) -(22), and convergence of the two bounds is checked at the end of each forward pass run, according to (23), as in [5].…”

Section: Convergence Criteriamentioning

confidence: 99%

See 1 more Smart Citation

A stochastic dual dynamic programming approach for optimal operation of DER aggregators

Fatouros

Konstantelos

Papadaskalopoulos

et al. 2017

2017 IEEE Manchester PowerTech

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Abstract-The operation of aggregators of distributed energy resources (DER) is a highly complex task that is affected by numerous factors of uncertainty such as renewables injections, load levels and market conditions. However, traditional stochastic programming approaches neglect information around temporal dependency of the uncertain variables due to computational tractability limitations. This paper proposes a novel stochastic dual dynamic programming (SDDP) approach for the optimal operation of a DER aggregator. The traditional SDDP framework is extended to capture temporal dependency of the uncertain wind power output, through the integration of an n-order autoregressive (AR) model. This method is demonstrated to achieve a better trade-off between solution efficiency and computational time requirements compared to traditional stochastic programming approaches based on the use of scenario trees.

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Managing Energy Storage in Microgrids: A Multistage Stochastic Programming Approach

Cited by 91 publications

References 50 publications

Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming

Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming

Reliability improvement in smart grid through incorporating energy storage systems in service restoration

A stochastic dual dynamic programming approach for optimal operation of DER aggregators

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