A Comprehensive Battery Energy Storage Optimal Sizing Model for Microgrid Applications

Alsaidan, Ibrahim; Khodaei, Amin; Gao, David Wenzhong

doi:10.1109/tpwrs.2017.2769639

Cited by 224 publications

(114 citation statements)

References 47 publications

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“…Narrowing these ranges further would improve the model and its specificity, potentially via the incorporation of correlations between cycle life and DoD, temperature, and charge-discharge rate. Such correlations can be found in the literature [38,39]. This is one possible focus of future work.…”

Section: Model Equations and Parametersmentioning

confidence: 61%

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A General Model for Estimating Emissions from Integrated Power Generation and Energy Storage. Case Study: Integration of Solar Photovoltaic Power and Wind Power with Batteries

2018

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The penetration of renewable power generation is increasing at an unprecedented pace. While the operating greenhouse gas (GHG) emissions of photovoltaic (PV) and wind power are negligible, their upstream emissions are not. The great challenge with the deployment of renewable power generators is their intermittent and variable nature. Current electric power systems balance these fluctuations primarily using natural gas fired power plants. Alternatively, these dynamics could be handled by the integration of energy storage technologies to store energy during renewable energy availability and discharge when needed. In this paper, we present a model for estimating emissions from integrated power generation and energy storage. The model applies to emissions of all pollutants, including greenhouse gases (GHGs), and to all storage technologies, including pumped hydroelectric and electrochemical storage. As a case study, the model is used to estimate the GHG emissions of electricity from systems that couple photovoltaic and wind generation with lithium-ion batteries (LBs) and vanadium redox flow batteries (VFBs). To facilitate the case study, we conducted a life cycle assessment (LCA) of photovoltaic (PV) power, as well as a synthesis of existing wind power LCAs. The PV LCA is also used to estimate the emissions impact of a common PV practice that has not been comprehensively analyzed by LCA—solar tracking. The case study of renewables and battery storage indicates that PV and wind power remain much less carbon intensive than fossil-based generation, even when coupled with large amounts of LBs or VFBs. Even the most carbon intensive renewable power analyzed still emits only ~25% of the GHGs of the least carbon intensive mainstream fossil power. Lastly, we find that the pathway to minimize the GHG emissions of power from a coupled system depends upon the generator. Given low-emission generation (<50 gCO2e/kWh), the minimizing pathway is the storage technology with lowest production emissions (VFBs over LBs for our case study). Given high-emission generation (>200 gCO2e/kWh), the minimizing pathway is the storage technology with highest round-trip efficiency (LBs over VFBs).

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Section: Model Equations and Parametersmentioning

confidence: 61%

“…(6) Temperature-induced degradation is not considered. More information on battery degradation modes can be found in the literature [38,39]. (7) DC-DC coupling is possible for PV and battery storage, but is not analyzed here.…”

Section: Model Assumptions and Approximations Include The Followingmentioning

confidence: 99%

A General Model for Estimating Emissions from Integrated Power Generation and Energy Storage. Case Study: Integration of Solar Photovoltaic Power and Wind Power with Batteries

2018

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“…This work is addressed as a deterministic model and excludes additional costs such as installation and maintenance costs. A MILP formulation solving for optimal sizing of BESS for microgrid applications is presented by I. Alsaidan et al, however this model does not incorporate the use of a PV system [29]. P. Yun et al design a multi-objective hybrid optimization model for wind farm and ESS operation [30].…”

Section: State Of the Artmentioning

confidence: 99%

Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach

et al. 2020

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In the distribution system, customers have increasingly use renewable energy sources and battery energy storage systems (BESS), transforming traditional loads into active prosumers. Therefore, methodologies are needed to provide prosumers with tools to optimize their investments and increase business opportunities. In this paper, a stochastic mixed integer linear programming (MILP) formulation is proposed to solve for optimal sizes of prosumer assets, considering the use of a BESS and photovoltaic (PV) units. The objective is to minimize the total cost of the system, which is defined as the combination of a solar PV system investment, BESS investment, maintenance costs of assets, and the cost of electricity supplied by the grid. The developed method defines the optimal size of PV units, the power/energy capacities of the BESS, and the optimal value for initial energy stored in the BESS. Both deterministic and stochastic approaches were explored. For each approach, the proposed model was tested for three cases, providing a varying combination of the use of grid power, PV units, and BESS. The optimal values from each case were compared, showing that there is potential to achieve more economic plans for prosumers when PV and BESS technologies are taken into account.

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“…where E st B is the remaining energy stored in the BS; P st B is the available output of the BS; E B and E B are the upper bound and lower bound of the charging-discharging process and set to be 90% and 10% of the BS energy rating E B , respectively [25]; the charging-discharging efficiency η = η 0 , charging 1/η 0 , discharging where η 0 = 0.95 for a sodium-sulfur (NaS) BS [26]. From Figure 1, the possible output of P st B can be given by…”

Section: Battery Storagementioning

confidence: 99%

A Computationally Efficient Optimization Method for Battery Storage in Grid-connected Microgrids Based on a Power Exchanging Process

et al. 2019

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Battery storage (BS) sizing problems for grid-connected microgrids (GCμGs) commonly use stochastic scenarios to represent uncertain natures of renewable energy and load demand in the GCμG. Though taking a large number of stochastic scenarios into consideration can deliver a relatively accurate optimal result, it can also highly deteriorate the computational efficiency of the sizing problem. To make an accuracy-efficiency trade-off, a computationally efficient optimization method to optimize the BS capacities based on the power exchanging process of the GCμG is proposed in this paper. According to the imbalanced power of the GCμG, this paper investigates the power exchanging process between the GCμG, BS and external grid. Motivated by the BS dynamics, a forward/backward sweep-based energy management scheme is proposed based on the power exchanging process. A heuristic two-level optimization model is developed with sizing BS as the upper-level problem and optimizing the operational cost of the GCμG as the lower-level problem. The lower-level problem is solved by the proposed energy management scheme and the objective function of the upper-level is minimized by the pattern search (PS) algorithm. To validate the accuracy and computational efficiency of the proposed method, the numerical results are compared with the mixed integer linear programming (MILP) method. The comparison shows that the proposed method shares similar accuracy but is much more time-efficient than the MILP method.

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A Comprehensive Battery Energy Storage Optimal Sizing Model for Microgrid Applications

Cited by 224 publications

References 47 publications

A General Model for Estimating Emissions from Integrated Power Generation and Energy Storage. Case Study: Integration of Solar Photovoltaic Power and Wind Power with Batteries

A General Model for Estimating Emissions from Integrated Power Generation and Energy Storage. Case Study: Integration of Solar Photovoltaic Power and Wind Power with Batteries

Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach

A Computationally Efficient Optimization Method for Battery Storage in Grid-connected Microgrids Based on a Power Exchanging Process

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