Reliability improvement in radial electrical distribution network by optimal planning of energy storage systems

Saboori, Hedayat; Hemmati, Reza; Jirdehi, Mehdi Ahmadi

doi:10.1016/j.energy.2015.10.125

Cited by 152 publications

(31 citation statements)

References 50 publications

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“…Several techniques have been proposed in the literature for BESS sizing for a variety of applications [30]. These can be generally classified into three main categories: (i) analytical methods [31,32]; (ii) linear programming methods [33,34]; and (iii) nonlinear heuristic methods [35,36]. Analytical methods perform a series of simulations on varying variables of interest, in this case BESS power and energy capacity, to calculate the key performance metrics.…”

Section: Introductionmentioning

confidence: 99%

“…To calculate the BESS charged and discharged energy during each time-step, one should consider not only the energy import inaccuracy and BESS state of charge and capacity, but also BESS nominal power capacity. To account for the latter, researchers often divide the required energy by time-interval length to arrive at an average required power [29][30][31][32][33][34][35][36]. However, such an approach does not take into account the power variations within the interval, which may go beyond the nominal power of the BESS, resulting in a trade-off between accuracy and time-interval resolution.…”

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confidence: 99%

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Data-Driven Mitigation of Energy Scheduling Inaccuracy in Renewable-Penetrated Grids: Summerside Electric Use Case

Farrokhabadi¹

2019

Energies

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This paper presents findings on mitigating the negative impact of renewable energy resources variability on the energy scheduling problem, in particular for island grids and microgrids. The methods and findings presented in this paper are twofold. First, data obtained from the City of Summerside in the province of Prince Edward Island, Canada, is leveraged to demonstrate the effectiveness of state-of-the-art time series predictors in mitigating energy scheduling inaccuracy. Second, the outcome of the time series prediction analysis is used to propose a novel data-driven battery energy storage system (BESS) sizing study for energy scheduling purposes. The proposed probabilistic method accounts for intra-interval variations of generation and demand, thus mitigating the trade-off between time resolution of the problem formulation and the solution accuracy. In addition, as part of the sizing study, a BESS management strategy is proposed to minimize energy scheduling inaccuracies, and is then used to obtain the optimal BESS size. Finally, the paper presents quantitative analyses of the impact of both the energy predictors and the BESS on the supplied energy cost using the actual data of the Summerside Electric grid. The paper reveals the significant potential for reducing energy cost in renewable-penetrated grids and microgrids through state-of-the-art predictors combined with applications of properly-sized energy storage systems.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Data-Driven Mitigation of Energy Scheduling Inaccuracy in Renewable-Penetrated Grids: Summerside Electric Use Case

Farrokhabadi¹

2019

Energies

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“…ESSs offer many applications in electric power systems including mitigating renewable resources uncertainties [26], micro-grid applications [27], risk mitigation in electricity market [28], frequency-voltage control, stability enchantment, power quality improvement, congestion relief, peak load shaving, and load leveling [29], reliability improvement [8], and electricity market [30].…”

Section: Introductionmentioning

confidence: 99%

Multistage generation expansion planning incorporating large scale energy storage systems and environmental pollution

2016

Self Cite

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a b s t r a c tThis paper addresses a multistage electricity generation expansion planning (GEP) incorporating largescale energy storage systems (ESSs). The proposed coordinated GEP-ESS planning aims at minimizing the planning cost and environmental pollution at the same time, while it considers large-scale ESSs. Problem is expressed as a mixed-integer nonlinear programming and solved using PSO algorithm. Problem is solved subject to practical constraints of the network. ESS capacities are installed to support peak load level and reducing planning cost and environmental pollution. A typical test system including several existing and candidate generating units is considered to evaluate the proposed methodology. ESSs with various capacities are considered as candidate ESSs. Considering a large number of generating units and ESSs capacities increases the flexibility of the planning. Simulation results demonstrate that utilizing ESSs significantly reduces GEP cost as well as decreases the environmental pollution.

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“…Ngamroo proposed an optimization technique to adjust the power controller parameters and coil size of multiple SMES units in interconnected power systems with wind farms. In another study, to improve the reliability of radial distribution networks, an optimal approach was introduced to specify the location and size of the energy storage systems …”

Section: Introductionmentioning

confidence: 99%

“…In another study, to improve the reliability of radial distribution networks, an optimal approach was introduced to specify the location and size of the energy storage systems. 18 An island management system was proposed in Best et al, 19 with an emphasis on maximum island flexibility and an intelligent control. This method allows passive islanding transitions to occur.…”

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confidence: 99%

A new controlled superconducting magnetic energy storage for dynamic stabilization of distributed generation in islanding mode of operation

Asadi

Meyar‐Naimi

Jahangiri

2017

Int Trans Electr Energ Syst

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Summary According to IEEE std. 1547, islanding mode is “a condition in which a portion of an Electric Power System (EPS) is energized solely by one or more local EPSs through the associated Point of Common Coupling (PCC) while that portion is electrically separated from the rest of the area EPS”. Therefore, the dynamic instability due to islanding may result in power swing and finally loss of synchronism. Hence, many studies have been done for islanding detection and disconnection of distributed generation (DG) in an EPS. But, these conventional methods eventually lead to the disconnection of the DG units. To improve DG dynamic stability, superconducting magnetic energy storage (SMES) can be used effectively, because SMES have a high‐energy density and fast response. This paper proposes a new method to damp the power swing after DG islanding and to maintain synchronism conditions based on SMES. Hence, the disconnection of the DG units is not required. Also, new controllers are developed for SMES including voltage source converter (VSC), and DC‐DC chopper. The controller structures of VSC and DC‐DC chopper are of PI and fuzzy logic‐based type, respectively. Superconducting coil charging is controlled by the DC‐DC chopper. SMES sizing is performed, based on power swing equations. Hereupon, dynamic load model is considered. Performance of the proposed method is evaluated by defining 12 scenarios such as strong and weak networks with load changing simulated in PSCAD. Simulation results show that the islanded DG stabilization (IDGS) method has good performance to maintain stability margin in a weak network.

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Reliability improvement in radial electrical distribution network by optimal planning of energy storage systems

Cited by 152 publications

References 50 publications

Data-Driven Mitigation of Energy Scheduling Inaccuracy in Renewable-Penetrated Grids: Summerside Electric Use Case

Data-Driven Mitigation of Energy Scheduling Inaccuracy in Renewable-Penetrated Grids: Summerside Electric Use Case

Multistage generation expansion planning incorporating large scale energy storage systems and environmental pollution

A new controlled superconducting magnetic energy storage for dynamic stabilization of distributed generation in islanding mode of operation

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