Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties

Pinto, Rafael S.; Unsihuay-Vila, Clodomiro; Tabarro, Fabricio H.

doi:10.1016/j.apenergy.2021.117108

Cited by 33 publications

(10 citation statements)

References 39 publications

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“…The degradation of electrical storage devices by charging/discharging and its efficiency are also ignored, as well as active losses in lines. Similar simplifications are used in other expansion planning problems, such as in [15,17].…”

Section: Assumptionsmentioning

confidence: 99%

“…The DGs are considered renewable solar-wind power sources with constant power factors, which is a consideration for the case study but not a limitation of the model, similar approach used in [11,15].…”

Section: Assumptionsmentioning

confidence: 99%

“…Set

Ψ^{b a l}

defines the power balance for each node of the system. Set

Ψ^{s t g}

represents the storage device equations, which is the same approach as used in [15].…”

Section: Proposed Modelmentioning

confidence: 99%

“…The challenges posed by the DEP problem have encouraged many studies, including those considering reliability, uncertainty, and distributed generation. Some of these works have been carried out considering these modelling components individually, such as reliability [3–7], uncertainty [8], distributed generation [9, 10], and a combination of them [11–21]. Few are the works that consider all these elements jointly [22–25].…”

Section: Introductionmentioning

confidence: 99%

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Reliability‐constrained robust expansion planning of active distribution networks

Pinto

Unsihuay-Vila

Tabarro³

2021

IET Generation Trans & Dist

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Power distribution systems have become more complex in recent years due to the integration of new technologies. Motivated by these challenges, this paper describes a model to solve the multi-period expansion planning problem of active distribution systems, considering uncertainty, reliability, distributed generation, self-healing, reactive power support, switches, and energy storage devices. The objective is to determine the best installation times and locations of new components, minimizing the total cost, and ensuring desired reliability levels. The approach consists of a three-level decomposition. The first level identifies expansion proposals, the second level finds the worst-case scenario using adaptive robust optimization, and the third level performs a Monte Carlo Simulation to compute reliability indexes. The main contributions are the introduction of a novel reliability sensitivity matrix to improve computational performance and the representation of the hours of the day inside the expansion planning formulation. The proposed method is illustrated using the IEEE 123-bus test system. The analyses show high computational efficiency as compared with similar works. The impacts on the number of expansion components placed in the system and on the total cost are presented and discussed using cases varying the uncertainty budget and not considering some of these components.

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Section: Assumptionsmentioning

confidence: 99%

Section: Assumptionsmentioning

confidence: 99%

“…Set

Ψ^{b a l}

defines the power balance for each node of the system. Set

Ψ^{s t g}

represents the storage device equations, which is the same approach as used in [15].…”

Section: Proposed Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reliability‐constrained robust expansion planning of active distribution networks

Pinto

Unsihuay-Vila

Tabarro³

2021

IET Generation Trans & Dist

Self Cite

View full text Add to dashboard Cite

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“…Multiple microgrids will be an effective means to solve this problem [15,16]. With the development of distributed energy, more and more microgrids are connected to the distribution system to form a Micro-Grid Community [17,18]. Compared with the economic operation and management of a single microgrid, the cooperative operation of the MGC and the main grid system will become the core problem of large-scale microgrid applications [19,20].…”

Section: Introductionmentioning

confidence: 99%

Bi-Level Energy Management Model of Grid-Connected Microgrid Community

Cao¹,

Dong²,

Ren³

et al. 2022

Energy Engineering

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As the proportion of renewable energy power generation continues to increase, the number of grid-connected microgrids is gradually increasing, and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community (MGC). In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community, this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the total electricity cost of a single micro grid. The lower-level model optimizes the output of each equipment unit in the system and the exchange power between the system and the external grid with the goal of minimizing the operating cost of each microgrid. The upper-level model optimizes the goal of maximizing the social welfare of the microgrid. Taking a microgrid community with four microgrids as an example, the simulation analysis shows that the proposed optimization model is beneficial to reduce the operating cost of a single microgrid, improve the overall revenue of the microgrid community, and reduce the power interaction pressure on the main grid.

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Stochastic multi‐objective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure

Azari

Tabar

Tohidi

2022

Intl J of Energy Research

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Summary Due to the increase in global warming and environmental pollution, heavy penalties have been imposed on pollution producers such as electrical energy networks. Hence, the role of renewable resources expansion in power systems is unavoidable. However, their high penetration increases the uncertainties and decreases the reliability. This paper investigates the expansion of renewable resources in distribution systems based on the zero energy concept. In this regard, different scenarios are designed to determine the optimal location and sizing of wind turbines and photovoltaics as the most matured technologies. To achieve such a goal, a multiobjective linear programming consisting of investment cost and environmental pollution is suggested, which is solved by the augmented epsilon constraint method. Moreover, an incentive‐based demand response program is implemented using shiftable and curtailable responsive loads. Eventually, the uncertainties of renewable resources are modeled by a scenario generation and reduction approach to simulate realistic conditions. The results show that the system that includes only wind turbines or only photovoltaics cannot completely overcome the pollution problem due to the uncertainties. By contrast, a zero energy structure is achievable by their combination, where the investment cost is increased by 73.17% and 48.13% compared to the separate expansion of photovoltaics and wind turbines, respectively. The participation of responsive loads decreases the investment cost by 49.29% as well. Furthermore, the uncertainties of renewable resources increase the total cost by only about 5.95% in the presence of responsive loads; however, the system will be robust against at least 6% of wind turbines and photovoltaics fluctuations.

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Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties

Cited by 33 publications

References 39 publications

Reliability‐constrained robust expansion planning of active distribution networks

Reliability‐constrained robust expansion planning of active distribution networks

Bi-Level Energy Management Model of Grid-Connected Microgrid Community

Stochastic multi‐objective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure

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