A bi-level robust planning model for active distribution networks considering uncertainties of renewable energies

Wu, Ming; Kou, Lingfeng; Hou, Xiaogang; Ji, Yu; Xu, Bin; Gao, Hongjun

doi:10.1016/j.ijepes.2018.09.032

Cited by 48 publications

(24 citation statements)

References 35 publications

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“…An optimal OEPADS must minimise total investment costs and the aggregated operation costs; meanwhile, it must maximise the system reliability. The objective function of OEPADS problem can be proposed as (3).…”

Section: First-stage Problem Formulationmentioning

confidence: 99%

“…Hence, the OEPADS problem must consider the coordinated bidding of AMGs/DRPs procedure in investment practices. The OEPADS must minimise the investment and operation cost; meanwhile, it must maximise the reliability of provided services for the downward loads [3].…”

Section: Problem Modelling and Formulationmentioning

confidence: 99%

“…Ref. [3][4][5][6][7][8][9][10][11][12][13][14][15][16] did not consider AMGs and DRPs coordinated bidding impact on the OEPADS problem. The ADS can pay capacity and energy fees to the AMGs and DRPs to encourage them to coordinate their biddings with the ADS.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal expansion planning of active distribution system considering coordinated bidding of downward active microgrids and demand response providers

Qaeini

Nazar

Yousefian

et al. 2019

IET Renewable Power Generation

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This paper addresses a framework for expansion planning of an active distribution network (ADS) that supplies its downward active microgrids (AMGs) and it participates in the upward wholesale market to sell its surplus electricity. The proposed novel model considers the impact of coordinated and uncoordinated bidding of AMGs and demand response providers (DRPs) on the optimal expansion planning. The problem has six sources of uncertainty: upward electricity market prices, AMGs location and time of installation, AMGs power generation/consumption, ADS intermittent power generations, DRP biddings, and the ADS system contingencies. The model uses the conditional value at risk (CVaR) criterion in order to handle the trading risks of ADS with the wholesale market. The proposed formulation integrates the deterministic and stochastic parameters of the risk-based expansion planning of ADS that is rare in the literature on this field. The introduced method uses a four-stage optimisation algorithm that uses genetic algorithm, CPLEX and DICOPT solvers. The proposed method is applied to the 18-bus and 33-bus test systems to assess the proposed algorithm. The proposed method reduces the aggregated expansion planning costs for the 18-bus and 33-bus system about 44.04% and 11.82% with respect to the uncoordinated bidding of AMGs/DRPs costs, respectively.

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Section: First-stage Problem Formulationmentioning

confidence: 99%

Section: Problem Modelling and Formulationmentioning

confidence: 99%

See 1 more Smart Citation

Optimal expansion planning of active distribution system considering coordinated bidding of downward active microgrids and demand response providers

Qaeini

Nazar

Yousefian

et al. 2019

IET Renewable Power Generation

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show abstract

“…Numerous studies have discussed AC DSEP problems, which is a non-convex mixed integer nonlinear problem. The methods used to solve this problem can be divided into two categories: mathematical programming methods [5]- [7] and heuristic methods [8], [9]. The mathematical methods are proved to find an optimal solution for DSEP, but its computational effort increases rapidly as the size of the problem increases [5].…”

mentioning

confidence: 99%

“…Several uncertainty modeling techniques have been used in DSEP problems. For example, the probabilistic technique [4], [18], the stochastic optimization [5], [19], [20], and the robust optimization (RO) [7], [21]. It should be noted that the above optimization methods are limited to a static description of making planning solutions, and the investment decisions in all stages have been optimized before the realization of uncertainties [22].…”

mentioning

confidence: 99%

AC/DC Hybrid Distribution System Expansion Planning Under Long-Term Uncertainty Considering Flexible Investment

Wu¹,

Sun²,

Gu³

et al. 2020

IEEE Access

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This paper presents a novel flexible multistage AC/DC distribution system expansion planning model, where the flexible investment strategy is taken into account to address the long-term development uncertainty of load demand and DG. Uncertainty is modeled through a multistage scenario tree to capture the possible system states across the planning horizon. As uncertain information revealed gradually over the planning horizon, the planning decisions at each stage are made sequentially within limited disposable reservation funds (RFs). The overall problem is formulated as a mixed-integer linear programming model that guarantees the convergence to optimality by using commercially available software. We compare the total costs of the optimal planning solutions within different proportions of RFs and analyze the flexibility value of RFs for long-term planning problems. In addition, the impact of RFs on the adjustment ability of the plans and the investment risks under uncertainty are evaluated. Case studies are carried out on an AC/DC hybrid system to validate the effectiveness of the proposed model to constitute flexible options when facing long-term uncertainty. The obtained results show the importance of reserving a suitable proportion of RFs in the planning stage, which has a significant influence on the adaptability of the planning solution to uncertain factors. INDEX TERMS AC/DC distribution system, expansion planning, mixed-integer linear programming, flexible investment, long-term uncertainty. NOMENCLATURE INDICES

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An alternating direction method of multipliers ‐based approach to solve mixed‐integer nonlinear volt/var optimization problems in distribution systems

Alburidy

Fan

2021

Int Trans Electr Energ Syst

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Summary This paper presents a tailored version of the alternating direction method of multipliers to achieve a centralized voltage and VAR optimization (VVO) in the electric distribution system. The adopted VVO model is a mixed‐integer nonlinear optimization problem derived from the generic optimal power flow problem. A novel generalized and decomposable version of the VVO model is developed first to establish the proposed approach. The approach accounts for load tap‐changers and switchable capacitor banks for illustration. However, it can be expanded to a broad range of controllable VVO equipment with discrete/integer settings. The approach performance is validated on different distribution networks. Results are compared with current leading heuristic approaches used to solve nonconvex mixed‐integer nonlinear problems such as the Branch‐and‐Bound method. Furthermore, a comparison vs the branch flow model‐based mixed integer second‐order conic programming model is conducted to illustrate the proposed model's advantages. Moreover, to benchmark the proposed approach optimality, a direct search scheme is developed to capture guaranteed globally optimal results. Experiments show the superiority of the proposed approach with noteworthy convergence rates and promising optimal solution allocation.

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A bi-level robust planning model for active distribution networks considering uncertainties of renewable energies

Cited by 48 publications

References 35 publications

Optimal expansion planning of active distribution system considering coordinated bidding of downward active microgrids and demand response providers

Optimal expansion planning of active distribution system considering coordinated bidding of downward active microgrids and demand response providers

AC/DC Hybrid Distribution System Expansion Planning Under Long-Term Uncertainty Considering Flexible Investment

An alternating direction method of multipliers ‐based approach to solve mixed‐integer nonlinear volt/var optimization problems in distribution systems

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