Planning for distributed wind generation under active management mode

Zhang, Jietan; Fan, Hong; Tang, Wenting; Wang, Maochun; Cheng, Haozhong; Yao, Liangzhong

doi:10.1016/j.ijepes.2012.10.024

Cited by 48 publications

(31 citation statements)

References 25 publications

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“…Economic objectives ·Minimization of investment and operation costs [23], [24], [25], [26], [30], [31], [38], [42], [46]... ·Minimization of network losses [34], [40], [41], [56], [63], [73], [84], [91], [102]... ·Maximization of net profit value [33], [44], [72], [81], [84], [92], [97], [103]...…”

Section: Objectives Of Ads Planning Modelmentioning

confidence: 99%

“…The process is shown in Figure 9. Then, combined with the approaches of probabilistic optimal power flow [44,60,79], chance constrained programming [62,70], etc., these simulated data of RDGs and load demand could be used in ADS planning models considering high-level uncertainties.…”

Section: Probabilistic Approachesmentioning

confidence: 99%

“…As the main sources of uncertainties, wind speed, solar irradiance, and load demand, are approximately assumed to follow Weibull distribution, Beta distribution, and normal distribution, respectively, as shown from Equations (2)-(4). Therefore, these PDFs are adopted to represent the high fluctuation and randomness features of wind speed, solar irradiance, and load demand in many articles [25,35,44,48,53,65,66,75,81,90].…”

mentioning

confidence: 99%

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A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

Wang

Chen³

et al. 2017

Energies

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Due to the widespread deployment of distributed energy resources (DERs) and the liberalization of electricity market, traditional distribution networks are undergoing a transition to active distribution systems (ADSs), and the traditional deterministic planning methods have become unsuitable under the high penetration of DERs. Aiming to develop appropriate models and methodologies for the planning of ADSs, the key features of ADS planning problem are analyzed from the different perspectives, such as the allocation of DGs and ESS, coupling of operation and planning, and high-level uncertainties. Based on these analyses, this comprehensive literature review summarizes the latest research and development associated with ADS planning. The planning models and methods proposed in these research works are analyzed and categorized from different perspectives including objectives, decision variables, constraint conditions, and solving algorithms. The key theoretical issues and challenges of ADS planning are extracted and discussed. Meanwhile, emphasis is also given to the suitable suggestions to deal with these abovementioned issues based on the available literature and comparisons between them. Finally, several important research prospects are recommended for further research in ADS planning field, such as planning with multiple micro-grids (MGs), collaborative planning between ADSs and information communication system (ICS), and planning from different perspectives of multi-stakeholders.

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Section: Objectives Of Ads Planning Modelmentioning

confidence: 99%

Section: Probabilistic Approachesmentioning

confidence: 99%

mentioning

confidence: 99%

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A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

Wang

Chen³

et al. 2017

Energies

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“…ANM can be a solution to these operational problems. ANM is a smart-grid technology that enables a MGO to measure the state of each bus, such as the voltage and angle, in real-time; calculate the optimal dispatch of resources considering the network conditions and physical constraints; and then deliver the dispatched signals to resources through a communication infrastructure [12][13][14][15]. Therefore, a MGO with ANM is able to stably and efficiently operate a renewable MG by optimally curtailing the outputs of RDGs and loads and scheduling the active/reactive powers of BESSs without violating physical constraints.…”

Section: Features Of Active Network Management In Microgrid Operationmentioning

confidence: 99%

“…The above real-time adjustments of the MGO can be realized through Active Network Management (ANM) [12][13][14][15]. Owing to the real-time adjustments using ANM, the power flow in the line connecting the main grid and MG can deviate significantly from the submitted bid, which is obtained according to the bidding strategies proposed in [10,11].…”

Section: Introductionmentioning

confidence: 99%

Optimal Bidding Strategy for Renewable Microgrid with Active Network Management

Kim

Kim²,

Jin

et al. 2016

Energies

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Active Network Management (ANM) enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG) and Battery Energy Storage System (BESS) units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.

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Optimal siting and sizing of intermittent distributed generators in distribution system

Zhang

Cheng

et al. 2015

IEEJ Transactions Elec Engng

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Intermittent distributed generators (IDGs), such as distributed wind turbine generator (WTG) and photovoltaic generator (PVG), have been developing rapidly in recent years. The output power of WTG and PVG highly depends on the wind speed and illumination intensity, respectively. There always exist correlations among the wind speed, illumination intensity, and bus load, which could have significant influence on the determination of siting and sizing of IDGs in distribution system. Given this background, a chance‐constrained‐programming‐based IDGs planning model, which can take into account the correlations, is developed in this paper. Latin hypercube sampling technique and Cholesky decomposition are introduced to handle the correlations. A Monte Carlo simulation‐embedded multi‐population differential evolution algorithm is employed to solve the developed model. Case studies carried out on the Baran & Wu 33‐bus distribution system verify the feasibility of the developed model and effectiveness of the proposed solving methodology. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Planning for distributed wind generation under active management mode

Cited by 48 publications

References 25 publications

A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

Optimal Bidding Strategy for Renewable Microgrid with Active Network Management

Optimal siting and sizing of intermittent distributed generators in distribution system

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