Energy storage for active network management on electricity distribution networks with wind power

Carr, Stephen; Premier, Giuliano C.; Guwy, Alan J.; Dinsdale, Richard M.; Maddy, Jon

doi:10.1049/iet-rpg.2012.0210

Cited by 47 publications

(27 citation statements)

References 30 publications

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“…Aiming to addressing these undesirable conditions, several AM key approaches are introduced and listed in Figure 1. All these AM approaches, such as active network reconfiguration [35,77,97,110], coordinated volt-var control [98,109], coordinated dispatch of DERs, including DGs [22,52,94], ESSs [46,71,88,111], demand response (DR) [53,65,89,112], and optimal charging strategy of electric vehicles (EVs) [55,99], offer many potential benefits to the planning of ADSs and affect quality of the planning solution. The coupling of operation and planning is able to achieve the simultaneous optimization of planning and operation, and to identify the benefits and the effects of optimal operation on the planning solution.…”

Section: High-level Uncertaintiesmentioning

confidence: 99%

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: High-level Uncertaintiesmentioning

confidence: 99%

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

Wang

Chen³

et al. 2017

Energies

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“…Reference [18] proposes the modeling and the optimal management of a hot- temperature (sodium nickel chloride) battery system coupled with wind generators connected to a medium voltage grid. In reference [19], the ability of the ESS to increase the amount of wind energy accepted onto a network is assessed. The results show that the ESS is able to increase the accepted energy onto a distribution network.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The inves and other network data are given in the Table 3 and Fig Table 2. The data used in plann (19) The transmission power of the line between nodes i and j in tth year, hth hours and scenario s should have a maximum limit. , , deg max , ,…”

Section: Problem Assumptmentioning

confidence: 99%

Simultaneous Planning of Renewable/ Non-Renewable Distributed Generation Units and Energy Storage Systems in Distribution Networks

Jannati¹,

Yazdaninejadi²,

Talavat³

2017

Transactions on Electrical and Electronic Materials

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The increased diversity of different types of energy sources requires moving towards smart distribution networks. This paper proposes a probabilistic DG (distributed generation) units planning model to determine technology type, capacity and location of DG units while simultaneously allocating ESS (energy storage systems) based on predetermined capacities. This problem is studied in a wind integrated power system considering loads, prices and wind power generation uncertainties. A suitable method for DG unit planning will reduce costs and improve reliability concerns. Objective function is a cost function that minimizes DG investment and operational cost, purchased energy costs from upstream networks, the defined cost to reliability index, energy losses and the investment and degradation costs of ESS. Electrical load is a time variable and the model simulates a typical radial network successfully. The proposed model was solved using the DICOPT solver under GAMS optimization software.

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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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Energy storage for active network management on electricity distribution networks with wind power

Cited by 47 publications

References 30 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

Simultaneous Planning of Renewable/ Non-Renewable Distributed Generation Units and Energy Storage Systems in Distribution Networks

Optimal Bidding Strategy for Renewable Microgrid with Active Network Management

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