SAIDI Constrained Economic Planning and Utilization of Central Storage in Rural Distribution Networks

Narimani, A.; Nourbakhsh, Ghavameddin; Arefi, Ali; Ledwich, Gerard; Walker, Geoffrey R.

doi:10.1109/jsyst.2018.2852630

Cited by 21 publications

(11 citation statements)

References 44 publications

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“…Ant Colony Optimization [24] Approximate Q-Learning [35] Artificial Bee Colony [32] Artificial Neural Network [38] Differential Evolution [37] Expert System [28] Fuzzy Sets [17,27,44,47] Genetic Algorithm [16,22,25,34,36,39,43] Geometric Clustering with Unsupervised Learning [42] Heuristic Optimization [21] Imperialist Competitive Algorithm [18] Multi Agent Systems [10,14,23,41,48,49] Particle Swarm Optimization [11][12][13]15,26,29,30,33,37,40,46] Reinforcement Learning [50] Scatter Search [31] Simulated Annealing [19] Support Vector Machines [45] 4.…”

Section: Computational Intelligence Methods Referencementioning

confidence: 99%

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Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Georgilakis

2020

Energies

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The massive integration of distributed energy resources in power distribution systems in combination with the active network management that is implemented thanks to innovative information and communication technologies has created the smart distribution systems of the new era. This new environment introduces challenges for the optimal operation of the smart distribution network. Local energy markets at power distribution level are highly investigated in recent years. The aim of local energy markets is to optimize the objectives of market participants, e.g., to minimize the network operation cost for the distribution network operator, to maximize the profit of the private distributed energy resources, and to minimize the electricity cost for the consumers. Several models and methods have been suggested for the design and optimal operation of local energy markets. This paper introduces an overview of the state-of-the-art computational intelligence methods applied to the optimal operation of local energy markets, classifying and analyzing current and future research directions in this area.

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Section: Computational Intelligence Methods Referencementioning

confidence: 99%

“…Out of 41 reviewed papers, only 14 papers consider the alternating current (AC) power flow constraints at their optimization models [12,13,15,17,[29][30][31]34,35,38,40,41,43,46].…”

Section: Power Flow Constraintsmentioning

confidence: 99%

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Georgilakis

2020

Energies

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“…These VPPs use a bidding strategy considering their resources and market situation in, for example, day-ahead electricity market [46]. In addition, energy storage integrated VPPs can contribute to the adequacy and reliability of generation systems in distribution networks [47,48], for which an optimization algorithm should determine the charging/discharging of energy storage. As uncertainties associated with load profile, renewable energy and electricity price makes forecast of DR very difficult, ref.…”

Section: Demand Response Aggregatormentioning

confidence: 99%

“…Moreover, a DR aggregator can reduce potential equipment damage along the grid by offering a better power quality, provide operators with better mechanisms for load forecasting by better understanding of load profile through an effective communication [16,17]. Mitigation of congestions and reliability improvement through the investment on energy storage and other low-cost technical solutions such as dynamic voltage restorer would be other benefits of DR aggregators [48,73]. This area is another benefit for DR aggregators can provide to utilities and communities, which needs an appropriate agreement between aggregators and utilities and the corresponding analysis.…”

Section: Economic Considerationsmentioning

confidence: 99%

Aggregator of Demand Response for Renewable Integration and Customer Engagement: Strengths, Weaknesses, Opportunities, and Threats

et al. 2018

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The world is progressing towards a more advanced society where end-consumers have access to local renewable-based generation and advanced forms of information and technology. Hence, it is in a current state of transition between the traditional approach to power generation and distribution, where end-consumers of electricity have typically been inactive in their involvement with energy markets and a new approach that integrates their active participation. This new approach includes the use of distributed energy resources (DER) such as renewable-based generation and demand response (DR), which are being rapidly adopted by end-consumers where incentives are strong. This paper presents the role of the DR aggregator to effectively integrate DER technology as a new source of energy capacity into electricity networks using information communication technology and industry knowledge., Based on DR aggregators, this framework will efficiently facilitate renewable energy integration and customer engagement into the electricity market. To this aim, advantages and disadvantages of DR aggregators are discussed in this paper from political, economic, social, and technological (PEST) points of view. Based on this analysis, a strengths, weaknesses, opportunities, and threats (SWOT) analysis for a typical DR aggregator is presented.

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“…Sekhavatmanesh et al [19] presents optimal infrastructure planning for active distribution networks meeting service renewal requirements. Narimani et al [20] provides a framework for the allocation of a central electricity storage facility (EES) in discrete communities, which is created as segmentation along rural energy supplies where the installation of cross connectors is not economical or even feasible. Modeling of the impact of automation failure on distribution system reliability is presented in paper [21].…”

Section: Introductionmentioning

confidence: 99%

Management of Smart Switchboard Placement to Enhance Distribution System Reliability

et al. 2020

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One way of handling short-time short-circuits without causing equipment failure is the management of the reclose function integrated into smart switchboard which is described in this article. Due to the cost of the application, the optimal placement of such equipment must be well-planned. During the planning of the placement optimization of a low-voltage electricity network quality, the increase of the consumer supply security must be considered along with the best economic utilization. The research presented in this article aims to introduce a new special decision support methodology calculated with these variables. The management of smart switchboard (SSB) tool installation into low voltage (LV) network was investigated. The selection of the placement nodes is based on the complex investigation of the network characteristics. Investigation is performed by empiric analysis. This method can support the power companies to make the optimal decision. The presented new device can have outstanding importance for the electric industry and for further research as no testing results of such investigations have been published yet. 101 Narimani et al. [20] provides a framework for the allocation of a central electricity storage facility 102 (EES) in discrete communities, which is created as segmentation along rural energy supplies where 103 the installation of cross connectors is not economical or even feasible. Modeling of the impact of 104 automation failure on distribution system reliability is presented in paper [21]. Reinders [22] focuses 105 on the reliability of electricity supply at three different locations in Indonesia by comparing reported 106 energy reliability indices (SAIFI and SAIDI). A common FLISR approach is to use error indicator (FI) 107 signals with distribution network states [23].108 2. The Smart Switchboard 109 The smart switchboard (SSB) developed by AD&TE is a low voltage distribution switchboard 110 which, under the described maintenance and operational circumstances during its entire life cycle 111 and without the partial or total change of the equipment, interrupts the overcurrent or the short-112 circuit current up to the value defined by the manufacturer, compliant to the applicable standards.113 The SSB detects the overcurrent with the combined usage of the local measure-and evaluation system 114 [24]. The operation happens according to the predefined current-time curve. The equipment is 115 remote, thus the existence of tension (yes/no) at each measuring point, the effective and inefficient 116 current components, the tension and the calculated performance data based on tension-with the 117 application of the security protocols in the related standards-is forwarded to a centre by using 118 wireless communication. The SSB can be operated remotely, accordingly, it is suitable for performing 119 remote switching operations. In order to the secure feasibility of the planned tasks the remote 120 operation can be blocked in-site and has visible breakdown point and earthing possibility. The 121 eq...

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SAIDI Constrained Economic Planning and Utilization of Central Storage in Rural Distribution Networks

Cited by 21 publications

References 44 publications

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Aggregator of Demand Response for Renewable Integration and Customer Engagement: Strengths, Weaknesses, Opportunities, and Threats

Management of Smart Switchboard Placement to Enhance Distribution System Reliability

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