Algorithmic Formulation for Network Resilience Enhancement by Optimal DER Hosting and Placement

Dharmasena, Shamini; Olowu, Temitayo O.; Sarwat, Arif I.

doi:10.1109/access.2022.3154056

Cited by 14 publications

(3 citation statements)

References 33 publications

(47 reference statements)

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“…Indeed, the optimal placement of DERs is essential to fully exploit their benefits. Several studies are dedicated to the placement of DERs (See [47], [48] for example). In this paper, we merely study the effect of DER placement on the network losses in DER energy.…”

Section: Der Placementmentioning

confidence: 99%

A Combinatorial Double Auction for Community Shared Distributed Energy Resources

2023

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The integration of distributed energy resources (DERs), such as renewable energy (RE) and energy storage systems, can have many environmental and economic benefits. The sharing of medium-scale DERs can enhance these benefits by ensuring efficient resource utilisation and can promote sharing economy and economies of scale opportunities. In this paper, we design a combinatorial double auction (CDA) for DER sharing between multiple DER providers and a community of consumers. The proposed DER market addresses the complementarity of DER services and supports the environmentally sustainable behaviour of consumers. The purpose of the proposed auction is to allocate the limited DER resources efficiently without compromising the privacy or the comfort of consumers. First, the combinatorial bidding rules are designed and the social welfare optimisation problem is formulated. Then, utility maximising strategies for consumers with both economic and environmental objectives are proposed. Additionally, three types of DER providers are introduced, and their revenue maximising strategies are investigated. A case study with real world RE

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Section: Der Placementmentioning

confidence: 99%

A Combinatorial Double Auction for Community Shared Distributed Energy Resources

2023

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“…The influence of changes in DG location on the network losses and system losses have been investigated in detail. In [7], the authors formulated an algorithm for optimal sizing and deployment of DG units in the utility network to improve network resiliency. This is achieved by the use of a unique critical infrastructure (CI) ranking scheme by prioritizing the CI nodes for DG unit deployment.…”

Section: Introductionmentioning

confidence: 99%

Transmission Network Loss Reduction and Voltage Profile Improvement Using Network Restructuring and Optimal DG Placement

et al. 2023

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This paper introduced a method using hybrid combination of network restructuring and optimal placement of optimally sized distributed generators (DG) to reduce loss and improve voltage profile in a practical transmission network for scenario of high load demand for a period of ten years. A study is performed for four study cases which includes the test transmission network without considering optimal DG placement and network restructuring, considering network restructuring, optimal placement of DG units using proposed grid parameter oriented harmony search algorithm (GPOHSA) and considering hybrid combination of network restructuring and DG placement using GPOHSA. Network restructuring is achieved by addition of a new 400 kV Grid-substation (GSS) and a 220 kV GSS along with associated transmission system. GPOHSA is obtained by a modification in the conventional harmony search algorithm (HSA) where grid coordinates are used for locating the individuals in an objective space. Performance Improvement Indicators such as real power loss reduction indicator (SPLRI), reactive power loss reduction indicator (SQLRI) and summation of node voltage deviation reduction indicator (SNVDRI) are proposed to evaluate performance of each case of study. The period of investment return is assessed to evaluate the pay back period of the investments incurred in network restructuring and DG units. It is established that hybrid combination of network restructuring and DG units placement using GPOHSA is effective to meet the increased load demand for time period of ten years with reduced losses and improved voltage profile. Investment incurred on the network restructuring and DG units placement will be recovered in a time period of 4 years. Effectiveness of the GPOHSA is better relative to the conventional genetic algorithm (GA) for DG unit placement. The study is performed using the MATLAB software on a practical transmission network in India.

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“…The DGs helped to reduce the energy loss and maximized the cost savings [17]. In ref [18], DG placement enhanced the distribution system resiliency. Authors in [19] enhanced the capability to restore the critical loads during natural disasters with the help of DGs.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Placement of Multiple Rooftop Solar PV Integrated Electric Vehicle Charging Stations for Reliability Benefits

Reddy,

Depuru,

Gope

et al. 2023

IEEE Access

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Electric Vehicles (EVs) are known to be future mode of transportation because of their environment-friendly nature. The increase in electric vehicle (EV) penetration needs to set up the new charging stations to meet the demand. The EV charging shows the negative impact on distribution system and system failures lead to the unavailability of power to charge EVs. The EVs not charging due to system failure is to be considered but ignored in the previous studies. Incorporating the Vehicle-to-Grid (V2G) technologies into charging station (CS) improves the system reliability. In this paper, solar rooftop PV units are integrated with CSs to overcome the negative impacts of EV charging and further enhance the reliability of the system. To extracts the maximum benefits from the solar PV integrated charging stations (PVCS), optimal placement is done with objective of reliability improvement. EV reliability is evaluated by using a novel index called as expected energy not charged (EENC). The reliability of both distribution system and EVs are considered as objective functions simultaneously, hence, placement problem becomes multi-objective. The optimal placement is done by considering different EV penetration levels. A multi-objective Grasshopper optimization algorithm (MOGOA) is applied to solve the optimal placement problem of PVCS. The EENS value is improved by 6.18% and 13.9% as compared to base case for case 1 and case 2 respectively. The EENC is improved by 11.51% in case 2 as compared to case 1.

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Algorithmic Formulation for Network Resilience Enhancement by Optimal DER Hosting and Placement

Cited by 14 publications

References 33 publications

A Combinatorial Double Auction for Community Shared Distributed Energy Resources

A Combinatorial Double Auction for Community Shared Distributed Energy Resources

Transmission Network Loss Reduction and Voltage Profile Improvement Using Network Restructuring and Optimal DG Placement

Simultaneous Placement of Multiple Rooftop Solar PV Integrated Electric Vehicle Charging Stations for Reliability Benefits

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