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Optimal placement of wide area monitoring system components in active distribution networks

  • Surinder Chauhan ORCID logo EMAIL logo and Ratna Dahiya
Published/Copyright: October 22, 2021
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International Journal of Emerging Electric Power Systems
From the journal International Journal of Emerging Electric Power Systems Volume 23 Issue 4

Abstract

The optimal placement of micro-Phasor Measurement Units (µPMUs) reduce the cost of wide area monitoring system (WAMS) in active distribution networks (ADNs); therefore, it is becoming a popular research topic. However, µPMUs alone cannot minimize the WAMS cost. An appropriate location of Phasor Data Concentrator (PDC) and a fiber optic communication link (CL) that transfers data from µPMUs to PDCs also need to be optimized. Hence this paper proposes a hybrid algorithm that determines the optimal cost-effective solution of the placement problem of µPMUs, PDC, and CL. The proposed algorithm uses the graph theory and binary integer linear programming (BILP) with the constraints of distribution generation (DG) presence, regular network reconfiguration, and maximizing system redundancy. The proposed algorithm is tested on IEEE 69 bus, IEEE 123 bus, and 345 bus active distribution system. The results obtained show the reduction in cost mainly through the CL and optimal placement of µPMUs in decentralized WAMS.

Keywords: active distribution network (ADNs); Phasor Data Concentrator (PDC); Phasor Measurement Unit (PMU); wide area monitoring system (WAMS)
Corresponding author: Surinder Chauhan, Electrical Engineering Department, National Institute of Technology, Kurukshetra, Kurukshetra, Haryana 136119, India, E-mail:

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

Appendix

NPV is generally used for the cost benefit analysis of the project which provides the sum of the cash flow of each year in the expected project lifetime [43]. When the NPV is positive, the project can be accepted since it means the project can add value to the utility [44]; otherwise, the project should be rejected because it will subtract the value to the utility. Generally NPV is represented as [45].

(19) NPV = ∑ T = 1 n R T ( 1 + K ) T − ( intial investment + operating & maintenance cost )

where

  • R T is the net cash inflow-outflow during a single period,

  • K is the discount rate or return that could be earned in alternative discount,

  • T number of Time periods.

However, the NPV of WAMS component placement may be determined by considering the following assumptions.

  • – Annual net cash flow (R T ) equals the saving achieved in WAMS cost after optimizing the WAMS component and subtracting the operating & maintenance cost of the WAMS component.

  • – Operating and maintenance case is equals to 10% of total investment.

  • – Time horizon of the project is five years.

While the discount rate is determined by (20).

(20) K = ( Future cash flow Present value ) ( 1 T ) − 1

The WAMS component cost before and after implementing the proposed algorithm for different test systems are summarized in Table 19.

Table 19:

Wide area monitoring system (WAMS) component cost for different test system.

Test system WAMS component cost with DGs (10ˆ3 USD) WAMS component cost with DGs under restructuring environment (10ˆ3 USD)
Before implementing the proposed algorithm After implementing the proposed algorithm Before implementing the proposed algorithm After implementing the proposed algorithm
Centralized Decentralized Centralized Decentralized
69 bus ADN 5057.694 1910.512 1263.850 5057.694 1936.862 1447.225
123 bus ADN 11,567.311 3385.057 1852.038 11,567.311 3426.874 1995.377
345 bus ADN 108,978.034 40,682.100 10,198.876 108,978.034 40,864.452 12,687.995

The WAMS component cost before implementing the proposed algorithm is 5057.694 (10ˆ3 USD). It consists of µPMUs cost (24,150 USD), PDC cost (8000 USD), CL link length cost (354,544.5 USD) and bandwidth cost (4,671,000). After implementing the proposed algorithm, the total WAMS component cost is reduced to 1910.512 (10ˆ3 USD). Considering the net cash flow equal to the net saving earned by optimizing the WAMS component, i.e., 3147.182 (10ˆ3 USD) subtracting operating & maintenance costs (191,051.2 USD). The NPV of WAMS component optimization was determined using (19) and (20) in IEEE 69 bus system, indicated in  Table 20. Likewise, the NPV for different test systems are determined.

Table 20:

Net present value (NPV) for different test cases.

Test system IEEE 69 bus IEEE 123 bus 345 bus
Centralized Decentralized Centralized Decentralized Centralized Decentralized
With DGs (USD 10ˆ3) 3951.856 4403.170 9847.882 11,354.877 87,311.142 90,567.534
With DGs under restructuring environment (USD 10^3) 3868.376 4312.208 9728.462 10,978.351 86,109.189 89,837.515

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Received: 2021-04-20
Accepted: 2021-10-09
Published Online: 2021-10-22

© 2021 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Theorems to explore the nature of cyber attacks on power system voltage stability
  4. An integrated PMU architecture for power system applications
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  6. Design and performance improvements of solar based efficient hybrid electric vehicle
  7. A fault detection technique based on line parameters in ring-configured DC microgrid
  8. Integration of deterministic and game-based energy consumption scheduling for demand side management in isolated microgrids
  9. Optimal placement of wide area monitoring system components in active distribution networks
  10. Modeling, cost optimization and management of grid connected solar powered charging station for electric vehicle
  11. Improvements in deviation settlement mechanism of Indian electricity grid system through demand response management
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https://doi.org/10.1515/ijeeps-2021-0184
Keywords for this article
active distribution network (ADNs); Phasor Data Concentrator (PDC); Phasor Measurement Unit (PMU); wide area monitoring system (WAMS)

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Theorems to explore the nature of cyber attacks on power system voltage stability
  4. An integrated PMU architecture for power system applications
  5. Commercial building load characteristics modeling considering equipment innate laws and various staff behaviors under demand response mechanism
  6. Design and performance improvements of solar based efficient hybrid electric vehicle
  7. A fault detection technique based on line parameters in ring-configured DC microgrid
  8. Integration of deterministic and game-based energy consumption scheduling for demand side management in isolated microgrids
  9. Optimal placement of wide area monitoring system components in active distribution networks
  10. Modeling, cost optimization and management of grid connected solar powered charging station for electric vehicle
  11. Improvements in deviation settlement mechanism of Indian electricity grid system through demand response management
  12. Design and implementation of an adaptive relay based on curve-fitting technique for micro-grid protection
  13. The comparison and analysis of Type 3 wind turbine models used for researching the stability of electric power systems
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