A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique

This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

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Ranking Index in the Pareto Optimal Front Based Evolutionary Programming Technique for Best Selection of Several Optimal Multi-Objective Capacity Benefit Margins

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.785.506 ◽

2015 ◽

Vol 785 ◽

pp. 506-510

Author(s):

Muhammad Murtadha Othman ◽

Nurulazmi Abd Rahman ◽

Ismail Musirin

Keyword(s):

Electricity Market ◽

Evolutionary Programming ◽

Test System ◽

Pareto Optimal ◽

Programming Technique ◽

Pareto Optimal Front ◽

Multi Objective ◽

Transfer Capability ◽

Loss Of Load Expectation ◽

Ranking Index

The amount of power transfer between areas is purporting as imperative information required by the utility so that this will assist them towards an effective operation of electricity market performed in a deregulated power system. CBM is defined as the amount of the transfer capability reserved by the load-serving entities which will be used during the case of generation deficiency. This paper presents a new approach used to perform simultaneous determination of capacity benefit margin (CBM) for all areas by using the evolutionary programming (EP) technique. Ranking index in the Pareto optimal front cluster of total loss-of-load expectation (LOLE) and total LOLE difference will be used for selecting several best solutions of multi-objective CBMs. Eventually, performance of the proposed method is investigated thoroughly via a test system of modified IEEE-RTS79. Utilization of the proposed technique is superior in terms of offering flexibility to the utility in selecting several best solutions of multi-objective CBMs.

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A systematic approach to evaluating the influence of demand side management resources on the interarea capacity benefit margin

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v8i4.1587 ◽

2019 ◽

Vol 8 (4) ◽

Cited By ~ 2

Author(s):

Olatunji Obalowu Mohammed ◽

Mohd Wazir Mustafa ◽

Daw Saleh Sasi Mohammed ◽

Sani Salisu ◽

Nabila Ahmad Rufa’i

Keyword(s):

Systematic Approach ◽

Demand Side Management ◽

Test System ◽

Demand Side ◽

Available Transfer Capability ◽

Interconnected System ◽

Transfer Capability ◽

Supply Capacity ◽

Efficient Power ◽

Tie Line

Available transfer capability is an index to measure the security and economic viability of an interconnected system. However, to accurately determine this index, other associated parameters need to be accurately evaluated. One of these parameters is the capacity benefit margin (CBM). For efficient power generation reliability and sustainability, a certain amount of supply capacity is commonly reserved by utilities, which in most cases remain unused, to reduce the effect of generation outage. To minimize this unused reserve, utilities usually reserve a predetermined amount of tie-line capacity between interconnected areas to have access to external supply. This tie-line reserved for this purpose is termed as capacity benefit margin (CBM). In this paper a technique for computing CBM is used, the sensitivity of CBM support from other areas to the increase in load in one of the areas is investigated, and conclusively, demand side management is proposed to improve the quantification of CBM. The contribution of this work is the assessment of the CBMs support from other areas during a critical condition, using the flexibility of DSM technique. The modified 24-bus IEEE reliability test system is employed for the verification of the approach.

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Available Transfer Capability Optimisation Using Evolutionary Programming

Scientific Research Journal ◽

10.24191/srj.v4i2.5656 ◽

2007 ◽

Vol 4 (2) ◽

pp. 13 ◽

Cited By ~ 1

Author(s):

Muhammad Murtadha Othman ◽

Bibi Norashiqin Sheikh Rahimullah

Keyword(s):

Power Flow ◽

Computation Time ◽

Electric Power Industry ◽

Evolutionary Programming ◽

Base Case ◽

Available Transfer Capability ◽

Ac Power ◽

Transfer Capability ◽

Contingency Ranking

In a deregulated electric power industry, transmission providers are required to rapidly produce commercially viable information of available transfer capability (ATC) so that such information can help power marketers, sellers and buyers in planning, operation and reserving transmission services. ATC is a measure of the additional amount of power transfer that may flow across the interface, over and above the base case flows without jeopardizing power system security. This paper presents the ATC determination using the evolutionary programming (EP) technique using modified Gaussian formulation. The proposed EP technique has the ability in providing accurate ATC results and the computation burden caused by the AC power flow solutions are significantly reduced. The outages of critical line that adversely affect the amount of ATC are determined by performing the line contingency ranking and selection. ATC determinations have been made on the case study of Malaysian system. Comparison in terms of accuracy and computation time in estimating the ATC are made by considering the three methods which are the EP using modified Gaussian formulation (EPMG), EP using standard Gaussian formulation (EPSG) and the recursive AC power flow solution (RACPF).

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