Addressing loss due to transmission and its cost allocation in deregulated electricity market is an essential issue. Independent System Operator (ISO) provides the real power loss from the generators and the associated cost is allocated to the concerned parties in a fair way. The generators and loads participate in the loss/cost allocation process. The highlight of the paper is that the effect of mutual inductance (MI) that exists on transmission line in transmission loss/cost allocation process for bilateral contracts is illustrated. To demonstrate the effect of mutual inductance, the results of two existing loss allocation methods like penalized quoted cost (PQC) based approach and proportional generation and proportional load (PGPL) based approach are discussed. Effect of mutual inductance is presented using an IEEE 14 bus system. The simulation results are carried out using MATLAB R2014a. The result shows that mutual inductance has a significant impact on transmission loss and hence cannot be ignored. © 2017 IEEE.

Prabhakar Karthikeyan S

Department of Electrical Engineering

School of Electrical Engineering

Vellore Campus

Shafeeque Ahmed K

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Impact of transmission line mutual inductance on transmission loss/cost allocation in deregulated electricity market

2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

Transmission loss/cost allocation to the individual buses in a fair way is an essential issue in restructured electricity market. This paper splits active power transmission loss into two components namely real and reactive loss component. The real and reactive loss components are due to the real power transaction from the generator to the load and reactive power demand of the load respectively. The active power loss changes due to the reactive power loads and this increase in loss are allocated to the relevant loads based on load sensitivity factor (LSF). The loss allocation using LSF is a valid approach as it is derived from solved load flow solution. The cost allocation of real loss component to a transaction and reactive loss component to loads is based on the loss contribution fraction (LCF) and LSF respectively. The highlight of this paper is to allocate real loss component to the respective buses equally and to allocate the cost of reactive loss component to the respective loads in a fair way. This paper also presents a detailed discussion on impact of mathematical loss and comparison with four existing loss allocation methods. All the methods are discussed by considering with and without reactive power load. The effectiveness of the proposed approach is illustrated using a sample four bus and 30 bus IEEE system. © 2018 Elsevier Ltd

Sustainable Energy, Grids and Networks

Modified penalized quoted cost method for transmission loss allocation including reactive power demand in deregulated electricity market

In deregulated electricity market, economic allocation of transmission loss to the generators and the loads in a fair way is a tremendous challenge for power engineers. This paper presents a methodology to price the real power loss due to bilateral contracts considering reactive power drawn by the loads. The real power loss is divided into two components namely transaction loss component and reactive power loss component. Transaction loss component is due to the bilateral contracts and reactive power loss component is due to the reactive power demand of the loads. Based on transaction loss factor and reactive power loss factor the total cost for real power loss is allocated to both generators and loads. Transaction loss factor depends on quantum of real power generation and load and hence cost of transaction loss component is shared among the generators and the loads equally. Reactive power loss factor depends on quantum of reactive power demand of the loads and hence cost of reactive power loss component is allocated to the loads. The results of the proposed approach in comparison with other loss allocation methods are presented using an IEEE 30 bus system. The simulation is carried out using MATLAB R2014a. © 2017 IEEE.

TENCON 2017 - 2017 IEEE Region 10 Conference

Proportional generation and proportional load based transmission loss allocation considering reactive power demand in restructured environment

Electricity deregulation has caused rapid changes in electricity market structure. Vertically integrated utility which performed all the functions including generation, transmission, distribution and retail services are now disaggregated into separate companies devoted to each function. The main goal of this deregulation is to enhance competition and provide new choices and economic benefits to the consumers. In a deregulated environment, determination of Market Clearing Price (MCP) is the main objective of a pool operator. Market Clearing Price is based on bids received from the generators as well as consumers. The Independent System Operator (ISO) finds out the Market Clearing Price based on these bids from generators and consumers. The calculation of market clearing price using conventional methods is not suitable for spot market as they are slow and less efficient. In this paper, optimum generation cost is determined using metaheuristic optimization techniques like firefly algorithm and particle swarm optimization and comparative analysis of optimum generation is also carried out using these techniques. Optimum location of DG is also determined in this work. Both fixed and variable demands are considered in this paper. IEEE standard 9 bus system is taken as the test system and the programming is carried out using MATLAB platform (R2014a). © 2017 IEEE.

Optimization of market clearing price using firefly and PSO algorithm in bilateral electricity market

Transmission losses are considered to be thekey factor of power generation to meet the load requirement. Deregulated electricity markets operate under bilateral market, pool market or hybrid market. In this competitive electricity market, Independent System Operator (ISO) should allocate transmission losses among the involved partners in a fair way. Transmission loss pricing should take into account the distance between the generator and the load. This paper presents a detail discussion and comparison of five recent and relevant loss allocation methods like penalized quoted cost (PQC), proportional generation and proportional load (PGPL), proportional sharing, Zbus and modified Zbus method. The significance of PQC and PGPL methods are highlighted with other methods. The results are presented for a sample 6 bus system and IEEE 14 bus system. The simulation results are obtained using MATLAB R2014a. © 2017 IEEE.

2017 Innovations in Power and Advanced Computing Technologies (i-PACT)

Comparison of various transmission loss/cost allocation methods — A review

Supplying transmission losses economically under bilateral contract is a challenge for power engineers. In this study, penalised quoted cost (PQC) based approach is proposed where generators will participate for supplying the transmission losses which may be incurred from their customers through their bilateral contracts in a deregulated electricity market. The loss supplying generators will quote the cost and the quantum of real power that can be supplied by them to independent system operator (ISO) in a day-ahead market. This study presents a lucid approach for loss allocation economically by ranking the loss supplying generators based on their PQC. Penalty factor for each loss supplying generator is calculated using the loss coefficients. ISO will meet the losses due to bilateral contracts in an economical way by selecting the generators with minimum PQC and the associated cost is allocated to the individual transactions based on loss contribution fraction. The proposed algorithm is tested using a sample four-bus system and IEEE 30 bus system using MATLAB R2014a. This method is based on the participation of generators and their given quotation in transmission loss allocation process. The study gives both the real power loss/cost allocation to the generators and for individual transactions. © The Institution of Engineering and Technology 2016.

IET Generation, Transmission & Distribution

Penalised quoted cost based approach on transmission loss allocation for a bilateral contract in deregulated electricity market

Fair allocation of transmission loss is a challenging task for power engineers in deregulated electricity market. One of the key roles of Independent System Operator (ISO) is to provide the details of transmission loss in real time and to allocate the associated cost to the involved parties. For effective and reliable operation of power system, compensation of real and reactive power loss in real time is essential. For a bilateral contract, a generator and a load is involved in the transmission loss allocation process. This paper presents a simple, novel and a fair method to allocate real power loss due to bilateral contracts. The total cost for supply of loss is allocated to the generators and loads based on loss factors. Two loss factors are computed namely generator loss factor for generators and load loss factor for loads. Loss factors are computed from the AC load flow. The proposed method is tested on IEEE 30 bus system and a comparison is made with the other existing methods like proportional sharing, Zbusand modified Zbus. MATLAB R2014a is used for all simulations. © 2016 IEEE.

Journal	Data powered by Typeset2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
Publisher	Data powered by TypesetIEEE
Open Access	0