S A SOMAN
Articles written in Sadhana
Volume 41 Issue 10 October 2016 pp 1123-1133
Combining forecasts in short term load forecasting: Empirical analysis and identification of robust forecaster
YOGESH K BICHPURIYA S A SOMAN A SUBRAMANYAM
We present an empirical analysis to show that combination of short term load forecasts leads to better accuracy. We also discuss other aspects of combination, i.e.,distribution of weights, effect of variation in the historical window and distribution of forecast errors. The distribution of forecast errors is analyzed in order to get a robust forecast. We define a robust forecaster as one which has consistency in forecast accuracy, lesser shocks (outliers) and lower standard deviation in the distribution of forecast errors. We propose a composite ranking (CRank) scheme based on a composite score which considers three performance measures—standard deviation, kurtosis of distribution of forecast errors and accuracy of forecasts. The CRank helps in identification of a robust forecasts given a choice of individual and combined forecaster. The empirical analysis has been done with the real life data sets of two distribution companies in India.
Volume 45 All articles Published: 18 July 2020 Article ID 0183
A cost-causal marginal participation method using min-max fairness for transmission services cost allocation
RASHESH P MEHTA M S S RAO S A SOMAN
We consider the problem of fair allocation of the cost of a transmission system among load and generation entities using the marginal participation approach. We show that a cost-causal approach involving capacity-based line cost rate and a min-max fair economic slack bus selection for price-taking entities leads to arigorously fair and more accurate implementation of marginal participation method. In the existing methods the counter-flows are masked, which is a compromise with fairness and linearity. However, if the counter-flows areincentivized then it can lead to pay-offs to some entities. The proposed approach solves the problem of pay-offs without masking the counter-flows. This is achieved by separation of the total transmission services cost into usage, reliability and residual capacity components. The allocation of the first two components is based on the min-max fairness policy, and the residual capacity costs are allocated on a pro-rata basis. Simulation results on multiple IEEE test systems, Indian utility power systems and extensive comparative evaluations for the contemporary methods demonstrate the claims made.
Volume 47 All articles Published: 31 March 2022 Article ID 0062
A novel method for transmission system cost allocation with better accuracy and fairness
RASHESH P MEHTA S A SOMAN M S S RAO
This paper proposes an integrated method for the accurate and fair cost allocation of the transmission system among the users (generators and loads) of the network. It mitigates the existing research gaps and implementation issues in the marginal participation approach for network cost allocation. Major challengesin the marginal participation approach are 1) fair selection of economic slack busses 2) inaccuracy due to use of DC power flow 3) treatment of the counter flows and 4) enforcement of cost-causality. While the prior art has addressed the sub-problems individually, an integrated approach has been missing. This work fills this research gap. Besides, it for the first time introduces the use of linearized AC power flow for calculating the marginal flows. This provides a major improvement over the DC power flow model as nominal voltage and reactive power variables can be modeled without compromising linearity. Economic slack bus selection by min-max fairness approach, modelling of counter flows without resulting in negative cost-shares (payoffs), enhancement of costcausalityby segregating usage cost, reliability cost, and residual costs are other salient contributions of the proposed work. These features result in a rigorously fair, accurate, and yet tractable method computationally. Case-studies on many systems including the IEEE-118 bus system demonstrate the claims made.
Volume 48, 2023
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