IET GENERATION TRANSMISSION & DISTRIBUTION (17518687)17(10)pp. 2401-2418
Economic efficiency is the ultimate goal of all markets, including the electricity market. Several technical and pecuniary restrictions known as externalities in economics literature can significantly affect the economic efficiency of the electricity market. Negative externalities resulting from the operational restrictions of generation units are inherent to electricity markets. In this paper, after reviewing the effects of externalities on the day-ahead electricity markets' economic efficiency using a unit commitment-based model, an innovative and theoretically efficient service-based procedure aimed at internalizing negative externalities in the day-ahead electricity markets is presented. In this way, a new service procured by the energy storage system to provide energy interchange possibilities in the electricity market is introduced. The proposed service uses both price and quantity adjustment methods to internalize externalities. A new discriminatory method for pricing the service and a bi-level optimization problem for determining the capacity of the energy storage system required to provide the service are considered. The consideration of the proposed method facilitates reaching the first-best optimal market solution by alleviating negative externalities existing in the sub-optimal second-best solution in the presence of generation sector operational constraints. Numerical case studies demonstrate the functioning of the proposed externalities internalization scheme.
IEEE Transactions on Energy Markets, Policy and Regulation (27719626)1(4)pp. 420-429
Economic efficiency is the main goal of all markets, including the electricity market. Technical and pecuniary restrictions, known as externalities, caused by the technical limits of generation units are inherent in electricity markets and can significantly affect their economic efficiency. In this article, an efficient service-based method is proposed aimed at internalizing negative externalities in the electricity markets. The method employs services procured by energy storage systems and responsive demand to internalize the generation sector's technical externalities. For the optimal capacity and price of the proposed service, bi-level optimization and an innovative discriminatory pricing scheme are applied. In this way, the first-best optimal market solution can be reached by internalizing the negative externalities in the sub-optimal second-best solution due to the generators' operational constraints. Numerical case studies verify the effectiveness of the proposed scheme, where considering nearly 5% responsive demand and storage capacity around 5% of peak load, it is possible to achieve economic efficiency by reducing the total cost. In real power systems, this cost reduction can result in millions of dollars in annual operational cost savings.
Applied Econometrics and International Development (15784487)15(1)pp. 143-160
This case study estimated an electricity demand function for industrial sector of Iran by applying the structural time series technique to quarterly data for 2000q1-2011q4. In addition to identifying the size and significance of the price and output elasticities, this technique also uncovers UEDT. It is found that the estimated long-run and short-run industrial output elasticities are respectively, 0.85 and 0.36 and the estimated long-run and short-run industrial energy price elasticities are -0.47 and -0.27, respectively. The results suggest that the nature of the trend is not linear and deterministic but stochastic in form. The UEDT for the electricity usage of the industrial sector shows an upward slope.
