Mokhtar Bozorg

Probabilistic Spinning Reserve Provision Model in Multi-Control Zone Power System

Inter-zonal trading in multi-area power system (MAPS) improves the market efficiency and the system reliability by sharing the resources (energy and reserve services) across zonal boundaries. Actually, each area can operate with less reserve resources than would normally be required for isolated operation. The aim of this work is to propose a model that includes the problem of optimal spinning reserve (SR) provision into the security constraint unit commitment (SCUC) formulation based on the reliability criteria for a MAPS. The loss of load probability (LOLP) and the expected load not served (ELNS) are evaluated as probabilistic metrics in the case of a multi-control zone power system. Moreover, we demonstrate how these criteria can be explicitly incorporated into the market-clearing formulation. The non-coincidental nature of spinning reserve requirement across the zonal boundary is effectively modeled. Two system cases including a small-scale (six-bus) test system and the IEEE reliability test system (IEEE-RTS) are used to demonstrate the effectiveness of the presented model.

Developing Offer Curves for an Electric Railway Company in Reserve Markets Based on Robust Energy and Reserve Scheduling

This paper proposes an appropriate offering strategy method for an electric railway company (ERC) to participate in reserve markets. In this respect, first the problem of energy and reserve scheduling for the ERC is modeled in a deterministic way. Next, a robust optimization technique is used to solve the problem taking into account the uncertain energy and reserve prices as well as the uncertain hourly energy demand of the electric railway substations. Afterward, a reserve offering curve construction algorithm based on the solution of robust energy and reserve scheduling is proposed. This algorithm takes into account the correlation between upward and downward reserve prices. Finally, to show the effectiveness of the proposed method, a realistic case study based on the characteristic of an ERC in Switzerland is presented.

Converter placement in the interconnection of railway power grid and public power grid based on cost-reliability approach

The railway load in Switzerland is expected to increase in the next years. Increasing the capacity of the interconnection between the railway power system and the public grid is a reasonable solution to deal with this problem. This paper proposes a way to find the locations and capacities for new interconnections and the capacity expansion for the existing one. To show the effectiveness of the proposed model, the networks in the Suisse Romande region (French part of Switzerland) is considered as a case study.

Energy and reserve scheduling for Electric Railway power system using stochastic optimization

This paper proposes an optimal joint energy and reserve scheduling model for electric railway power system which is operated by an Electric Railway Company (ERC). The model relies on a two stage stochastic optimization method that accounts for the uncertainties of the ERC energy demand and the availability of its generators and interconnecting converters. A case study based on the characteristics of Swiss railway power system in the western part of Switzerland is presented to demonstrate the effectiveness of the proposed model.

Statistical analysis of optimal energy and security controls under different sources of uncertainties

The management of uncertainties is a challenging task for reliable and secure operation of power systems. The uncertainties come from multiple sources, including the forecast errors of wind power and load, the forced outage of generating units, loss of transmission equipments, etc. This paper classifies different uncertainties based on their binary and continuous attributes. The main idea is to investigate the effect of each source of uncertainties on the cost of energy and security controls. For this purpose, a specific optimization method is developed which takes into account a forecasted scenario and a stochastic scenario. This optimization problem is solved for a fixed forecasted scenario and a varying stochastic scenario. The stochastic scenarios are constructed using a Monte Carlo Simulation that considers various sources of uncertainties. The main advantage of the proposed optimization is that the number of incorporated stochastic scenarios does not increase the size of the optimization problem. The models of different uncertainties, particularly wind power forecast errors, are discussed in depth. This optimization allows obtaining the statistical moments and constructing the probability distributions. The proposed optimization approach is then applied to the IEEE RTS 24-bus system. The probability distributions and statistical moments of objective functions and control variables are assessed for three cases, namely: (i) with only binary uncertainties, (ii) with only continuous uncertainties and (iii) with both of them.