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Publications

Publications by Mohamed Lotfi

2019

Urban Wind Resource Assessment: A Case Study on Cape Town

Authors
Gough, M; Lotfi, M; Castro, R; Madhlopa, A; Khan, A; Catalao, JPS;

Publication
ENERGIES

Abstract
As the demand for renewable energy sources energy grows worldwide, small-scale urban wind energy (UWE) has drawn attention as having the potential to significantly contribute to urban electricity demand with environmental and socio-economic benefits. However, there is currently a lack of academic research surrounding realizable UWE potential, especially in the South African context. This study used high-resolution annual wind speed measurements from six locations spanning Cape Town to quantify and analyze the city's UWE potential. Two-parameter Weibull distributions were constructed for each location, and the annual energy production (AEP) was calculated considering the power curves of four commonly used small-scale wind turbines (SWTs). The two Horizontal Axis Wind Turbines (HAWTs) showed higher AEP and capacity factors than Vertical Axis Wind Turbine (VAWT) ones. A diurnal analysis showed that, during summer, an SWT generates the majority of its electricity during the day, which resembles the typical South African electricity demand profile. However, during winter, the electricity is mainly generated in the early hours of the morning, which does not coincide with the typical load demand profile. Finally, the calculation of Levelized Cost of Electricity (LCOE) showed that SWT generation is more expensive, given current electricity market conditions and SWT technology. The study provides a detailed, large-scale and complete assessment of UWE resources of Cape Town, South Africa, the first of its kind at the time of this work.

2019

Optimal Spinning Reserve Allocation in Presence of Electrical Storage and Renewable Energy Sources

Authors
Javadi, MS; Lotfi, M; Gough, M; Nezhad, AE; Santos, SF; Catalao, JPS;

Publication
2019 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2019 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)

Abstract
This paper investigates the optimal allocation of Spinning Reserve (SR) for power systems in the presence of Renewable Energy Sources (RES) and Electrical Energy Storage (EES) devices. This is done in order to reduce the system's dependency on thermal generation units and the decrease total daily operational cost. A Security Constrained Unit Commitment (SCUC) model for a typical power system was used, which includes thermal and renewable generation units and EES devices in the form of batteries. In the proposed model, the hourly operation strategy is determined by adopting a predetermined level of SR. In order to optimize SR requirements, the Independent System Operator (ISO) runs the SCUC problem and determines the minimum SR that should be provided by generation units and EES devices. The simulation results illustrate that by optimizing the operation of batteries, the ISO can effectively reduce the required capacity of thermal units. Therefore, optimal SR allocation under RES uncertainty is determined in this study.

2019

Two-Stage Stochastic Mixed Integer Programming Approach for Optimal SCUC by Economic DR Model

Authors
Kia, M; Etemad, R; Heidari, A; Lotfi, M; Catalao, JPS; Shafie Khah, M; Osorio, GJ;

Publication
2019 IEEE MILAN POWERTECH

Abstract
Due to influences by power system restructuring, fuel price uncertainties, future demand forecasting, and utilities and transmission lines availability, demand response (DR) programs for consumers have gained more attention. One important DR scheme is the emergency demand response program (EDRP). This paper focuses on simultaneous implementation of security-constraint unit commitment (SCUC) and EDRP by using an economic model. Moreover, a stochastic optimization method is employed for realistic modelling. Since the combined implementation of SCUC and EDRP results in a complex nonlinear optimization problem, a linearization method to ensure computational efficiency is used. The proposed model is formulated as two-stage Stochastic Mixed-Integer Programming ( SMIP) model implemented using GAMS. The implemented model is tested on three case studies using the IEEE 24-bus system. Results are analyzed with a focus on the impact of demand elasticity and electricity prices.

2019

Stochastic Security Constrained Unit Commitment with High Penetration of Wind Farms

Authors
Kia, M; Hosseini, SH; Heidari, A; Lotfi, M; Catalao, JPS; Shafie khah, M; Osorio, G; Santos, SF;

Publication
2019 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2019 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)

Abstract
Secure and reliable operation is one of the main challenges in restructured power systems. Wind energy has been gaining increasing global attention as a clean and economic energy source, despite the operational challenges its intermittency brings. In this study, we present a formulation for electricity and reserve market clearance in the presence of wind farms. Uncertainties associated with generation and line outages are modeled as different system scenarios. The formulation incorporates the cost of different scenarios in a two-stage short-term (24-hours) clearing process, also considering different types of reserve. The model is then linearized in order to be compatible with standard mixed-integer linear programming solvers, aiming at solving the security constrained unit-commitment problem using as few variables and optimization constraints as possible. As shown, this will expedite the solution of the optimization problem. The model is validated by testing it on a case study based on the IEEE RTS1, for which results are presented and discussed.

2019

Analyzing the Role of Microgrids to Mitigate the Effects of Forecasting Error of Renewable Distributed Generators

Authors
Lujano Rojas, JM; Dominguez Navarro, JA; Yusta, JM; Osorio, GJ; Santos, SF; Lotfi, M; Catalao, JPS;

Publication
2019 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2019 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)

Abstract
In this study, the operation of an energy system composed of a battery energy storage system (BESS) and a conventional generator to compensate the forecasting error of renewable power production has been analyzed. A scenario with low forecasting error and another with high forecasting error have been synthetically modeled and incorporated to a computational model of the energy system. The results obtained from a case study suggest that a low forecasting error could be compensated by a single BESS. However, a high forecasting error would require the installation of a controllable power source such as a conventional generator.

2019

Multiobjective Congestion Management and Transmission Switching Ensuring System Reliability

Authors
Sheikh, M; Aghaei, J; Rajabdorri, M; Shafie khah, M; Lotfi, M; Javadi, MS; Catalao, JPS;

Publication
2019 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2019 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)

Abstract
Congestion in transmission lines is an important topic in power systems and it continues to be an area of active research. Various approaches have been proposed to mitigate congestion especially immediate ready ones such as Congestion Management (CM) and Transmission Switching (TS). Using either of the two or their combination (CMTS) may have undesirable consequences like increasing operational costs or increasing the number of switching of transmission lines. More switching aggravates system reliability and imposes extra costs on the operator. In this paper, a multi-objective model is introduced which reduces overall operation costs, the number of switching in transmission lines, and the congestion of lines, compared to available approaches which employ congestion management and TS simultaneously. To verify the performance of the proposed model, it is implemented using GAMS and tested on 6- and 118- bus IEEE test systems. A benders' decomposition approach was employed.

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