S. M. Moghaddas Tafreshi

Bio: S. M. Moghaddas Tafreshi is an academic researcher from K.N.Toosi University of Technology. The author has contributed to research in topics: Electricity market & Microgrid. The author has an hindex of 9, co-authored 16 publications receiving 240 citations. Previous affiliations of S. M. Moghaddas Tafreshi include University of Gilan.

A developed energy management system for a microgrid in the competitive electricity market

Abstract: This paper presents a developed energy management system for a microgrid (MG). This Microgrid Management System (MMS) generates an optimum operation plan for a microgrid on next day. This planning is optimized from economical view point based on profit maximization while abiding by system constraints and regulatory rules. The MG considered in this paper consists of wind turbine, microturbines, photovoltaic array, fuel cell, electrolyzer, H 2 storage tank, reformer, a boiler, electrical and thermal loads. Also in the model possibility of selling and buying electrical energy from the local grid is considered. This system includes the operational cost, thermal recovery, power trade with the local grid, and hydrogen production.

Contract-based utilization of plug-in electric vehicle batteries for day-ahead optimal operation of a smart micro-grid

Abstract: The development of smart micro-grids makes the use of new and green technologies like plug-in electric vehicles more suitable. The plug-in electric vehicles can play a role in storing energy due to their network connection capability. The smart micro-grid can use this stored energy to reduce its operating cost. In this paper, a new mechanism based on the contractual agreements between the owners of plug-in electric vehicles and the smart micro-grid is proposed to provide the system's energy during the operating day. The proposed model enables plug-in electric vehicles parked in official parking to be integrated into the operation of smart micro-grid and earn revenue. The operation optimization is formulated as a two-stage stochastic mixed-integer linear problem and is implemented on energy management of a typical smart micro-grid as a case study. The simulation results confirm the effectiveness of the proposed design for both smart micro-grid and plug-in electric vehicles in the case of expected cost reduction. Also, the performance of the stochastic model for uncertainty handling is shown by the value of the stochastic solution.

Operation optimization for a virtual power plant

Abstract: In the 21st century the concept of electrical power supply is morphing gradually from centralized into decentralized system, indicated by increasing the Installation of distributed generation on the main grid With emerging of advanced Communication and information technology, the aggregation of several small size, environmentally compatible, generators close to the loads can be developed as virtual power plant in order to provide added-value to the electric Power system In this paper an operation optimization algorithm is proposed to integrate two DGs and a micro grid into a VPP control area, containing several loads, which will be able to generate and sell electrical energy to loads and power market Suitable models are proposed to simulate electric production, and the energy exchange between VPP and Grid The optimization problem is here formulated as a non-liner maximization algorithm with constraints, where the objective function is profit of the VPP with supply of electric energy for all the loads Solving the VPP optimization problem in two different scenarios with GAMS software will complete the paper

Hydrogen Production From Water Electrolysis: Current Status and Future Trends

Abstract: This paper reviews water electrolysis technologies for hydrogen production and also surveys the state of the art of water electrolysis integration with renewable energies. First, attention is paid to the thermodynamic and electrochemical processes to better understand how electrolysis cells work and how they can be combined to build big electrolysis modules. The electrolysis process and the characteristics, advantages, drawbacks, and challenges of the three main existing electrolysis technologies, namely alkaline, polymer electrolyte membrane, and solid oxide electrolyte, are then discussed. Current manufacturers and the main features of commercially available electrolyzers are extensively reviewed. Finally, the possible configurations allowing the integration of water electrolysis units with renewable energy sources in both autonomous and grid-connected systems are presented and some relevant demonstration projects are commented.

Optimum design of hybrid renewable energy systems: Overview of different approaches

Abstract: Public awareness of the need to reduce global warming and the significant increase in the prices of conventional energy sources have encouraged many countries to provide new energy policies that promote the renewable energy applications. Such renewable energy sources like wind, solar, hydro based energies, etc. are environment friendly and have potential to be more widely used. Combining these renewable energy sources with back-up units to form a hybrid system can provide a more economic, environment friendly and reliable supply of electricity in all load demand conditions compared to single-use of such systems. One of the most important issues in this type of hybrid system is to optimally size the hybrid system components as sufficient enough to meet all load requirements with possible minimum investment and operating costs. There are many studies about the optimization and sizing of hybrid renewable energy systems since the recent popular utilization of renewable energy sources. In this concept, this paper provides a detailed analysis of such optimum sizing approaches in the literature that can make significant contributions to wider renewable energy penetration by enhancing the system applicability in terms of economy.

Bidding Strategy of Virtual Power Plant for Participating in Energy and Spinning Reserve Markets—Part I: Problem Formulation

Abstract: This paper addresses the bidding problem faced by a virtual power plant (VPP) in a joint market of energy and spinning reserve service. The proposed bidding strategy is a non-equilibrium model based on the deterministic price-based unit commitment (PBUC) which takes the supply-demand balancing constraint and security constraints of VPP itself into account. The presented model creates a single operating profile from a composite of the parameters characterizing each distributed energy resources (DER), which is a component of VPP, and incorporates network constraints into its description of the capabilities of the portfolio. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and solved by genetic algorithm (GA).

Cloud Computing Applications for Smart Grid: A Survey

Abstract: The fast-paced development of power systems necessitates smart grids to facilitate real-time control and monitoring with bidirectional communication and electricity flows. Future smart grids are expected to have reliable, efficient, secured, and cost-effective power management with the implementation of distributed architecture. To focus on these requirements, we provide a comprehensive survey on different cloud computing applications for the smart grid architecture, in three different areas— energy management , information management , and security . In these areas, the utility of cloud computing applications is discussed, while giving directions on future opportunities for the development of the smart grid. We also highlight different challenges existing in the conventional smart grid (without cloud application) that can be overcome using cloud. In this survey, we present a synthesized overview of the current state of research on smart grid development. We also identify the current research problems in the areas of cloud-based energy management, information management, and security in smart grid.

Optimal Bidding Strategy for Microgrids Considering Renewable Energy and Building Thermal Dynamics

Abstract: In this paper, we study an optimal day-ahead price-based power scheduling problem for a community-scale microgrid (MG). The proposed optimization framework aims to balance between maximizing the expected benefit of the MG in the deregulated electricity market and minimizing the MG operation cost considering users' thermal comfort requirements and other system constraints. The power scheduling and bidding problem is formulated as a two-stage stochastic program where various system uncertainties are captured by using the Monte Carlo simulation approach. Our formulation is novel in that it can exploit the thermal dynamic characteristics of buildings to compensate for the variable and intermittent nature of renewable energy resources and enables us to achieve desirable tradeoffs for different conflicting design objectives. Extensive numerical results are presented to demonstrate the great benefits in exploiting the building thermal dynamics and the flexibility of the proposed scheduling method in achieving different practical design tradeoffs. We also investigate the impacts of different design and system parameters on the curtailment of renewable energy resources and the optimal expected profit of the MG.