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Morteza Nazari-Heris

Researcher at Pennsylvania State University

Publications -  101
Citations -  2495

Morteza Nazari-Heris is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Electric power system & Renewable energy. The author has an hindex of 23, co-authored 84 publications receiving 1562 citations. Previous affiliations of Morteza Nazari-Heris include University of Tabriz.

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Optimal economic dispatch of FC-CHP based heat and power micro-grids

TL;DR: In this article, a probabilistic framework based on a scenario method, which is considered for load demand and price signals, is employed to overcome the uncertainties in the optimal energy management of the MG.
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A comprehensive review of heuristic optimization algorithms for optimal combined heat and power dispatch from economic and environmental perspectives

TL;DR: The most popular heuristic and meta-heuristic optimization algorithms are studied in this paper, and implementation of the optimization procedures for the solution of CHPED problem taking into account the objective functions and different constrains are discussed.
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Solving combined heat and power economic dispatch problem using real coded genetic algorithm with improved Mühlenbein mutation

TL;DR: In this article, a real coded genetic algorithm with improved Muhlenbein mutation (RCGA-IMM) was proposed for solving the combined heat and power economic dispatch (CHPED) optimization problem.
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Economic-environmental effect of power to gas technology in coupled electricity and gas systems with price-responsive shiftable loads

TL;DR: In this paper, a multi-objective two-stage stochastic unit commitment scheme for integrated gas and electricity networks taking into account novel flexible energy sources such as P2G technology and demand response (DR) programs as well as high penetration of wind turbines was proposed.
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Robust Short-Term Scheduling of Integrated Heat and Power Microgrids

TL;DR: The optimal solution, provided for optimal scheduling of MG, prevents the MG from being exposed to high operational cost considering the undesired deviation of market power prices from the forecasted amount.