Browsing by Author "Nehrir, M. Hashem"

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A Load Profile Management Integrated Power Dispatch Using a Newton-Like Particle Swarm Optimization Method
(2014-10) Wang, Caisheng; Miller, Carol J.; Nehrir, M. Hashem; Sheppard, John W.; McElmurry, Shawn P.
Load profile management (LPM) is an effective demand side management (DSM) tool for power system operation and management. This paper introduces an LPM integrated electric power dispatch algorithm to minimize the overall production cost over a given period under study by considering both fuel cost and emission factors. A Newton-like particle swarm optimization (PSO) algorithm has been developed to implement the LPM integrated optimal power dispatch. The proposed Newton-like method is embedded into the PSO algorithm to help handle equality constraints while penalty/fitness functions are used to deal with inequality constraints. In addition to illustrative example applications of the proposed Newton-like PSO technique, the optimization method has been used to realize the LPM integrated optimal power dispatch for the IEEE RTS 96 system. Simulation studies have been carried out for different scenarios with different levels of load management. The simulation results show that the LPM can help reduce generation costs and emissions. The results also verify the effectiveness of the proposed Newton-like PSO method.
Multi-Timescale Power Management for Islanded Microgrids Including Storage and Demand Response
(2015-05) Pourmousavi Kani, Seyyed Ali; Nehrir, M. Hashem; Sharma, R.K.
Power management is an essential tool for microgrid (MG) safe and economic operation, particularly in the islanded operation mode. In this paper, a multi-timescale cost-effective power management algorithm (PMA) is proposed for islanded MG operation targeting generation, storage, and demand management. Comprehensive modeling, cost, and emission calculations of the MG components are developed in this paper to facilitate high accuracy management. While the MGs overall power management and operation is carried out every several minutes to hours, depending on the availability of the required data, simulation for highly dynamic devices, such as batteries and electric water heaters (EWHs) used for demand response (DR), are performed every minute. This structure allows accurate, scalable, and practical power management taking into consideration the intrainterval dynamics of battery and EWHs. Two different on/off strategies for EWH control are also proposed for DR application. Then, the PMA is implemented using the two different DR strategies and the results are compared with the no-DR case. Actual solar irradiation, ambient temperature, nonEWH load demand, and hot water consumption data are employed in the simulation studies. The simulation results for the MG studied show the effectiveness of the proposed algorithm to reduce both MGs cost and emission.