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A home energy management (HEM) system is an integral part of a smart grid that can potentially enable demand response applications for residential customers. This paper presents an intelligent HEM algorithm for managing high power consumption household appliances with simulation for demand response (DR) analysis. The proposed algorithm manages household loads according to their preset priority and guarantees the total household power consumption below certain levels. A simulation tool is developed to showcase the applicability of the proposed algorithm in performing DR at an appliance level. This paper demonstrates that the tool can be used to analyze DR potentials for residential customers. Given the lack of understanding about DR potentials in this market, this work serves as an essential stepping-stone toward providing an insight into how much DR can be performed for residential customers.Index Terms-Customer choice, demand response (DR), home energy management (HEM), load priority, smart appliance.

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As Plug-in Hybrid Vehicles (PHEVs) take a greater share in the personal automobile market, their penetration levels may bring potential challenges to electric utility especially at the distribution level. This paper examines the impact of charging PHEVs on a distribution transformer under different charging scenarios. The simulation results indicate that at the PHEV penetration level of interest, new load peaks will be created, which in some cases may exceed the distribution transformer capacity. In order to keep the PHEVs from causing harmful new peaks, thus making the system more secure and efficient, several PHEV charging profiles are analyzed and some possible demand management solutions, including PHEV stagger charge and household load control, are explored. Index Terms--Demand management, household load control, PHEVs and stagger charge. VIII. BIOGRAPHIESShengnan Shao (S'08 -IEEE) is pursuing her Ph.D. degree in the he is serving as the vice president for New Initiatives and Outreach for the IEEE PES and a member of its Board. He is a member-at-large of the IEEE-USA Energy Policy Committee. He is a distinguished lecturer of IEEE PES, and has published over 300 papers on conventional and renewable energy systems, load forecasting, uncertainty evaluation and infrastructure planning.

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Abshxct-The aim ofthis paper is to provide the core of a CAn/CAA tool that can help designers detennine the optimal design of a hybrid wind-solar power system for either autonomous or grid-linked applications. The proposed analysis einploys linear programming techniques to minimize the average production cost of electricity while meeting the load requircinents in a reliable manner, and takes environmental factors into consideration both in the design and operation phases. While in autoiionious systems, the environmental credit gained as compared to diesel alternatives can be obtained through direct optimization, in grid-linked systems eiiiission is another variable to be minimized such that the use of renewable energy can be justified. A controller that monitors the operation of the autonornoudgrid-linked system is designed. Such a colitloller dctei miles the energy available from each of the system components atid the environmental credit of the system. It then gives details relatcd to cost, uninet arid spilled energies, and battery charge and discharge losses. I . 2. 3.minimizing the electricity production cost ($/KWh), ensuring that the load is served according to a certain reliability criteria, and minimizing the power purchased from the grid.The cost fiinction is defined as [8]: 4 1 f=(c Ik-SPk+OA4 )-k= I Pk E,.Nwhere the index k is made to account for wind, solar, diesel generators or grid connection, and batteries.