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Demand side attracts large attention in smart grid for energy efficiency and demand response, and thermostatically controlled appliances (TCAs) are the most potential resources. TCAs scheduling is a basic tool to utilize the flexibility of TCAs to achieve payment savings or peak reduction for users. Current research usually models the users' comfort a hard constraint in TCAs scheduling, which may...
To fulfill demand response to a grid's control command, electric vehicles (EVs) are usually managed via a virtual power plant (VPP), and how to manage the EVs for optimal response is a key issue. Such a problem is defined as an optimal tracking problem (OTP) in the literature, and an improved OTP model considering network constraints is studied in this paper. In order to circumvent the computational...
Energy-intensive enterprises (EIEs) are typical kinds of industrial loads. They consume large amounts of electricity, and are very sensitive to electricity prices. Moreover, they have very good schedulability: they own various adjustable devices and dispatchable self-owned generation units, and have great flexibility in making production decisions. The characteristics of EIEs make them potentially...
Distributed storages have been widely used and studied recently, including batteries and demand side resources, with the development of distributed energy resources (DERs). Each distributed storage has small capacity but the number of all distributed storages is very large, so it is not practical for an independent system operator (ISO) to dispatch these distributed storages directly. A storage aggregator...
In a deregulated market, wholesale energy costs and distribution investment costs contribute significantly to consumers' electricity bills. However, in a low carbon electrical power system, the two cost pressure points may not be synchronous in time and space with each other. This paper develops a novel methodology for home area energy management as a key vehicle for demand response, using electricity...
The network reconfiguration optimal control in distribution networks is modeled as a multi-objective combinational optimization. Multiple objectives are considered for load balancing among the feeders, minimum deviation of the nodes voltage, minimize the power loss and branch current constraint violation. Based on the objectives evaluated by membership functions respectively. These objectives are...
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