13,849 research outputs found

    Charge Scheduling of an Energy Storage System under Time-of-use Pricing and a Demand Charge

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    A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS, and by 8% compared to a scheduling algorithm based on net power.Comment: 13 pages, 2 figures, 5 table

    Towards Intelligent Distribution Systems: Solutions for Congestion Forecast and Dynamic State Estimation Based Protection

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    The electrical distribution systems are undergoing drastic changes such as increasing penetration level of distributed renewable energy sources, energy storage, electrification of energy-efficient loads such as heat pumps and electric vehicles, etc., since the last decade, and more changes are expected in the future. These changes pose challenges for the distribution system operators such as increased level of network congestions, voltage variations, as well as protection settings and coordination, etc. These will require the development of new paradigms to operate distribution systems securely, safely, and economically while hosting a large amount of renewable energy sources.First, the thesis proposed a comprehensive assessment framework to assess the distribution system operator’s future-readiness and support them in determining the current status of their network infrastructures, business models, and policies and thus to identify areas for required developments. The analysis for the future-readiness of the three distribution system operators (from France, The Netherlands, and Sweden) using the proposed assessment framework has shown that presently the distribution system operators have a rather small penetration of renewable energy sources in their grids, however, which is expected to increase in the future. The distribution system operators would need investments in flexibilities, novel forecasting techniques, advanced grid control as well as improved protection schemes. The need for the development of new business models for customers and changes in the policy and regulations are also suggested by the analysis. Second, the thesis developed a congestion forecast tool that would support the distribution system operators to forecast and visualize network overloading and voltage variations issues for multiple forecasting horizons ranging from close-to-real time to day-ahead. The tool is based on a probabilistic power flow that incorporates forecasts of production from solar photovoltaic and electricity demand combined with load models along with the consideration of different operating modes of solar photovoltaic inverters to enhance the accuracy. The congestion forecast tool can be integrated into the existing distribution management systems of distribution system operators via an open cross-platform using Codex Smart Edge technology of Atos Worldgrid. The congestion forecast tool has been used in a case study for two real distribution systems (7-bus feeder and 141-bus system). It was demonstrated in the case study that the tool can predict the congestion in the networks with various prediction horizons. The congestion forecast tool would support distribution system operators by forecasting the network congestion and setting up a congestion management plan.Finally, the dynamic state estimation based protection scheme supported by advanced measurement technologies developed within EU project UNITED-GRID has been implemented and validated experimentally at Chalmers power system laboratory. This dynamic state estimation based protection scheme has a strong advantage over the traditional protection scheme as it does not require any relay settings and coordination which can overcome the protection challenges arising in distribution grids with a large amount of renewable energy sources. The results from the validation of the dynamic state estimation based protection scheme at Chalmers laboratory have shown that the fault detection using this scheme has worked properly as expected for an application of the line protection

    Smart home energy management

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    The new challenges on Information and Communication Technologies (ICT) in Automatic Home Systems (AHS) focus on the methods useful to monitor, control, and optimize the data management flow and the use of energy. An AHS is a residential dwelling, in some cases with a garden or an outdoor space, equipped with sensors and actuators to collect data and send controls according to the activities and expectations of the occupants/users. Home automation provides a centralized or distributed control of electrical appliances. Adding intelligence to the home environment, it would be possible to obtain, not only excellent levels of comfort, but also energy savings both inside and outside the dwelling, for instance using smart solutions for the management of the external lights and of the garden

    Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

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    The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

    Reliability-based economic model predictive control for generalized flow-based networks including actuators' health-aware capabilities

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    This paper proposes a reliability-based economic model predictive control (MPC) strategy for the management of generalized flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamically allocate safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuators’ availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the considered case study.Peer ReviewedPostprint (author's final draft
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