Financially optimized scheduling of electric energy storage in presence of renewable energy resources

The increasing integration of Renewable Energy Resources (RER) and the role of Electric Energy Storage (EES) in distribution systems has created interest in using energy management strategies. EES has become a suitable resource to manage energy consumption and generation in smart grid. Optimize scheduling of EES can also maximize retailer’s profit by introducing energy time-shift opportunities. This paper proposes a new strategy for scheduling EES in order to reduce the impact of electricity market price and load uncertainty on retailers’ profit. The proposed strategy optimizes the cost of purchasing energy with the objective of minimizing surplus energy cost in hedging contract. A case study is provided to demonstrate the impact of the proposed strategy on retailers’ financial benefit.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Establishing sustainable and reliable smart grids

This paper addresses challenges part of the shift of paradigm taking place in the way we produce, transmit and use power related to what is known as smart grids. The aim of this paper is to explore present initiatives to establish smart grids as a sustainable and reliable power supply system. We argue that smart grids are not isolated to abstract conceptual models alone. We suggest that establishing sustainable and reliable smart grids depend on series of contributions including modeling and simulation projects, technological infrastructure pilots, systemic methods and training, and not least how these and other elements must interact to add reality to the conceptual models. We present and discuss three initiatives that illuminate smart grids from three very different positions. First, the new power grid simulator project in the electrical engineering PhD program at Queensland University of Technology (QUT). Second, the new smart grids infrastructure pilot run by the Norwegian Centers of Expertise Smart Energy Markets (NCE SMART). And third, the new systemic Master program on next generation energy technology at østfold University College (Hiø). These initiatives represent future threads in a mesh embedding smart grids in models, technology, infrastructure, education, skills and people.

Smart resource control in distribution network to improve the integration level of PV

This project was an innovative approach in developing smart coordination of available energy resources to improve the integration level of PV in distribution network. Voltage and loading issues are considered as the main concerns for future electricity grid which need to be avoided using such resources. A distributed control structure was proposed for the resources in distribution network to avoid noted power quality issues.