Power & Energy Management in an SG, EMS/DMS

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By Vahraz Zamani and Terry Nielsen

Why is a Distribution System State Estimation (DSSE) is Necessary in an Advanced Distribution Management System? There is some debate in the industry as to whether a Distribution System State Estimator (DSSE) is a critical ADMS function. Without the DSSE, an ADMS uses SCADA measurements, load allocation, and a power flow to determine system state. The premise of state estimation is that by using redundant measurements, it is possible to identify the likely error in each measurement and find the system state that is the best fit. Algorithmically, DSSE estimates the bus voltage using power flow equations derived from the network model, represented in an admittance matrix. DSSE takes several measurements and solves a weighted least-squares problem using an iterative approach. If done properly, the ADMS will have a more accurate system state solution to use in all the advanced applications such as Voltage Optimization.

By William Hederman and Vince Cushing

The U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) has taken important steps forward from the long-standing "grid modernization" policy in the last few years.  Specifically, EERE is pursuing a grid-interactive efficient building initiative. Building-grid integration can enhance the grid resilience, efficiency, and other desired network characteristics. At the IEEE PES ISGT conference in Washington, DC in February 2020, there were reports on actual accomplishments from such integration. This technical note summarizes the important progress of one such project.

By Jorge L. Angarita, Jorge Martínez-Crespo, and Ameena Al Sumaiti


The Energy Storage Systems (ESS) -hydro pumping stations and battery systems, for example- are becoming a realistic alternative to act in the wholesale markets as any other participant, i.e. generators, consumers or prosumers. The increasing interest in ESS for the grid can be due to multiple factors, amongst others, the progressive integration of renewable energy sources, the high capital costs of handling peak demands or the investments required for the improvement of the grid reliability.

This article poses a model to calculate the revenue streams of ESS (batteries) in the Mexican electricity pool market. The model considers revenues from energy trading as a result of buying energy at a low price and selling it at a higher price acting in a day-ahead market (DAM). Another revenue stream could come from selling capacity or ancillary services, but this type of revenue is not considered here.

By Claude Ziad El-Bayeh, Khaled Alzaareer

Nowadays, energy demand is increasing rapidly worldwide due to the unprecedented comfortable lifestyle that people are becoming familiar with. The newly introduced heavy electrical loads such as electric vehicles and battery storage systems require much energy. The main problem is that they can introduce peak demands in certain periods, which would affect the stability of the grid. To solve this problem, renewable energy sources such as PV, wind turbines, concentrated solar power technologies are promoted. To install such systems, large land use is needed, while fewer land requirements are needed to install traditional coal or fuel-based thermal power plants. Some challenges can complicate the installation of renewable energy technologies, such as the high price of a land and lack of land area to install such systems. Therefore, a viable solution is to use the rooftop to install PV systems, wind turbines, and other renewable energy technologies to generate electricity and energy (heating/cooling). The available surface on a building including rooftop and facades may not be sufficient to generate electricity that supplies the whole energy demand of a building. The main question is how to create sustainable and self-sufficient buildings using only the existing and available surface of the building? This article attempts to answer this question with a few steps and recommendations to follow.

IEEE Smart Grid Newsletter Editors








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