Energy management system for smart grid: An overview and key issues

A systematic decision-making approach for planning and assessment of hybrid renewable energy-based microgrid with techno-economic optimization: A case study on an urban community in Egypt

To honor the enormous contribution that the applied mathematician Lee Segel made to the Springer journal Bulletin of Mathematical Biology (BMB) and the field of mathematical biology as a whole, Springer, in partnership with the Society of Mathematical Biology (SMB), is funding a series of prizes based on papers published in the BMB. This year’s prize for the best original research paper has been awarded to Tomas de-Camino-Beck and Mark Lewis for their paper A new method for calculating net reproductive rate from graph reduction with applications to the control of invasive species1. The prize for the best student research paper went to Emma Jin and Christian Reidys for their paper Asymptotic enumeration of RNA structures with pseudoknots2. The awards were presented at the annual conference of the SMB, which took place in Toronto, Canada, from 30 July to 2 August 2008. The winner of the prize for the best review paper will be announced at the 2009 SMB conference.

Книги издательства Springer Science & Business Media

This paper presents an overview of the integration of renewable energy resources in the urban sector. The article also describes the current global energy demand and growth challenges that the world is currently facing. The literature survey on the global energy scenario and renewable energy integration, which mainly involves solar photovoltaic (PV) and battery energy storage systems (BESS), is presented. The paper also addresses the different contexts of using renewable energy resources (RERs) and grid-connected applications. It develops the concept of PV energy storage integration in commercial building applications. Since the common RERs such as wind and solar vary according to seasonal and geographic locations, an outline of the energy storage system that provides a platform for optimal use of RERs is also presented. This structure refers to their ability and dynamic structure that can combine with the renewable power generation to maximise the use of RERs and to ensure the total energy supply to the load. It was observed that the integration of distributed energy resources (DERs) which are connected to the grid is beneficial when the PV and energy storage system (ESS) are smartly mixed with the utility grid. The primary purpose of this energy mix is to assist in improving the dynamic performance of any electrical network operating in a commercial building setup. Thus, this research work analyses the possibility of designing dynamic behaviour for energy management for commercial building applications in South Africa.

An overview of renewable energy resources and grid integration for commercial building applications

An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices

This study explores optimisation of the hybrid power system in the smart grid framework, in conjunction with the model predictive control (MPC) design. This study also creates a strategy that can maximise the use of renewable energy, e.g. photovoltaic, the wind turbine with battery storage and minimise the utilisation of the utility grid for electricity usage in the industry. This is devised by modelling a discrete state-space model of the hybrid power system for a given industry application. The system design is implemented within a real-time electricity pricing environment that is integrated with renewable energy to optimally meet the demand according to a specific performance of the consumer. The emphasis of this approach is on its capacity to supply optimal power to the demand side by selecting the appropriate source; and its robustness against uncertainties. The results show that MPC design for hybrid power system not only optimises the energy flow but also improves the overall process of energy management. It was also observed that the optimal solution minimises the delay cost of energy demand from the utility grid according to a given reference from the consumer for the specified tuning parameter values of the performance index.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2017.0381

Optimisation of grid connected hybrid photovoltaic–wind–battery system using model predictive control design

A dynamic energy management system using smart metering

This paper presents a single input / single output model predictive control (SISO-MPC) in the framework of a smart grid to include energy management and real-time electricity pricing. This research also addresses the challenges associated with the increasing utility costs within commercial buildings. The modeling of this paper is based on electrical energy demand, in conjunction with real-time electricity pricing, when the fixed tariff is prepaid. This model is established with a smart meter and it can be managed by controlling the load system during the operating time to ensure the optimal cost of electricity. It has been found that SISO-MPC in real-time pricing is robust, and allows the control of electricity usage within commercial buildings while saving energy and managing the electrical system. The performance index of this design can handle all system constraints and a gain from 50 to 60 percent or more of the total cost of electricity. As there is also an increase in demand for electricity, this is of significant value to both the consumer and the utility company.

Minnesh Bipath

Papers

An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices

Optimisation of grid connected hybrid photovoltaic–wind–battery system using model predictive control design

A dynamic energy management system using smart metering

Smart SISO-MPC based energy management system for commercial buildings: Technology trends

Optimal single phase smart meter design