Application and Management of Smart Energy for Smart Cities

Dear Colleagues,

In recent years, the exponential growth of the world population has reached approximately eight billion people, with an ever-greater concentration in cities, where today approximately 4.4 billion people live. Forecasts for 2050 state that seventy percent of the world’s population will live in cities. Therefore, starting now and increasingly for the future, this means that cities will be large centers of energy consumption.

At the same time, the necessity to reduce the use of fossil fuels in the energy system can no longer be postponed and, consequently, it is increasingly necessary to increase the contribution of renewable energy sources (RESs) to meet the energy needs of cities.

With these premises, it is important to consider that in large urban centers it is difficult to produce energy from RESs. On the contrary, the production from RESs becomes easier in the suburbs, considering the useful land for the potential development of photovoltaic or wind power plants or, in small urban centers near cities, considering the roofs of terraced houses or single-family homes, where it is generally easy to size generation systems in order to have surplus production from RESs to contribute to cities’ supply.

As consequence, it would be appropriate to be able to optimally store and/or use the energy produced from RES in the suburbs in large urban centers.

At the same time, the dependence of urban centers on an increasing proportion of energy supplied by RESs, which are characterized by uncertain power production, underlines the necessity of stable operation: the improvement of the adequacy, security and resilience of the electric power system becomes necessary to make our cities increasingly smart in terms of the generation, transportation and distribution of electric energy.

In this context, solutions that make it possible to create aggregations among users of large cities and prosumers or producers of peripheral areas become very interesting, with the aim of achieving excellent instant self-consumption results in the aggregation (e.g., for renewable energy communities). This allows for a strong penetration of RESs while minimizing their impact on the grid, adopting technological solutions that make it possible to store and instantly consume the energy produced elsewhere. These solutions can be improved by adopting demand response and by demand-side management strategies as well as new electricity market solutions.

The development of the electricity transport sector in smart cities also represents a point to be evaluated, both in order to integrate it in the best possible way into the electricity grid while reducing the impact as much as possible, but also to take advantage of them using solutions such as vehicle-to-grid (V2G) to support the grid itself.

All this involves many fields, such as control systems, power electronic technologies, communications, high-performance computing, IoT, big data, machine learning, energy markets, smart grids, microgrid and renewable energy communities.

Therefore, the main concern of this Special Issue is the identification of new smart solutions based on advanced green energy technologies for a sustainable and resilient future grid which enable large urban centers to use energy produced from RESs in suburbs or in small urban centers near cities.

This Special Issue invites original contributions on topics including but not limited to the following:

• Renewable energy communities;
• Smart grid modeling for smart cities;
• Smart grid for integration of RES distributed generation into the renewable energy communities framework;
• Distributed energy storage management systems;
• Operation and control of RESs in the presence of distributed energy storage;
• Demand response and demand-side management;
• Forecasting techniques for renewable energy sources and loads;
• V2G applications in smart cities;
• Electricity market modeling and simulation for the integration of renewable sources;
• Artificial intelligence, machine learning, IoT and big data applications for energy systems in the presence of RES dispersed generation.

Prof. Dr. Daniele Menniti
Dr. Giovanni Brusco
Dr. Pasquale Vizza
Dr. Anna Pinnarelli
Dr. Nicola Sorrentino
Guest Editors

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• smart cities
• renewable energy
• renewable energy communities
• smart grid and microgrid
• distributed energy storage
• distributed generation
• demand side management
• demand response
• power generation forecasting of RES
• V2G