Energy Infrastructure of the Factory as a Virtual Power Plant: Smart Energy Management

Abstract

Smart energy factories are crucial for the development of upcoming energy markets in which emissions, energy use and network congestions are to be decreased. The virtual power plant (VPP) can be implemented in an industrial site with the aim of minimizing costs, emissions and total energy usage. A VPP considers the future situation forecasting and the situation of all energy assets, including renewable energy generation units and energy storage systems, to optimize the total cost of the plant, considering the possibility to trade with the energy market. For a VPP to be constructed, a proper communication system is essential. The energy management system (EMS) enables the monitoring, management and control of the different energy devices and permits the transference of the decisions made by the VPP to the different energy assets. VPP concept is explained together with the methods used for forecasting the future situation and the energy flow inside the facility. To reach its benefits, the optimization of the VPP is assessed. After that, the communication technologies that enable the VPP implementation are also introduced, and the advantages/disadvantages regarding their deployment are stated. With the tools introduced, the VPP can face the challenges of energy markets efficiently.

Modelling and analysis of virtual power plants interactive operational characteristics in distribution systems

“…10, shows that when the energy demand is higher than the energy produced, i.e. [11][12][13][14][15][16][17][18][19][20][21][22] peak hours, the storage unit supplies the energy stored to satisfy the DSO demand. Figure 11, reveals that the total energy in the storage unit decreases because of the discharge during that period.…”

“…At present, relatively little progress has thus far been made in terms of local market design mechanisms at the distribution level. As a result, it is therefore not yet well understood that the current market-oriented mechanisms could support energy trading while improving network operation at the distribution level [15][16][17]. Therefore, it is necessary to design a platform for managing energy exchange among various market participants involved in energy delivery.…”

“…Figure 10, shows that when the energy demand is higher than the energy produced, i.e [11][12][13][14][15][16][17][18][19][20][21][22]. peak hours, the storage unit supplies the energy stored to satisfy the DSO demand.…”

Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants

“…The development of computationally efficient data-driven prediction and decision-making methods for VPPs has seen increasing interest during the last years. Such methods, commonly referred to in the literature as soft-computing or ''artificial intelligence'' (AI)-based methods [291], are being increasingly incorporated into feedback control loops in energy systems [292], [293]. For example, machine learning (ML), the leading exponent of data-driven techniques in practical applications, has been incorporated into VPPs for the purpose of forecasting [28] and optimization [29].…”