Geographic routing protocol for the deployment of virtual power plant within the smart grid
Introduction
The electric grids are undergoing radical changes to transform into SG promoting sustainable energy resources and reducing carbon emissions resulting from energy generation and consumption. Conventional electricity grid has been developed based on the assumption that electricity is generated at few stations generally outside urban areas and transported and distributed to large, medium and small sized consumers. The grid is evolving to a power network with distributed energy resources and storage (DERSs) combined with large central power plants. Electricity can be generated, consumed and stored anywhere in the grid. Renewable energy sources offer pollution free, climate friendly, sustainable and unlimited sources of energy. Their integration into the power grid is driven largely by environmental and economic regulation aimed at transforming into a clean and sustainable energy grid.
Smart governments promote deployment of “in-grid” technologies that are susceptible to improve operational efficiency and labor use and reduce capital investment through management of peak demand. Indeed, SG technologies allow for better prediction of electricity supply and demand anywhere in the grid and provide efficient grid conditions monitoring and control. Moreover, it will give energy prosumers provisions to actively interact in managing demand and/or production on their side and to contribute to the resilience and efficiency of the electricity system through responsible interaction with the grid state. In fact, instead of continuously rushing to satisfy customer demand, SG integrates demand-side management (DSM) programs that aim at adapting demand to available production. These strategies try to fulfill load profile constraints either through providing financial incentives to consumers to encourage them to shift their energy demand to periods with extra available power, or through direct control of energy intensive devices like air conditioners and water heaters (Davito, Tai, & Uhlaner, 2010). The effectiveness of these strategies is somewhat relativistic. It has been found that these strategies can certainly shift part of the load demand, but, conversely, could lead to new demand peaks as soon as the DSM signal is off and introduce artificial periodicity in the load profile (Strbac, 2008).
The integration of DERSs and DSM programs is a key, yet challenging, feature for SG implementation. An information communication networks is deployed in parallel to the power network to coordinate bidirectional power flows and support related services and actions in order to accommodate high integration of sustainable energy systems and enable development of innovative smart sustainable energy programs.
As mentioned earlier, the integration of DERSs into the grid, in particular renewable energy sources or natural storage, act for a sustainable energy system with less environmental concerns, more diversified energy resources and enhanced energy efficiency. However, distributed energy resources and storage (DERS) units working isolated from each other because of their different ownerships. They help satisfying local needs for a house, a building or a business but their integration within a grid could rapidly become a headache for utilities and distribution system operator (DSOs) for their influence on grid's stability, voltage levels, power factor, etc. The existing approaches for DERS integration are divided in two main classes based on prosumer participation and management strategies (Rathnayaka, Potdar, & Kuruppu, 2011): individual integration, and group integration.
Individual integration strategy consists of connecting the prosumers directly to the grid. This facilitates direct prosumer-utility interactions. However, due to their small size, DERs are invisible to the grid as well as to the electricity market. Moreover, the number of DERs is expected to rise quickly, and with the variable amount of generated energy, the uncertainty need to be addressed in real time through active grid management. This integration strategy is clearly unsustainable.
Group integration strategy consists of grouping a number of prosumers, with different energy resources and storage who are having diverse behaviors in consuming/producing energy, in a single entity and identifying them as virtual power plant (VPP) to the utilities or distribution system operator (DSO). A VPP knits together DERs including power generators, controllable loads and storage as a single generator. Any residential energy user or producer can be hooked up to the VPP. Energy that is generated but not used can also contribute to the VPP's capacity. The group of prosumers can attain the critical amount of energy, load and storage requested by utility companies to take part in energy auctions or be considered for ancillary services. Thus, the group integration seems more feasible, scalable and sustainable strategy.
In this work, we investigated an information and technology protocol to support VPP deployment. We analyzed data communication requirements for VPPs in terms of latency, delivery rate and communication types. Also, we provided data routing protocol that satisfies VPP requirements. The proposed protocol is scalable and capable of following VPP deployment at the different stages. It can handle different communication types among participants of the VPP such as multipoint-to-point, point-to-multipoint, and point-to-point. The proposed protocol can also accommodate VPP dynamic structure with seamless enrollment and dis-enrollment of prosumers. The protocol is capable of finding optimal communication paths with small number of control packets. The newly proposed routing protocol uses geographic routing (GR) combined with ACO concept in order to solve the communication void problem in GR. The main reason behind using ACO is to explore reliable paths around void areas. In fact wireless sensor networks suffer from such a problem in urban environment that have very dynamic structure due to radio frequency propagation and inherent fading. Therefore, an available node at a specific time is likely to become unavailable for relaying packets some milliseconds after. Hence, it's not useful to spend resources on optimization to find optimal paths each time we reach a void area. Indeed, a node within new path could itself become unavailable because of RF propagation. The performance of the overall protocol is shown to be within the requirements of SG communication.
In the next section, we introduce the concept of VPP and its control types. This will allow us to highlight communication needs for the VPP. Then we report routing protocol for low power and lossy networks (RPL). This protocol has been standardized by the internet engineering task force (IETF) and is intended for wide variety of applications including home automation, urban sensor networks and advanced metering infrastructure (AMI) systems (Popa, Jetcheva, Dejean, Salazar, & Hui, 2011). We overview the RPL protocol with the objective of pointing limitations that can hinder its application in the VPP. Finally, numerical simulations are conducted and presented for the proposed protocol for different node densities of VPP.
Section snippets
Virtual power plant (VPP)
A VPP is a set of geographically sparse DERs including power generators, controllable loads and storages that are aggregated in a way to perform as a single power facility, as illustrated in Fig. 1. A set of units among the available DERs (home energy management system (HEMSs), energy storage system (ESSs), distributed generation (DG), electric vehicle (EVs)), surrounded with red circles, decided to participate into the VPP. The VPP management system consists of a technical VPP (TVPP) and a
ISO/OSI model
Communication networks products and applications are usually referenced to the ISO/OSI model. This model represents a layer model which defines the process of communication between two endpoints in a network. As presented in Fig. 5, the OSI model is a networking framework composed of seven layers: application layer, presentation layer, session layer, transport layer, network layer, data-link layer and physical layer. Each of these layers relies on the layers below it to provide supporting
Geographic routing
Geographic routing is a class of routing approaches that exploit geographic position in routing decision in stead of topological information. It has been widely used in ad-hoc and wireless sensor networks for its diverse advantages. In fact, GR is a localized routing scheme since packet forwarding decision is achieved by using only information about the position of nodes in the vicinity and the position of the destination node, which minimizes significantly communication overhead. Hence, no
Performance analysis
The effectiveness of the proposed routing protocol, reported in Section 4 is evaluated through simulation.
Conclusion
In this paper, we applied ant colony optimization method in conjunction with geographic greedy forwarding mechanism as a routing protocol to support scalable and rapid deployed VPP. The communication requirements of the VPP are discussed in relation with the possible control strategies and deployment phases. VPP control strategies could be either centralized, hierarchical or fully distributed. In order to achieve these requirements, our proposed ICT supports multipoint-to-point,
Acknowledgments
This work has been partially supported by a grant for the CPER CIA and the MESRST TIC.
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