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Private households constitute a considerable share of Europe's electricity consumption. The current electricity distribution system treats them as effectively passive individual units. In the future, however, users of the electricity grid will be involved more actively in the grid operation and can become part of intelligent networked collaborations. They can then contribute the demand and supply flexibility that they dispose of and, as a result, help to better integrate renewable energy in-feed into the distribution grids.
Digital networked communications are the key to all Internet-of-Things applications, especially to smart metering systems and the smart grid. In order to ensure a safe operation of systems and the privacy of users, the transport layer security (TLS) protocol, a mature and well standardized solution for secure communications, may be used. We implemented the TLS protocol in its latest version in a way suitable for embedded and resource-constrained systems. This paper outlines the challenges and opportunities of deploying TLS in smart metering and smart grid applications and presents performance results of our TLS implementation. Our analysis shows that given an appropriate implementation and configuration, deploying TLS in constrained smart metering systems is possible with acceptable overhead.
Energy management in distribution grids is one of the key challenges that needs to be overcome to increase the share of fluctuating renewable energies. Current control systems for energy management mainly demonstrate centralized- or decentralized-hierarchical control structures. Very few systems manifest a fully decentralized multiagent-based control structure. Multiagent-based control systems promise to be an advantageous approach for the future distributed energy supply system because no central control entity is necessary, which eases parameterization in case of grid topology changes, and the agents are more stable against failures and changes of control topologies. Research is necessary to prove these benefits. In this study, we introduce a design of a multiagent-based voltage control system for low-voltage grids. In detail we introduce cooperative decision-making processes and software solutions that allow the agents to perceive and control their environment, the agent-discovery and localization in different types of communication networks, agent-to-agent communication, and the integration of the multiagent system in existing grid-control infrastructures. Furthermore, the study proposes how different existing technologies can be combined into an applicable multiagent-based voltage control system: the Java/OSGi-based OpenMUC framework allows a generic field–device interaction; peer-to-peer discovery and session establishment functionalities are combined with the agent communication defined by the Foundation for Intelligent Physical Agents (FIPA). The ripple control-signal technology is applied as a fallback communication between the agent and a central grid-control center.
Optimal microgrid scheduling with peak load reduction involving an electrolyzer and flexible loads
(2016)
This work consists of a multi-objective mixed-integer linear programming model for defining optimized schedules of components in a grid-connected microgrid. The microgrid includes a hydrogen energy system consisting of an alkaline electrolyzer, hydrogen cylinder bundles and a fuel cell for energy storage. Local generation is provided from photovoltaic panels, and the load is given by a fixed load profile combined with a flexible electrical load, which is a battery electric vehicle. The electrolyzer has ramp-up constraints which are modeled explicitly. The objective function includes, besides operational costs and an environmental indicator, a representation of peak power costs, thus leading to an overall peak load reduction under optimized operation. The model is used both for controlling a microgrid in a field trial set-up deployed in South-West Germany and for simulating the microgrid operation for defined period, thus allowing for economic system evaluation. Results from defined sample runs show that the energy storage is primarily used for trimming the peak of electricity drawn from the public grid and is not solely operated with excess power. The flexible demand operation also helps keeping the peak at its possible minimum.