Building management systems (BMSs) are being implemented broadly by industries in recent decades. However, BMSs focus on specific domains, and when installed on the same building, they lack interoperability to work on a centralized user interface. On the other hand, BMSs interoperability allows the implementation of complex rules based on multi-domain contexts. The Building’s Reasoning for Intelligent Control Knowledge-based System (BRICKS) is a context-aware semantic rule-based system for the intelligent management of buildings’ energy and security. It uses ontologies and semantic web technologies to interact with different domains, taking advantage of cross-domain knowledge to apply context-based rules. This work upgrades the previously presented version of BRICKS by including services for energy consumption and generation forecast, demand response, a configuration user interface (UI), and a dynamic building monitoring and management UI. The case study demonstrates BRICKS deployed at different aggregation levels in the authors’ laboratory building, managing a demand response event and interacting autonomously with other BRICKS instances. The results validate the correct functioning of the proposed tool, which contributes to the flexibility, efficiency, and security of building energy systems.
Globally, the amount of renewable energy generation is increasing, which raises the complexity of operating electrical grids to maintain stability and balance and boosts the need for developing new electricity market (EM) models fitting this new reality. To test, study, and validate the possible effects of novel EM designs, simulation techniques are frequently employed. This work proposes the use of two open-access tools for the modeling and simulation of complex EMs. These are the Electricity Markets Service (EMS) and the Spine Toolbox. EMS enables the simulation of two commonly used auction-based algorithms and the execution of three European wholesale EMs. Being published as a web service facilitates its integration with other services, systems, or software agents, such as the Spine Toolbox. The Spine Toolbox, in turn, is an open-source software for complex energy systems modeling. Combining them allows the modeling and simulation of complex EMs from the wholesale to local markets, as well as testing and validating new market designs. This work’s case study demonstrates how to use these tools to simulate the operation of the Iberian EM – MIBEL – for a month, using public data available from the market operator’s website. The results are analyzed from the perspective of the market operator and two players, i.e., a selected buyer and seller, for a specific day and the whole month.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.