Effects of the load forecasts mismatch on the optimized schedule of a real small-size smart prosumer. (September 2017)

• Record Type: Journal Article
• Authors: Danti, Piero; Magnani, Sandro
• Is Part Of: Energy procedia. Volume 126(2017)
• Page Start: 406
• Page End: 413
• Publication Date: 2017-09
• Subjects: CHP -- EHP -- Optimization Algorithm -- Load forecast mismatch; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.08.283
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: The increasing need for reducing the costs and the environmental impact of the energy supply renewed the interest on distributed generation, also favoured by the recent EU directives. Anyway, the solely installation of efficient small- and medium-size pieces of equipment is not sufficient to achieve the expected targets, being their proper scheduling and management, of course based on the fluctuations of both the loads pattern and the energy prices, the fundamental issue determining their effectiveness. In recent times, several techniques have been proposed with the purpose of optimizing the operation of the installed generators on the basis of load predictions; even if these latter ones heavily affect the performance of the plant management, especially when considering a single prosumer whose behaviour is scarcely predictable with a good accuracy, often this aspect is neglected. The present study aims to analyse how inaccurate load predictions affect the performance of an energy plant whose generators are scheduled by an optimization tool working considering a time span of one day. Different "structures" of error will be modelled and analysed, taking as benchmark load profiles the acquired data for different periods of the year from an office building plant, equipped with a PV plant, two micro-CHP system combined with an absorption chiller, an electric chiller, a gas boiler and a reversible electric heat pump, with thermal storages. The focus will be on the comparison of both the economic and CO2 emission impact, by considering on one side the loads prediction as perfect and on the other side with different entity of errors, with the target to stress the importance of the correct loads prediction issue.