Optimised allocation of PV and storage capacity among different consumer types and urban settings: A prospective analysis for Switzerland. (20th June 2020)

• Record Type: Journal Article
• Authors: Rinaldi, Arthur; Soini, Martin Christoph; Patel, Martin K.; Parra, David
• Is Part Of: Journal of cleaner production. Volume 259(2020)
• Publication Date: 2020-06-20
• Subjects: Storage -- PV -- Dispatch model -- Sub-national nodes -- Consumer types -- Distribution capacity constraints; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2020.120762
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: This paper discusses the optimal configuration of PV and electricity storage in a detailed representation of the Swiss power system. The sensitivity of storage deployment with respect to distribution network capacity is also investigated. We propose an open-source dispatch model to optimise the electricity supply of Switzerland and its four neighbouring countries with hourly time resolution. Moreover, our representation of the Swiss power system includes various types of consumers, namely, the residential (single-family house and multi-family house), service and industrial sectors, with a differentiation by rural, suburban and urban settings, resulting in 12 sub-national nodes. We then use monitored electricity demand load data for each sector. We find that the achievement of the Swiss federal target of 13.8 GWp PV capacity by 2050, which corresponds to 30% of the annual production, requires an additional storage capacity of 11 GWh (corresponding to 1.6 h of average consumption) in order to minimise total costs. However, when letting the optimisation model choose both the PV capacity and the size of energy storage, then minimal costs are achieved by a system with 24.6 GWp of PV (corresponding to 53% of the annual production) combined with 29.2 GWh (4.1 h of average consumption) of storage capacity. Our results show that storage plays an important role in minimising the total cost for energy systems with large PV capacity as well as satisfying the distribution capacity constraints. The detailed results and mechanisms at the level of sub-national nodes are discussed. The model and the methodology presented in this study with a focus the Swiss case can be applied to any country/region. Highlights: We present a dispatch model with sub-national nodes combining consumer types and urban settings. We discuss the trade-offs between storage deployment and distribution capacity upgrade. 24.6 GWp of PV combined with 14.6 GW (29.2 GWh) of storage is the cost optimal solution for Switzerland by 2050. Storage plays an important role in minimising the total cost and in satisfying the distribution capacity constraints.