Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus

Vladimir Z Gjorgievski,George E Georghiou,Georgios C Christoforidis,Venizelos Venizelou,Nikolas G Chatzigeorgiou,Grigoris K Papagiannis

doi:10.3390/en13081934

Abstract

Three load matching indicators (self-consumption rate, self-sufficiency rate, loss of load probability) and the CO2 emissions were evaluated for 55 Cypriot households with 3 kWp rooftop photovoltaic (PV) generators. The calculations were performed using 30-minute generation and consumption data from a large scale smart meter project in Cyprus. To investigate the effects of recent advances in local legislation, an analysis for higher PV capacities (5 kWp and 10 kWp) was also performed. The PV generation profiles for 5 kWp and 10 kWp PVs were obtained by scaling the 3 kWp PV generation profiles. The results showed that the self-consumption of the analyzed households varied seasonally, as it was related to their heating and cooling demand. More interestingly, the ratio between the households’ annual electricity generation and demand, formally defined here as generation-to-demand ratio (GTDR), was found to be related to the value ranges of the studied load matching indicators. Hence, on average, households with 3 kWp PV generators annually self-consumed 48.17% and exported 2,415.10 kWh of their PV generation. On the other hand, households with larger PV generators were characterized by a higher GTDR, but lower load matching capabilities. For the cases of 5 kWp and 10 kWp PV generators, the average self-consumption fell to 34.05% and 19.31%, while the exported PV generation was equal to 5,122.47 kWh, and 12,534.90 kWh, respectively. Along with lower load matching capabilities, households that generated more than they consumed were also found to have a lower potential for CO2 emissions reduction per installed kWp within the boundaries of the building. In this context, the GTDR could be used by stakeholders to characterize buildings, infer possible value ranges of more complex indicators and make evidence based decisions on policy and legislation.

Highlights

The need to reduce the energy and carbon intensity of buildings has transcended geographical boundaries
The statistical analysis of the energy consumption and PV generation of 55 Cypriot households led to the following conclusions: (1) best load-matching was achieved during the summer and winter months
This result was specific to Cyprus, it numerically demonstrates that load-matching is driven by a combination of consumption habits, climate conditions and local policy; (2) the analyzed load matching indicators (SCR, self-sufficiency rate (SSR) and loss of load probability (LOLP)) are related to the generation-to-demand ratio (GTDR); (3) oversized PVs only marginally reduce the on-site CO2 emissions within the building boundaries

Summary

Introduction

The need to reduce the energy and carbon intensity of buildings has transcended geographical boundaries. Global building-related CO2 emissions have been rising for two years in a row to a record high 9.6 GtCO2 , which is equivalent to 28% of the global emissions in 2018 [1] This trend has been the result of the continuously growing energy demand, the decrease in energy intensity. In order to meet the 2-degree and 1.5-degree targets, in particular, the global emissions from the building sector should drop by 32 GtCO2 , and 50 GtCO2 , respectively [3] This will likely be achieved through a combination of actions, such as the electrification of buildings [4], the integration of renewable energy sources (RES) [5] and deep retrofit measures [6]. Policy makers need to be guided by simple, but robust, indicators, in order to make evidence-based decisions

Methods

Results

Discussion

Conclusion