Elsevier

Renewable Energy

Volume 87, Part 1, March 2016, Pages 686-696
Renewable Energy

Increasing climate-related-energy penetration by integrating run-of-the river hydropower to wind/solar mix

https://doi.org/10.1016/j.renene.2015.10.064Get rights and content

Highlights

  • Integration of run-of-the river (RoR) power in solar/wind power mix is analyzed.

  • Integrating RoR power in solar/wind power mix increases the global penetration rate.

  • Integrating RoR modifies the optimal share between solar- and wind-power.

  • In Europe, optimal RoR/solar/wind energy mix is region dependent.

Abstract

The penetration rate of Climate Related Energy sources like solar-power, wind-power and hydro-power source is potentially low as a result of the large space and time variability of their driving climatic variables. Increased penetration rates can be achieved with mixes of sources. Optimal mixes, i.e. obtained with the optimal share for each source, are being identified for a number of regions worldwide. However, they often consider wind and solar power only.

Based on 33 years of daily data (1980–2012) for a set of 12 European regions, we re-estimate the optimal mix when wild run-of-the-river energy is included in the solar/wind mix. It is found to be highly region dependent but the highest shares are often obtained for run-of-the-river, ranging from 35% to 65% in Belarus and England. High solar shares (>40%) are found in southern countries but solar shares drop to less than 15% in northern countries. Wind shares range from 10 to 35% with the exception of Norway where it reaches 50%. These results put in perspective the optimal 60%–40% wind/solar mix currently used for Europe. For all regions, including run-of-the-river in the mix allows increasing the penetration rate of CREs (from 1 to 8% points).

Introduction

Installed capacity of Climate Related Energy (CRE), i.e. solar-power, wind-power and hydro-power, is growing quickly across Europe. A new goal of 27% of renewable share by 2030 has been defined by the EU [5]. For some European countries such as Austria, Spain, Norway or Sweden, this objective is already achieved [21]. On the other hand, the European Climate Foundation states that 100% renewable is an objective to be achieved by 2050 [4]. This scenario is physically realistic even at the global scale since the technical potential of renewable energies covers several times the energy demand [13]. However, it is well-known that this available potential is not equally distributed over space [2]. In Europe, solar power potential is much higher in Southern countries than in the Northern ones. For wind power, it is the opposite with higher potential in the north and along the shores [15]. show that the space distribution of hydropower potential relates with the mountain ranges in Europe: higher is the altitude, the higher the hydropower potential. Ref. [11] illustrated that Europe could take advantage of combining different CREs allowing a limited use of conventional power.

Even though it is not yet clear what will look like such a 100% renewable energy mix, solar and wind energy sources are expected to be important contributors. The main reason is that, contrary to biomass, their weather driving variables (i.e. wind, solar irradiance and temperature) are exploitable everywhere in Europe [20].

For a 100% scenario at the European scale [2]; shows that the mix composed by 60% of wind and 40% of Photo-Voltaic (PV) minimizes the monthly energy balance variance which governs the balancing costs related to energy transport and storage. The hourly energy balance variance is however minimized with a lower share of solar due to its diurnal cycle [11]. show that even if a certain rate of fossil-nuclear still remains in activity (for instance covering lower than 50% of the energy demand on average), the optimal share between wind and solar would not differ significantly [12]. find that oversizing solar and wind power capacities modifies the optimal mix minimizing the storage requirement. Following these studies, Ref. [23] show that the highest penetration rate is obtained in Germany for a wind power share ranging from 60 to 80%.

In some ways, hydropower is never explicitly included in the mix computation but considered as a storage facility. Indeed, large hydropower storage is used for balancing production and load mismatches. In this sense, the term of ‘blue battery’ is used when referring to the huge energy storage capacity provided by Scandinavian or Alpine reservoirs [17]. Less attention is paid to small run-of-the-river power (hereafter denoted as RoR power), even if the amount of energy produced is important in several places. In Italy for instance, small run-of-the-river hydropower plants (i.e. with a power capacity lower than 3 MW) provide 22% of the annual hydropower energy which reached 45,823 GWh in 2011, i.e. about 24% of the electricity consumption [25]. In Switzerland, 26% of the generated power is generated by run-of-the river power plants [1]. Even though RoR potential is already significant in Europe, new RoR power plants are under-construction or planned. For instance, an increase of about 33% of small RoR power capacity is under-study in Scotland [18].

In Northern Italy, the challenge of integrating run-of-the river power into the combination with solar energy source starts to be investigated [6]. Different degrees of complementarity are obtained, depending on the hydrological regime of the considered catchments (snow- or rainfall-dominated regimes) and on the time scales (e.g. hourly, monthly).

This study investigates how the use of RoR hydropower coming from uncontrolled river flows may increase the global penetration of climate related energies under the hypothesis that only solar, wind and RoR power are used to meet the demand. We use a benchmark set of 12 regions spread across Europe and covering a wide variety of climates. Neither storage nor transport among regions is considered in this study.

The paper is organized as follows: The description of the study areas and the databases are given in Section 2. The analysis framework is detailed in Section 3. Results are presented in Section 4. Section 5 concludes and gives some outlooks for future research directions.

Section snippets

Study areas and dataset used

Fig. 1 locates the different areas selected for this study. In the following, although the areas do not match country border, they will be referred for convenience with country or region names. As the surface area of each domain is roughly 40,000 km2 (Table 1), we assume that they are large enough for being representative of the in-situ climate, both in terms of weather variable average and time variability. These domains are chosen for two main reasons. First, they represent a variety of

Study framework

This section describes the computation of the different elements needed in our analysis: i) the power time series obtained from PV solar, wind and RoR, ii) the energy load time series and iii) the penetration rate for a given energy mix. Power generation from solar, wind and RoR are computed for each grid cell i and are then summed for each region. For the sake of simplicity, we assume that all grids have the same power capacity, i.e. the same level of equipment for each energy source. We

Seasonal opposition between wind and solar power

Solar power presents in all regions a similar seasonal pattern with a high production period during the summer (Fig. 4). The patterns have larger amplitude in Northern areas like Norway and Finland due to the important daylight time changes along the years. The consequence for these regions is twofold: i) an almost nil solar generation during winter while it remains significant over this period in Southern regions such as Andalucía, Greece and Tunisia; ii) on the opposite, longer daylight times

Conclusion

At the European scale, several past studies looked at the potential advantages of combining solar and wind power. Other renewable energies such as biomass and hydropower were considered, either directly or not, as storage facilities able to balance the mismatches between load, wind and solar power generation. The literature shows that the optimal share between wind and solar power varies according to the time scale. For Europe and at daily time scale, it is usually considered as a mix composed

Acknowledgments

This work is part of the FP7 project COMPLEX (Knowledge based climate mitigation systems for a low carbon economy; Project FP7-ENV-2012 number: 308601; http://www.complex.ac.uk/). This paper also benefited from comments and suggestions from two anonymous reviewers.

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