It is expected, and regionally observed, that energy demand will soon be covered by a widespread deployment of renewable energy sources. However, the weather and climate driven energy sources are characterized by a significant spatial and temporal variability. One of the commonly mentioned solutions to overcome the mismatch between demand and supply provided by renewable generation is a hybridization of two or more energy sources in a single power station (like wind-solar, solar-hydro or solar-wind-hydro). The operation of hybrid energy sources is based on the complementary nature of renewable sources. Considering the growing importance of such systems and increasing number of research activities in this area this paper presents a comprehensive review of studies which investigated, analyzed, quantified and utilized the effect of temporal, spatial and spatiotemporal complementarity between renewable energy sources. The review starts with a brief overview of available research papers, formulates detailed definition of major concepts, summarizes current research directions and ends with prospective future research activities. The review provides a chronological and spatial information with regard to the studies on the complementarity concept.

Small scale hybrid power systems gain popularity around the world as a viable way of reducing power generation environmental impact, reducing energy cost and increasing power supply reliability. Hybrid systems which are based on variable renewable sources usually utilize the effect of resources temporal, and to a smaller extent, spatial complementarity. Although there is already an extensive body of literature investigating the concept of resources complementarity, they rarely addressed the impact of complementarity on the reliability of a given hybrid system. In this paper we simulate the operation of wind and solar hybrid energy system (with and without battery) for evenly distributed 86 locations in Poland over the period 2010-2016 based on 15 min' time step data. We analyze the impact of resources complementarity (on various time scales: 15 min, hourly and monthly) on the system reliability. To remove the capacity factor (resources availability depends on location) on the results, we select the installed capacity in wind and solar sources in such a way that on an annual scale they generate evenly 50% of the observed demand (which is assumed to be constant = 1 kW). We investigate the impact on complementarity in the system reliability for hybrids with and without energy storage. The second part of the paper deals with the problem of simulating the system reliability (in terms of Loss of Load Parameter) based on multiple linear regression and artificial neural networks. The results indicate that both temporal complementarity (expressed as coefficient of correlation) and storage capacity has non-linear impact on the hybrid system capacity to cover the load. Generated relations between mentioned factors show how complementarity indices may be used to size the solar-wind hybrids. The follow up studies should concentrate on analyzing the operation of hybrids utilizing more than two energy sources and juxtaposing complementarity based reliability assessment with other methods.

Renewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. However, the weather-dependent nature of renewable energy sources often hinders their integration to national grids. Combining different sources to profit from beneficial complementarity has often been proposed as a partial solution to overcome these issues. This paper introduces a novel method for quantifying total temporal energetic complementarity between three different variable renewable sources, based on well-known mathematical techniques: correlation coefficients and compromise programming. It has the major advantage of allowing the simultaneous assessment of partial and total complementarity. The method is employed to study the complementarity of wind, solar and hydro resources on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the total temporal complementarity.

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This study investigates and compares the various combinations of renewable energies (solar, wind) and storage technologies (battery, pumped hydro storage, hybrid storage) for an off-grid power supply system. Four configurations (i.e., single RE source system, double RE source system, single storage, and double storage system) based on two scenarios (self-discharge equal to 0% and 1%) are considered, and their operational performance is compared and analyzed. The energy management strategy created for the hybrid pumped battery storage (HPBS) considers that batteries cover low energy surplus/shortages while pumped hydro storage (PHS) is the primary energy storage device for serving high-energy generations/deficits. The developed mathematical model is optimized using Particle Swarm Optimization and the performance and results of the optimizer are discussed in particular detail. The results evidence that self-discharge has a significant impact on the cost of energy (13%-50%) for all configurations due to the substantial increase in renewable energy (RE) generators size compared to the energy storage capacity. Even though solar-wind-PHS is the cost-optimal arrangement, it exhibits lower reliability when compared to solar-wind-HPBS. The study reveals the significance of HPBS in the off-grid RE environment, allowing more flexible energy management, enabling to guarantee a 100% power supply with minimum cost and reducing energy curtailment. Additionally, this study presents and discuss the results of a sensitivity analysis conducted by varying load demand and energy balance of all considered configurations is performed, which reveals the effectiveness of the supplementary functionality of both storages in hybrid mode. Overall, the role of energy storage in hybrid mode improved, and the total energy covered by hybrid storage increased (48%), which reduced the direct dependency on variable RE generation.