Declining cost of renewables and climate change curb the need for African hydropower expansion.

Across continental Africa, more than 300 new hydropower projects are under consideration to meet the future energy demand that is expected based on the growing population and increasing energy access. Yet large uncertainties associated with hydroclimatic and socioeconomic changes challenge hydropower planning. In this work, we show that only 40 to 68% of the candidate hydropower capacity in Africa is economically attractive. By analyzing the African energy systems' development from 2020 to 2050 for different scenarios of energy demand, land-use change, and climate impacts on water availability, we find that wind and solar outcompete hydropower by 2030. An additional 1.8 to 4% increase in annual continental investment ensures reliability against future hydroclimatic variability. However, cooperation between countries is needed to overcome the divergent spatial distribution of investment costs and potential energy deficits.

Neuro-Evolutionary Direct Policy Search for Multiobjective Optimal Control.

Direct policy search (DPS) is emerging as one of the most effective and widely applied reinforcement learning (RL) methods to design optimal control policies for multiobjective Markov decision processes (MOMDPs). Traditionally, DPS defines the control policy within a preselected functional class and searches its optimal parameterization with respect to a given set of objectives. The functional class should be tailored to the problem at hand and its selection is crucial, as it determines the search space within which solutions can be found. In MOMDPs problems, a different objective tradeoff determines a different fitness landscape, requiring a tradeoff-dynamic functional class selection. Yet, in state-of-the-art applications, the policy class is generally selected a priori and kept constant across the multidimensional objective space. In this work, we present a novel policy search routine called neuro-evolutionary multiobjective DPS (NEMODPS), which extends the DPS problem formulation to conjunctively search the policy functional class and its parameterization in a hyperspace containing policy architectures and coefficients. NEMODPS begins with a population of minimally structured approximating networks and progressively builds more sophisticated architectures by topological and parametrical mutation and crossover, and selection of the fittest individuals concerning multiple objectives. We tested NEMODPS for the problem of designing the control policy of a multipurpose water system. Numerical results show that the tradeoff-dynamic structural and parametrical policy search of NEMODPS is consistent across multiple runs, and outperforms the solutions designed via traditional DPS with predefined policy topologies.

Advancing the representation of reservoir hydropower in energy systems modelling: The case of Zambesi River Basin.

In state-of-the-art energy systems modelling, reservoir hydropower is represented as any other thermal power plant: energy production is constrained by the plant's installed capacity and a capacity factor calibrated on the energy produced in previous years. Natural water resource variability across different temporal scales and the subsequent filtering effect of water storage mass balances are not accounted for, leading to biased optimal power dispatch strategies. In this work, we aim at introducing a novelty in the field by advancing the representation of reservoir hydropower generation in energy systems modelling by explicitly including the most relevant hydrological constraints, such as time-dependent water availability, hydraulic head, evaporation losses, and cascade releases. This advanced characterization is implemented in an open-source energy modelling framework. The improved model is then demonstrated on the Zambezi River Basin in the South Africa Power Pool. The basin has an estimated hydropower potential of 20,000 megawatts (MW) of which about 5,000 MW has been already developed. Results show a better alignment of electricity production with observed data, with a reduction of estimated hydropower production up to 35% with respect to the baseline Calliope implementation. These improvements are useful to support hydropower management and planning capacity expansion in countries richly endowed with water resource or that are already strongly relying on hydropower for electricity production.

When timing matters-misdesigned dam filling impacts hydropower sustainability.

Decades of sustainable dam planning efforts have focused on containing dam impacts in regime conditions, when the dam is fully filled and operational, overlooking potential disputes raised by the filling phase. Here, we argue that filling timing and operations can catalyze most of the conflicts associated with a dam's lifetime, which can be mitigated by adaptive solutions that respond to medium-to-long term hydroclimatic fluctuations. Our retrospective analysis of the contested recent filling of Gibe III in the Omo-Turkana basin provides quantitative evidence of the benefits generated by adaptive filling strategies, attaining levels of hydropower production comparable with the historical ones while curtailing the negative impacts to downstream users. Our results can inform a more sustainable filling of the new megadam currently under construction downstream of Gibe III, and are generalizable to the almost 500 planned dams worldwide in regions influenced by climate feedbacks, thus representing a significant scope to reduce the societal and environmental impacts of a large number of new hydropower reservoirs.

Infectious agents identified in aborted swine fetuses in a high-density breeding area: a three-year study.

Reproductive failure in sows is one of the most important factors affecting pig breeding. Many reproductive disorders are linked to both environmental factors and infectious agents. The goal of our study was to determine the presence of pathogens that are known to cause abortion, considering a set of conditioning factors, such as seasonality and pregnancy period. A large number of aborted fetuses (1,625 fetuses from 140 farms) from a high-density breeding area in northern Italy was analyzed for a period of 3 years. The pigs were diagnosed based on direct (culture, PCR) or indirect (enzyme-linked immunosorbent assay) evidence. An infectious etiologic agent was found in 323 of 549 cases of abortion (58.8%). These included viral agents (Porcine circovirus-2, 138/323; Porcine reproductive and respiratory syndrome virus, 108/323; porcine parvovirus, 20/323; pseudorabies virus, 6/323; and Encephalomyocarditis virus, 3/323) and bacteria (Escherichia coli, 64/323; Streptococcus sp., 63/323; Staphylococcus sp., 5/323; Pasteurella sp., 3/323; Shigella sp., 1/323; and Yersinia sp., 1/323). This study describes the prevalence of infectious agents involved in reproductive failure in a high-density swine population. The data can be useful to swine breeders, practitioners, and medical specialists in monitoring animal health and in supervising the breeding process.