Energy Sufficiency for Rural Communities: The Case of The Bolivian Lowlands

Access to energy has proved to have strong links to other dimensions of socio-economic develop ment. As a first step to ensure electricity coverage in developing countries’ rural communities, a minimum energy access must be settled. To do this, the theoretical concept of energy sufficiency is expanded to fit in the rural energy access logic. Ideally, un-electrified communities must move from low energy consumption states to a position where they consume enough to have a contin uous development without risking global environment goals. For that purpose, a bibliographic review is performed to define the components of an ideal rural community where people’s basic needs for energy services are met equitably. Main findings show that besides the household component, public lighting, education, health, water and production services must be considered at the moment of estimated energy demands for rural electrification. To test the implication of this, a series of plausible village configurations of the Bolivian lowlands are proposed and simulated using a bottom-up stochastic model. Not considering community services and income generating activities, carries a 45 % underestimation on peak demand. In addition, improving people’s living conditions has a considerable effect on the electricity demand of Bolivia’s rural lowland communities

Using PyPSA-Earth to address energy systems modelling gaps in developing countries. A case study for Bolivia

peer reviewedBolivia is a developing country in South America which is slowly starting its energy transition towards more renewable technologies. However, at this moment, Institutions in charge of regulating, operating, and planning the development of the sector are still working with “black box” (or licensed) models, which are costly and less transparent, and are highly dependent on external expertise to formulate national plans. A proper transition will arguably require endogenous know-how and resources to be sustainable, affordable, and sovereign for the country. In this context, open-source energy models are increasingly used in Bolivia, mostly by academic and non-profit institutions. These are used to study alternative development scenarios, quantify environmental impacts and/or define potential techno-economic requirements. Previous works have focused on the development of dispatch models that analyse the stability and operation over short-terms and on energy-balance models to study impacts over long-term scenarios. However, while operation and planning aspects are somewhat covered independently, the combination of both is still missing (i.e. high time and spatial resolution and long-term horizon perspectives). To bridge this gap the PyPSA-Earth model was identified and used to derive a model specific for the Bolivian context using a dedicated workflow. The model is adapted to run and provide country-specific outputs regarding generation capacities, grid expansion and sector-specific demands, which are later compared with historical information to assess its accuracy and capabilities. Modelling results provide inputs regarding the characteristics of the tool and quantify deviations of its outputs compared to the Bolivian system in 2020. Based on these, it is concluded that the flexibility of the model, combined with its transparent structure, show great potential for implementation.7. Affordable and clean energ

Modeling hydropower to assess its contribution to flexibility services in the Bolivian power system

peer reviewedBolivia has an important hydroelectric potential that has the potential to be an important part of future energy supply. This potential is due to the topographic characteristics of the country, composed of two large hydrological systems, the Amazon and La Plata basin, with a power of 34,208.50 MW and 5,359.90 MW respectively. Hydropower has been increasing in the Bolivian territory in recent years, with a tripe objective: guarantee energy sovereignty, industrial development and the export of electrical energy. Today, the power system has a 33 % share of hydraulic component, a 61 % share of thermal component, and the rest of other renewable energy sources. Such a composition makes the system vulnerable to hydrological variations that can affect production costs and flexibility of the energy system. Therefore, this study aims to assess the effects of different rainfall years on the ability of hydropower to generate and store electricity. This is done using the hourly power system simulation software Dispa-SET, primarily developed by the European Commission. For the application of the methodology, the Dispa-Set Bolivia model is taken as a basis. For this study the hydroelectric systems are disaggregated by hydro unit, which allows to include the flows of sub-basins in run-of-the-river plants. The information on water inputs for different years is obtained from the Surface Water Balance of Bolivia 2017, which uses the Soil Moisture method (rainfall-runoff) through the software Water Evaluation and Planning (WEAP), for a period from 1980 to 2016. The model optimizes the system under all hydro years, both with a mid-term scheduling approach and a short-term optimal dispatch and unit commitment approach. Modeling has allowed to obtain a broad vision of different scenarios, where main results show that heavy rainfall years affect the electricity production of hydro plants by impacting the flexibility hydropower can provide to the system. This results in changes on the average production costs, which is quantified by differences in terms of electricity production of hydropower plants

Exploring the Tradeoff between Installed Capacity andUnserved Energy in Rural Electrification

peer reviewedWith the current goal of reaching a 100% electrification rate of the world population, the importance of PV/battery orsolar home systems (SHS) grows as the one of the most viable solution for the most remote and scattered communities.Their modularity and capacity to harvest local resources is particularly relevant for that purpose. The stochasticity of solarenergy and of the demand can however lead to energy shortages in the most critical periods of the day, while an over-sizedsystem represents an important increase in the levelized cost of energy (LCOE). To capture these dynamics and the trade-off between installed capacity and lost load probability (LLP), 16 different demand scenarios are modeled and analyzed.An optimal size for SHS is determined using a linear programming model with different levels of LLP in each scenario. TheDemand time series are constructed using a stochastic demand generator that simulates the behavior of each applianceon a household. The information to create the base-case scenario was obtained with field surveys of a rural community inCochabamba, Bolivia (Raqaypampa). Each scenario has different combinations of appliances, including the intensive useof radio to comply with guidelines of remote education (due to the COVID-19 crisis). The result shows that there is a highreduction of the LCOE in the lower range of LLP. This reduction reaches a breaking point where a higher LLP does notrepresent a significant further reduction of the LCOE. An empirical mathematical formulation is proposed to calculate thisinflection point and a Pareto front plotted to assess the tradeoff between quality of service and LCOE

Energy Transition Planning with High Penetration of Variable Renewable Energy in Developing Countries: The Case of the Bolivian Interconnected Power System

The transition to a more environmentally friendly energy matrix by reducing fossil fuel usage has become one of the most important goals to control climate change. Variable renewable energy sources (VRES) are a central low-carbon alternative. Nevertheless, their variability and low predictability can negatively affect the operation of power systems. On this issue, energy-system-modeling tools have played a fundamental role. When exploring the behavior of the power system against different levels of VRES penetration through them, it is possible to determine certain operational and planning strategies to balance the variations, reduce the operational uncertainty, and increase the supply reliability. In many developing countries, the lack of such proper tools accounting for these effects hinders the deployment potential of VRES. This paper presents a particular energy system model focused on the case of Bolivia. The model manages a database gathered with the relevant parameters of the Bolivian power system currently in operation and those in a portfolio scheduled until 2025. From this database, what-if scenarios are constructed allowing us to expose the Bolivian power system to a set of alternatives regarding VRES penetration and Hydro storage for that same year. The scope is to quantify the VRES integration potential and therefore the capacity of the country to leapfrog to a cleaner and more cost-effective energy system. To that aim, the unit-commitment and dispatch optimization problem are tackled through a Mixed Integer Linear Program (MILP) that solves the cost objective function within its constraints through the branch-and-cut method for each scenario. The results are evaluated and compared in terms of energy balancing, transmission grid capability, curtailment, thermal generation displacement, hydro storage contribution, and energy generation cost. In the results, it was found that the proposed system can reduce the average electricity cost down to 0.22 EUR/MWh and also reduce up to 2.22 × 106 t (96%) of the CO2 emissions by 2025 with very high penetration of VRES but at the expense of significant amount of curtailment. This is achieved by increasing the VRES installed capacity to 10,142 MW. As a consequence, up to 7.07 TWh (97%) of thermal generation is displaced with up to 8.84 TWh (75%) of load covered by VRES

Techno-economic assessment of high variable renewable energy penetration in the Bolivian interconnected electric system

Bolivia plans significant investments in conventional and renewable energy projects before 2025. Deployment of large hydro-power, wind and solar projects are foreseen in the investment agenda. However and despite the large renewable potential in the country non-conventional renewable technologies are not yet considered to be a main source in the supply chain. The aim of this article is to evaluate the flexibility of the Bolivian power generation system in terms of energy balancing, electricity generation costs and power plants scheduling in a scenario that considers large solar and wind energy technology deployment. This is done using an open source unit commitment and optimal dispatch model (Dispa-SET) developed by the Joint Research Center of the European Commission. National data for existing infrastructure, committed and planned energy projects are used to assess the case of Bolivia.  The base scenario consider all techno-economic data of the Bolivian power system up to 2016. A harmonized dataset is gathered and released as open data to allow other researchers to run and re-use the model. This model is then used to simulate scenarios with different levels of solar and wind energy deployment. Results from the analysis show that an energy mix with participation of solar and wind technology with values lower than 30% is technically feasible and indicates that further grid reinforcements are required

The Energy Sufficiency Concept and Its Impact on Energy Demand Estimation in Rural Communities from Developing Countries

Achieving universal electrification is a complex task because the populations that still do not have access to electricity are usually located in remote areas. The sizing of adequate energy systems requires a detailed study of the energy demand in the communities to be electrified. In this sense, the aim of this work is to explore the evolution of the electricity demand if rural communities follow a development path towards a state of ’energy sufficiency’. With this aim, a series of plausible scenarios are modelled using a bottom-up stochastic model to obtain the electricity demand. Main findings show the importance of considering three main sector of consumers (residential, community services and income generating activities) at the moment of analyzing the demand. The demand increases significantly between scenarios and the contribution of each considered sector is different. There are also substantial differences between the lowlands and highlands of Bolivia in terms of the energy demand of rural communities.7. Affordable and clean energ

Evaluación del costo de electrificación rural en Bolivia para alcanzar el ODS 7

This study quantifies the challenge posed by achieving Sustainable Development Goal 7: Access to Affordable and Clean Energy (SDG7) in Bolivia. The solution proposed by the project estimates the total cost of supplying electricity in all Bolivian populations, considering relevant socioeconomic factors when planning the total coverage for the country. The project has two stages: the first consists of data collection and analysis of the demand, as well as the perception / vision of the populations in relation to the use of energy; the second focuses on the analysis of the information and the generation of results. The collection of field data that contemplate energy demand and the behavior in the use and consumption of energy was carried out in the communities of Raqaypampa (Cochabamba) and El Sena (Pando). They complemented information previously obtained from El Espino (Santa Cruz) and Toconao (Altiplano bordering Chile). The Social Sciences Research Institute (INCISO), ENERGÉTICA and the Energy Research Center (CIE), with the information collected and data on indicators from the SDSN, structured the standard composition of a rural community in Bolivia. With this information, the RAMP demand curve generation program simulated the demands for populations in the low and high areas of Bolivia, then contrasting with different technologies of electrification; Thus, the most efficient cost of the solutions found was calculated. Finally, the cost to fully electrify the Bolivian population was estimated and, in particular, to electrify 100% of the isolated and dispersed population that reaches 587 million dollars, giving coverage to 273,286 rural families

Optimal design and deployment of isolated energy systems: The Bolivian pathway to 100 % rural electrification

During the past decades, the planet has undergone increased environmental pressure. This has led to a clear momentum towards the creation of a more sustainable world. In this context, the challenge to provide energy access for all in a fair and sustainable way is an enormous task. The international agency of energy has estimated that yearly investments of 55 billion USD are needed to reach set targets. To optimize the limited resources, researchers have focused on the use of geographical information systems (GIS) to better capture the spatial dimension and define least-cost pathways to universal energy access. The size of the deployment problem imposes to model dispersed energy demands and isolated energy systems in a simplified manner, which can lead to suboptimal solutions. In consequence, there is a need to capture the diversity of conditions in which these systems are deployed. The goal of this thesis is to contribute to the modeling of rural electrification processes through tailored models and methods. These tools are integrated into a coherent modeling framework, covering the whole value chain between accurate characterization of household demand to the macroscopic (national) planning of rural electrification. The models related to each relevant scale are soft-linked by defining common variables of interest. Then, methods to integrate the results of the more detailed models into the higher-level model are introduced. This approach provides additional technical insights and a better spatio-temporal optimum. The structure of this thesis reflects this bottom-up approach. It is organized in three parts. The first part deals with energy demand modeling in a rural context and presents the Bolivian case study. It introduces two methods to create stochastic load profiles depending on the available data (measurements or surveys). In addition, it explores the components of an ideal rural community and frames appliance ownership according to surveys in rural communities. Finally, demand curves at the household and community level are generated using an ad-hoc stochastic bottom-up profile generation model. The second part presents and applies an optimal sizing and operation framework for isolated energy systems in different contexts. The operational data from an existing microgrid in Bolivia is used as a benchmark and as a test case to test the model. Different sizing methods and formulations are compared, leading to the conclusion that a compromise must be found between system reliability and computational tractability. Finally, the trade-off between cost and lost load probability in single households equipped with a solar home system is analyzed. The third part deals with the creation of surrogate models for microgrid design and its use in GIS-based electrification models. The limitations of existing GIS tools are discussed and surrogate models are proposed as a solution to increase accuracy without compromising the solving time of the model. A methodology to create and validate surrogate models for rural electrification is introduced. Then, the OnSSET model is adapted and improved to integrate this new formulation. Finally, different electrification scenarios are computed for the case of Bolivia, where both hybrid microgrids and solar home systems proved to be essential technologies for the cost-optimal electrification of remote communities