Electricity demand forecasting for rural communities in developing countries: Calibrating a stochastic model for the Bolivian case

The world crusade to close the electrification gap is coming to an end in most regions of the world. In recent years the research in the area has concentrated on the development of planning methods to minimise the cost of implementation. Although successful, the lack of focus on the complex dynamics that govern electricity demand lead to over/under-sizing of technical solutions resulting in waste of resources and missed developing opportunities. In this sense, this paper aims to propose an electricity demand model for rural communities in Bolivia, based on an open-source bottom-up stochastic tool for load profile computation. The “energy sufficiency” concept is used to ensure that people’s basic needs for energy are met in all the analysed cases. Information from various sources, such as on-site surveys, databases and national reports were used to characterise the main geographical areas in Bolivia and the relative specific categories of users. Specific load curves generated with the model were used as inputs in a micro-grid sizing tool and the results were compared with an approach using a demand analysis in less detail. Main results show that the model obtained is capable of generating stochastic demand curves for single or multiple rural communities according to contextual particularities. Notably, the geographic location and the socioeconomic characteristics have a significant impact in the peak loads and the total demand. Considering small industries as an income generating activity can increase in the peak load by about 45%, consequently, there is an economic impact when investing in the solution.Tailored energy system models for energy planning in Bolivia7. Affordable and clean energ

Stability and Reserve Constraints in Optimal Dispatch Models

The United Nations Framework Convention on Climate Change (UNFCCC) is strongly committed to accelerating the transition of the power sector towards a high penetration of Variable Renewable Energy (VRE) sources, with the goal of reducing global dependence on fossil fuels for power generation. However, this transition poses a significant challenge, as the increasing VRE share in power systems gradually decreases their rotational inertia. This reduction in rotational inertia negatively impacts the stability and safety of power systems, creating new operational challenges. To address this, transmission system operators (TSO) have defined strategies to compensate for unexpected imbalances between load and generation by contracting primary and secondary reserves. Nevertheless, a method that compensates for the inertial response excursion after a disturbance adapted to these tools has not yet been fully identified. This work proposes a deterministic estimation of inertia constraint in UC/OD models. The Rate of change of Frequency (RoCoF) is estimated from an Optimal Dispatch model by considering the worst-case contingency in the test case. Then the lower inertia limit required to operate the system with stability is estimated. The estimation of the inertia limit is done offline the optimization and added as a new constraint in the UC/OD model. Finally, different scenarios of VRE penetration are defined to evaluate the impact of this new constraint with a sensitivity analysis. Results show that the proposed method can be complementary applied to UC/OD models to reduce the risk of unintended load shedding, which might lead to cascading failures and blackouts.ARES-CDD and ARES PRDBOL2022 programmes7. Affordable and clean energy13. Climate actio

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

Swarm electrification: Harnessing surplus energy in off-grid solar home systems for universal electricity access

peer reviewedAchieving universal access to electricity by 2030, as set out by the Sustainable Development Goals, presents a significant challenge given the current rate of progress. A recent promising concept is swarm electrification. Its central idea is the peer-to-peer energy sharing of surplus energy in solar home systems (SHSs) to connect additional neighbors and grow a bottom-up grid. This paper studies the surplus energy in SHSs and its underlying influencing factors as a basis for swarm electrification. An open-source multi-model-based techno-economic analysis of off-grid SHS including surplus energy as a value is presented. Three distinct household types from the tier 3 category in the Multi-tier framework are compared based on their unique ratios of peak-to-average demand and percentage of load consumption during sun hours. A statistical analysis of surplus energy for each household type is presented and energy sharing with additional households at tier 1–2 is simulated. Two economic analysis methods, including surplus energy, are presented and compared: single-objective cost minimization and multi-objective compromise programming. The study finds that a low ratio of demand during sun hours leads to higher surplus energy volumes, while a peak-to-average ratio alone cannot give such indications. Both economic methods suggest that optimizing the SHS design for tier 3 households involves a slight increase in solar power capacity when considering the expected revenue from selling surplus energy to 2–3 households in tiers 1–2. The total cost for the tier 3 households are reduced by 40%−64%, additionally to decreasing their own lost load by 4%−7%, and reducing the up-front cost to get electricity access for the tier 1–2 households by 50% compared to purchasing their own full SHS

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

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

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