• Energy Research

Abstract Achieving the maximum economic profitability is a priority for microgrid developers. However, although economic indicators usually dominate the business decision making, rarely numerical indicators are fully able to capture the entire sociopolitical, technical and geographical circumstances affecting the business environment, especially in rural areas of developing countries. Typical planning approaches achieve a single solution, or a set of solutions in multi-objective approaches, and near-optimal solutions are usually discarded even when they may better fit the specific multi-faceted circumstances of a project. In this paper, we propose a multi-objective approach that not only calculates the traditional Pareto-frontier but also compiles near-optimal solutions that enlarge the options portfolio for microgrid developers. The proposed iterative approach stores all the simulated solutions, and post-processes them to provide the developer with multiple design options (MDO). A modified version of Multiple-Objective Particle Swarm Optimization (MDO-MOPSO), with improved convergence criteria based on quadratic mean of the crowding distances and spread, is developed and used. A numerical case study of a Kenyan hybrid microgrid using real data confirms that near-optimal solutions can correspond to extremely different design solutions, even ± 100 % w.r.t. the Pareto-efficient ones, with only very limited disparities in the economic objective functions. The results, supported by a Key Performance Indicator (KPI) analysis, based on diversity measures, show that MDO methodology can successfully support the business decision making and help developers size microgrids considering several nearly-equivalent sizing options.

This study presents sector-coupled PyPSA-Earth: a novel global open-source energy system optimization model that incorporates major demand sectors and energy carriers in high spatial and temporal resolution, to enable energy transition studies worldwide. The model includes a workflow that automatically downloads and processes the necessary demand, supply and transmission data to co-optimize investment and operation of energy systems of countries or regions of Earth. The workflow provides the user with tools to forecast future demand scenarios and allows for custom user-defined data in several aspects. Sector-coupled PyPSA-Earth introduces novelty by offering users a comprehensive methodology to generate readily available sector-coupled data and model of any region worldwide, starting from raw and open data sources. The model provides flexibility in terms of spatial and temporal detail, allowing the user to tailor it to their specific needs. The capabilities of the model are demonstrated through two showcases for Egypt and Brazil. The Egypt case quantifies the relevant role of PV, exceeding 35 GW, and electrolysis in Suez and Damietta regions, for meeting 16% of the EU hydrogen demand. Complementarily, the Brazil case confirms the model's ability in handling hydrogen planning infrastructure, including repurposing of existing gas networks which results in 146 M€ lower costs than building new pipelines. The results prove the suitability of sector-coupled PyPSA-Earth to meet the needs of policymakers, developers, and scholars in advancing the energy transition. The authors invite the interested individuals and institutions to collaborate in the future developments of the model within PyPSA meets Earth initiative.

The lack of electricity access is increasingly concentrated in rural areas of developing countries, in which mini-grids are often a suitable solution; however, given the high risks, it is crucial to minimize costs. This paper aims at analyzing existing methodologies for the optimal design of mini-grids combined with different operating strategies. Typical system operations, like the load-following (LFS) and cycle charging (CCS) strategies, are compared with the more demanding predictive strategies based on Mixed-Integer Linear Programming (MILP). The problem is formulated and solved with Particle Swarm Optimization (PSO), so to simulate traditional and predictive operating strategies. Two reformulations based on the proposed Search Space Update are also detailed and compared with the so-called one-shot MILP model, which is able to con-jointly optimize both the design and the operation of the system, in order to reduce computational requirements with the predictive strategy. The results, tailored with data from a rural mini-grid in Kenya, highlight that heuristic methodologies can perform better than the traditional MILP approach, both in terms of optimality and computational time, especially when advanced operating strategies are considered. Conventional operating strategies (LFS or CCS) appear to be sub-optimal, but require very little computational requirements, which makes them suitable for preliminary designs.

Mini-grids are well known to be a suitable solution to foster rural electrification in developing countries, and yet risks and high costs are hampering their spreading. Even though effective tools can help developers to identify the optimal design and operation of a mini-grid, no standard approach have emerged yet. This paper proposes a numerical comparison among deterministic methodologies to optimize a rural minigrid considering the effect of different operating strategies. The typical load-following and cycle-charging strategies are compared to predictive approaches, as rolling-horizon and a one-shot model, which optimizes both the design and operation together. The two latter models allow achieving additional savings compared to traditional operating strategies, but the computational requirements increase sharply. Results suggest that sizing methodologies using load-following or cycle-charging strategies are more suitable for preliminary design, while predictive approaches should be used for the fine tuning of the size of components. This study can provide guidance on design and operating methodologies for rural mini-grids in developing countries.

Abstract Designing off-grid microgrids is a costly and risky activity, especially for newly electrified communities in developing countries. Private developers and researcher have been using several economic indicators to value the profitability of an investment, such as Net Present Value, Discounted Payback Period, Levelized Cost of Electricity; however, each index has its advantages and specific limitations. Selecting a single objective may lead the developer to misestimate the profitability of a project, because a single index cannot accommodate the variety of requirements of the business process. Acknowledging this, this study proposes a wide analysis for highlighting the effects of different indicators onto the optimal design of an off-grid hybrid energy system. A multi-objective approach that optimizes together different economic indicators is proposed, based on the results of a preliminary analysis on single-objective formulations. A sensitivity analysis with respect to the electricity price, the load curtailment cost and the dispatching strategy is also performed. A numerical case study is proposed for a possible off-grid microgrid in Soroti, Uganda, which well represents a hard environment for business development. Results suggest that the proposed multi-objective approach provides intermediate configurations that are a good compromise between multiple objectives, thus satisfying the difficult environment developers are enduring.

AbstractThe lack of affordable, clean, and reliable energy in Africa’s rural areas forces people to resort to poor quality energy source, which is detrimental to the people’s health and prevents the economic development of communities. Moreover, access to safe water and food security are concerns closely linked to health issues and children malnourishment. Recent climate change due to global warming has worsened the already critical situation.Electricity is well known to be an enabler of development as it allows the use of modern devices thus enabling the development of not only income-generating activities but also water pumping and food processing and conservation that can promote socioeconomic growth. However, all of this is difficult to achieve due to the lack of investors, local skills, awareness by the community, and often also government regulations.All the above mentioned barriers to the uptake of electricity in rural Kenya could be solved by the coordinated effort of government, private sector, and academia, also referred to as Triple Helix, in which each entity may partially take the other’s role. This chapter discretizes the above and shows how a specific county (Marsabit) has benefited from this triple intervention. Existing government policies and actions and programs led by nongovernmental organizations (NGOs) and international agencies are reviewed, highlighting the current interconnection and gaps in promoting integrated actions toward climate change adaptation and energy access.

Abstract Reaching universal access to electricity by 2030 requires a massive deployment of mini-grids in rural areas of developing countries. Among the many challenges hindering this process, there are the high uncertainties in assessing demand patterns in rural communities, the costs of field survey campaigns, and the absence of ample and reliable datasets coming from existing projects. This paper tries to address these issues by presenting and discussing a database of load profiles from sixty-one off-grid mini-grids from developing countries worldwide, gathered from the literature, private developers and fieldworks, and reported with technical, socio-economic and geographical characterization factors. A clustering procedure led to the identification of five archetypal load profile clusters, which are presented and analyzed together with their load duration curves. Subsequently, the distribution among the clusters of the various characterization factors selected is studied. The proposed approach allows to widen the range of load profiles usually considered, and to seek correlations between the load profile shapes, the peak power and average energy consumption per connection, the number of customers, the age of measurement, geographical position, operator model, type of tariff and generation technologies present. This work establishes a first step in the creation of a shared database for load profiles of rural mini-grids, helping to overcome the lack of available data and difficulties of demand assessment, proposing original insights for researchers to understand load patterns, and contributing to reduce risks and uncertainties for mini-grid developers.

Rural electrification in remote areas of developing countries has several challenges which hinder energy access to the population. For instance, the extension of the national grid to provide electricity in these areas is largely not viable. The Kenyan Government has put a target to achieve universal energy access by the year 2020. To realize this objective, the focus of the program is being shifted to establishing off-grid power stations in rural areas. Among rural areas to be electrified is Habaswein, which is a settlement in Kenya’s northeastern region without connection to the national power grid, and where Kenya Power installed a stand-alone hybrid mini-grid. Based on field observations, power generation data analysis, evaluation of the potential energy resources and simulations, this research intends to evaluate the performance of the Habaswein mini-grid and optimize the existing hybrid generation system to enhance its reliability and reduce the operation costs. The result will be a suggestion of how Kenyan rural areas could be sustainably electrified by using renewable energy based off-grid power stations. It will contribute to bridge the current research gap in this area, and it will be a vital tool to researchers, implementers and the policy makers in energy sector.