Experiments with Subversion Over OpenNetInf and CCNx

We describe experiences and insights from adapting the Subversion version control system to use the network service of two information-centric networking (ICN) prototypes: OpenNetInf and CCNx. The evaluation is done using a local collaboration scenario, common in our own project work where a group of people meet and share documents through a Subversion repository. The measurements show a performance benefit already with two clients in some of the studied scenarios, despite being done on un-optimised research prototypes. The conclusion is that ICN clearly is beneficial also for non mass-distribution applications

Subversion Over OpenNetInf and CCNx

We describe experiences and insights from adapting the Subversion version control system to use the network service of two information-centric networking (ICN) prototypes: OpenNetInf and CCNx. The evaluation is done using a local collaboration scenario, common in our own project work where a group of people meet and share documents through a Subversion repository. The measurements show a performance benefit already with two clients in some of the studied scenarios, despite being done on un-optimised research prototypes. The conclusion is that ICN clearly is beneficial also for non mass-distribution applications. It was straightforward to adapt Subversion to fetch updated files from the repository using the ICN network service. The adaptation however neglected access control which will need a different approach in ICN than an authenticated SSL tunnel. Another insight from the experiments is that care needs to be taken when implementing the heavy ICN hash and signature calculations. In the prototypes, these are done serially, but we see an opportunity for parallelisation, making use of current multi-core processors

Determining the factors of household energy transitions: A multi-domain study

Energy transitions at the household level are important because there are so many households, and motives and barriers to these transitions processes are not well understood. The objective of this paper is to investigate explanatory variables of household energy transitions. We select papers investigating explanatory variables underpinning household energy transitions in three domains: adoption of solar photovoltaics (PV) in households, adoption/transition to sustainable residential heating systems (RHS) and adoption/transition to alternative fuel vehicles (AFVs). In all three domains the chosen literature employ a wide variety of quantitative analyses such as discrete choice models ranging from multinomial logit models and principal component analysis to qualitative assessment of the answers through inductive analysis. The explanatory variables are categorized in six superordinate explanatory variable categories of economic factors, environmental factors, personal preferences and values, social factors, household characteristics and market and policy factors. In total we identify 31 explanatory variables which have been investigated in the 38 articles chosen, falling under the six categories. Investment cost is an important explanatory variable for all three domains, but a policy variable such as government subsidy could mitigate the former explanatory variable. We propose a conceptual framework as an initial step towards understanding the interactions and impacts of the explanatory variables with each other

Understanding social innovation in local energy transitions processes: A multi-case study

Social innovation (SI) in local energy transitions is gaining focus in current times but energy transitions have not yet been explicitly analysed in the context of SI. Our objective is to characterize SI in co-created local energy transitions processes through the study of three distinct cases based on energy transitions in localities in Sweden (Sk\ue5ne and Dalsland) and Denmark (Hj\uf8rring). In these localities, municipality actors (MA) are engaged in increasing the adoption of solar PV systems, uptake of EV and biogas cars, and phasing out oil-burners, respectively. We analyse the three cases by following the work of the MAs and through the frame of Transformative Social Innovation (TSI), which consists of four shades; social innovation, system innovation, game-changers, and narratives of change. Subsequently, we use causal loop diagrams to characterize the SI in the oil-burner phase-out case. We see shades of SI and system innovation but there are no ‘game changers’ or ‘narratives of change’ yet in any of the cases

Impacts of social innovation on local energy transitions: Diffusion of solar PV and alternative fuel vehicles in Sweden

Local energy transitions are gaining widespread attention through their contribution to sustainability, notably to climate change mitigation. Social innovation (SI) in local energy transitions have been scrutinized in multiple works, but the impact of SI on the local energy transitions is an under-studied field. The objective of this study is to put forward a method to model SI in local energy transitions. This is done using System Dynamics modelling (SDM) of the local energy transitions processes. The SDM method is to study a broad spectrum of socio-techno-natural phenomena, generally. In this study, SDM is used to capture the endogenous factors which underpin the transition processes. This study is based on two cases: solar photovoltaics (PV) diffusion in Sk\ue5ne, and transition to alternative fuel vehicles (AFV) in Dalsland, Sweden. The transitions are modelled with the municipality actors providing input. Two simulation runs of the local transitions are executed, namely the Base run and No SI run. The Base run has the municipality actors’ co-creation actions. Results show that the co-creation actions induce a significant increase in the diffusion of electric vehicles in Dalsland and higher diffusion of solar PV in Sk\ue5ne. The main outcome of this study is a model to assess the possible impacts of SI on local energy transitions. Ultimately, we hope to contribute to methods of quantitatively assessing the impact of SI in local energy transitions

Enhancing Urban Heating Systems Planning through Spatially Explicit Participatory Modeling

Effective planning of urban heating systems is crucial for achieving net-zero emissions at the city level. In particular, the spatial dimension plays a pivotal role in shaping the design and operation of these systems. Nonetheless, the integration of urban spatial and energy planning is rarely performed. To address this deficit, the current study proposes a participatory modeling methodology that explicitly incorporates the spatial dimension to facilitate integration and decision-making in the planning of urban heating systems. The methodology is applied to a case municipality to evaluate its benefits and implications for stakeholders involved in urban heat planning. The results reveal that the participatory nature of the methodology enhances the legitimacy, transparency, and relevance of the modeling process by engaging urban stakeholders, so as to exploit their valuable knowledge, experience, and understanding of the local context and related challenges. The developed methodology provides a spatial representation of district heating expansion, heating technology transition at the district-building level, and the installed capacities in each district, thereby improving the coherence of urban heat planning integrated with other urban plans. Consequently, the incorporation of the spatial dimension adds a nuanced layer of modeling outcomes to standard city level optimization models

Performance and reliability analysis of an off-grid PV mini-grid system in rural tropical Africa: A case study in southern Ethiopia

Although some progress has been made in recent years, ensuring universal access to electricity remains a major challenge in many countries in sub-Saharan Africa, particularly in rural areas. In light of this challenge, solar photovoltaic (PV) mini-grid systems have emerged as a promising solution for off-grid electrification. However, little is known about their actual performance and reliability when used in real-world applications. Using real-time monitored data and IEC\u27s evaluation standard, this paper examines the performance and reliability of a 375 kWp off-grid PV mini-grid system installed in a remote small town in Ethiopia. The findings showed that the mini-grid produced 1182 kWh/day of electricity compared to the estimated generation of 2214 kWh/day, a difference of 1032 kWh/day (46.6% less). In contrast, 87% of the average daily electricity generated was delivered to the load. The discrepancies can be attributed to average PV capture losses of 2.75 kWh/kWp/day and system losses of 0.40 kWh/kWp/day. The performance evaluation results revealed that the mini-grid system is performing poorly, with average on-site module efficiency (ηpc), temperature corrected performance ratio (PRcorr), capacity factor (CF) and overall system efficiency (ηsys) of 9.85%, 42%, 13%, and 8.76%, respectively. It was found that the daily PV energy output could not meet the daily demand. As a result, the load is shed off from the power supply for 13 h a day; between 17:00 and 19:00 and again between 21:00 and 08:00. The study demonstrated that accurate demand assessment and robust system sizing, taking into account the impact of local weather conditions and prospective electricity demand growth is critical to ensure high performance and reliability of off-grid PV mini-grid systems

Long-term optimal capacity expansion planning for an operating off-grid PV mini-grid in rural Africa under different demand evolution scenarios

Using real-time load data and HOMER Pro\u27s ‘multi-year’ optimization tool, this paper investigates the long-term cost optimal capacity expansion planning (CEP) for an overloaded photovoltaic (PV) mini-grid (MG) with storage batteries in off-grid rural Ethiopia over a 20-year planning horizon. Three distinct annual energy demand growth scenarios were considered: 0 % (fulfils the minimum load requirement), 5 %, and a 15 % from productive users only. In all scenarios, the generation mix consists of only solar energy and the maximum allowable capacity shortage (MACS) is limited to 10 %. The findings reveal that, in all scenarios, the largest capacity expansion is performed on the battery and PV systems, covering up to 73 % and 35 % of the total expansion costs, respectively. The annual unmet load fraction of the expanded MG system ranges from 5.9 % in scenario-3 to 9.4 % in scenario-1, and the cost of electricity (LCOE) ranges from $0.404/kWh in scenario-3 to$0.887/kWh in scenario-1. The results indicate that the scenario-3 expansion path is comparatively cost-effective and has the highest reliability; but it still falls short of fully satisfying the required load demand and is not financially viable. Surprisingly, increasing the reliability of the scenario-3 capacity expansion from 94 % to 100 % raises the MG\u27s Net Present Cost by 37 %. The sensitivity analysis shows that the MACS, ambient temperature, and battery\u27s depth of discharge significantly affect the cost and performance of the capacity expansion. The study demonstrates (a) there are significant trade-offs between minimizing MG expansion costs and maximizing reliability levels; (b) capacity expansion based solely on cost-minimization without considering key constraints and uncertainties (demand, cost, PV, and battery degradations) may not provide a practical and robust solution to severe reliability issues, (c) capacity expansion that supports demand from productive users increases the cost-effectiveness and bankability of isolated MGs

Households and tree-planting for wood energy production – Do perceptions matter?

While forests are a primary source of energy for the majority of Tanzanian households, the forest cover is rapidly declining. The Tanzanian government has introduced a tree-planting campaign strategy, aimed at reducing pressure on natural forests. However, the campaign appears not to have contributed significantly to the forest recovery rate. Thus, this study aims at examining household perceptions of tree-planting for wood energy production for both in-house uses and for sale, and identify the factors influencing household perceptions of tree-planting. We employed the multinomial logit model to analyse the factors influencing household perceptions of tree-planting for energy. Our findings indicate that respondents considered the right/freedom to harvest trees from farms and transport them to markets as the most important factor (86%), followed by lack of awareness of tree-planting programmes (72%), and the existence of fuelwood for free from natural forests (59%). The size of the farm, education, distance to forest reserves, and age of the household head are found to have significant impact on the household perceptions of tree-planting for energy. Our results further show that woodfuel harvesting and enforcement systems do not exist in nearby forests. This situation is exacerbated by the absence of a specific policy formulated to match with the daily demand of forest produce for energy and income of households near forest reserves. Thus, we suggest policy makers to target policies and actions promoting tree-planting for energy

Linear or mixed integer programming in long-term energy systems modeling – A comparative analysis for a local expanding heating system

Most computer models used in energy systems optimization modeling studies are formulated usinglinear equations. However, since linear formulations do not always well reflect real-world conditions,they may not always be adequate as policy and support tools. This is particularly the case for localsystem studies attempting to represent technologies at the individual scale, as in the case for localheating system modeling. Thus, the aim of this paper is to investigate differences in the resultingheating solutions and model solution times for a local expanding heating system. Three differentinvestment cost structures for individual and district heating solutions for the heating of new housingare investigated using linear and mixed integer linear programming. The results show that the use ofdistrict heating is higher for the cost structures that use mixed integer linear programming than it isfor the linear cost structures. This result is attributed mainly to the fact that individual air-to-waterheat pumps benefit from the linear equation formulation due to its high coefficient of performanceduring summertime. This finding is important to consider when modeling local energy systems. Thesolution time is, however, significantly shorter for the linear formulations than for the mixed integerlinear formulations