Gloria V Odo

Clustering historical electricity consumption data is very important for creating representative demand profiles for the planning and operation of the power grids. This paper investigates a multi-dimensional framework for data clustering, which takes scattering and separation metrics, as well as the number of clusters into account. A combination of wavelet mutation with the Invasive Weed Optimization (IWO) method for clustering features is proposed. One notable advantage of the IWO method over other metaheuristic optimization algorithms is its ability to dynamically adapt the number of weed colonies during the search process, resulting in improved exploration and exploitation of the search space. The proposed strategy is applied to cluster the electricity consumption data from a large municipal government center in Perth, Western Australia. The suggested method is then evaluated by comparing it with the well-known method in the literature, namely, the k-means technique. After the data clustering, the obtained results are implemented in the design of a multi-microgrid system under two different scenarios of cooperative and noncooperative modes. To evaluate the performance of the proposed method, the proposed method is implemented on the operational planning of a real multi-microgrid distribution system in Western Australia using linear programming to take the advantage of the mathematical-based solvers. After performing some investigations, the cooperative mechanism, where the microgrids have participated in supplying the demand of microgrids was found to yield to greater operational and investment cost minimimzation. In terms of numerical comparison, the total cost in the cooperative model is 6.5% lower than that in a non-cooperative situation.

The clustering of historical electricity consumption data is an effective means of developing representative load profiles for long-term energy planning. This paper presents a multi-dimensional approach for clustering, considering scattering and separation metrics and the number of clusters. A novel hybrid approach to solve the clustering function is also proposed: a combination of Invasive Weed Optimization (IWO) and wavelet mutation strategy. The hybrid method is applied to half-hourly metered electricity consumption data from the Civic Centre of a large local (municipal) government in Perth, Western Australia, to create representative seasonal load profiles. The novel clustering approach is then tested against the well-known k-means method using Davies-Bouldin and silhouette indices. In each seasonal clustered profile, the hybrid method is found to outperform the k-means method. The hybrid method has been identified as an effective clustering approach for analyzing the behavior of loads and assisting the identification of suitable energy efficiency initiatives.

Energy is a key enabler in achieving the Sustainable Development Goals (SDGs) as energy plays the pivotal role in ending poverty and hunger, providing healthcare, education, and water, as well as sustaining economic growth and protecting the environment. Consequently, since the SDGs are executable only at local and national levels, mainstreaming the SDGs into local/national development planning will put pressure on the country’s energy sector. Considering the broad scope of the SDGs, countries will prioritize different SDG targets based on their urgencies, resources, and capabilities. However, energy linkages with the SDGs and their targets are complex, with direct and indirect connections, synergies, and trade-offs. More importantly, there is a lack of capacity among policymakers to be able to develop an SDGs-responsive energy plan, as there is no guidance on how the impact of linkages can be translated into local/national energy planning. This study aims to examine the complexity of the interconnections between energy and the SDGs, as well as give examples of how these linkages can be quantified. Twenty-five SDG targets with direct links to energy are identified in this study, and a map of the multidimensional interaction between them are presented. The study also provides examples of quantification of the targets/indicators into their energy requirements. The results of the study will help energy planners and policymakers forecast energy demand more accurately for energy planning and policies under the SDGs regime.

This research presents the development of an optimal biogas system design model (OBSDM), which determines the most suitable biogas system design based on the context and priorities of the intended user(s) in the region of Sub-Saharan Africa (SSA). The model can be used as a decision-making tool, assisting biogas installers, program implementers, and other stakeholders in the biogas industry to carry out initial assessments on the type of biogas systems that are optimal for specific applications, particularly at the household-scale. To determine the optimal biogas system design, the model assesses the feasibility of different types of biogas system designs and sizes based on user-defined inputs, including energy and fertiliser requirements, feedstock (type, amount, and rate of supply), water supply, land use (area, soil type, groundwater level), and climate (ambient temperatures). The feasible biogas system designs and sizes are then compared and ranked based on the priorities of the intended user(s). These priorities are defined in the input through rating eight sustainability criteria related to biogas technology – reliability, robustness, simple operation & construction, lowcost, technical efficiency, environmentally benign, local materials and labour, and save time – according to their importance to the intended user. The output of the model provides a recommended biogas system design and size with estimates of expected costs, energy and fertiliser production, and links to contact the supplier. To develop the OBSDM, literature reviews were carried out on the types of biogas system designs applicable to SSA, specifically at the household-scale; the types of feedstocks available in the region; and, the tools and models that currently exist for biogas technology. Part of this literature review was used to help assess the energy production potential of different types of feedstocks that could be used in biogas systems in SSA. Databases on available digester types, sizes, and feedstocks were also developed for the model. The OBSDM was created in Microsoft Excel using Visual Basic for Applications (VBA) programming, and is recommended to be made freely accessible. It has been tested by applying household survey data from Kenya and Cameroon, as well as a detailed study of household biogas systems in the central and eastern districts of Rwanda. The outcomes from this analysis indicated that the model is able to recommend biogas system designs that are appropriate to the context and priorities of the intended user. However, the accuracy of the model outputs is highly dependent on the accuracy of the inputs. Through the Kenyan, Cameroonian, and Rwandan case studies, it is apparent that future development of biogas technologies in the region should focus on systems that require minimal water, and can be constructed from less expensive and energy intensive, local materials. Overall, this research aims to help increase biogas dissemination in the region through raising awareness about its potential, as well as encouraging industry stakeholders to make appropriate design choices that will ensure long-term sustainability of the biogas system and maximum benefits to the intended user(s).

The optimal biogas system design model (OBSDM) described in this paper is intended to be used as a decision-making tool to increase awareness of the potential of biogas technology for different applications in Sub-Saharan Africa (SSA). The decision-making tool identifies the most suitable biodigester design based on user defined inputs, including energy and fertiliser requirements; feedstock (type, amount, and rate of supply); water supply; land use (area, soil type, ground water level); climate (temperature and rainfall); construction materials available locally; and the priorities (based on sustainability criteria) of the intended biogas user. The output of the model provides a recommended design with estimates of the expected costs, energy and fertiliser production, and links to contact biodigester suppliers. In order to test the model, data from household surveys conducted in rural regions of Kenya and Cameroon were used as inputs to the model. An innovative fixed dome biodigester design, which uses stabilised soil blocks instead of bricks, was identified as optimal for both Kenyan and Cameroonian rural households. The expected performance of the optimal biogas system design from the model output was consistent with survey data on existing biogas systems in the region.

Optimising voltage levels to a controlled stable level at a facility can not only reduce the cost of energy but also enhance equipment performance, prolong equipment life, reduce maintenance costs and reduce greenhouse gas emissions. Voltage optimisation (VO) technology has been widely used in a number of different industries locally and internationally, but not to a large extent within the red meat processing sector in Australia. To determine whether VO technology can be implemented, and whether it is technically and economically viable for red meat processing sites, this study investigated, through case study analyses, the potential effectiveness of VO technology in Australian abattoirs. Through an extensive literature survey, the study initially explored the need and considerations of deploying VO technologies at a typical red meat processing plant. To determine the advantages of using VO technology the study then performed site analyses to investigate power quality (PQ) issues, such as voltage regulation, harmonics and power factor, at two typical medium-sized abattoirs, one in Western Australia and another in Queensland. Finally, an economic assessment of the use of VO in the red meat processing industry was undertaken to identify the potential electricity savings and payback periods. From the case study analyses, it is evident that power quality issues, such as under voltage, overvoltage, and harmonic distortion, can be reduced and significant energy savings can be achieved with the optimum selection of VO technology and voltage level. The outcomes of this study will enable engineering and operations staff to be better informed about the economic and technical benefits of (and possible issues with) using VO technologies in an abattoir.

Biogas technology has been recognised as a suitable technology for improving energy access, waste management, and sanitation in Sub-Saharan Africa (SSA). Uptake of the technology in the region has been sporadic and currently dissemination programmes are limited to five countries. The main barriers hindering larger dissemination include high installation costs, inadequate user training, insufficient servicing, and inappropriate designs. Poor design choices, mainly due to overlooking the user energy needs and local conditions, contribute to the short lifespan of many installed biogas systems. This research aims to address the gap in appropriate designs of biogas systems through the development of a model that identifies optimal designs for particular applications in SSA based on user defined priorities of sustainability criteria. TOPSIS, a multi-criteria decision making method is used in the model to identify the optimal system based on the priority rating of the criteria and the designs that are feasible according to the main parameters. The model was applied to a typical Kenyan household where a 9 m3 modified CAMARTEC solid state digester was identified as the optimal biogas system.

This paper aims to provide a broad review and assessment of the feedstocks and applicable biogas technologies that are feasible in Sub-Saharan Africa (SSA). Biodigesters and feedstocks available in SSA were identified according to scale and application – household, community, institutional, and commercial. Aside from livestock manure, suitable feedstocks for household, community, and institutional biodigesters include crop residues, night soil/domestic sewage, and the organic fraction of municipal solid waste (OFMSW). Significant untapped feedstocks exist from SSA agro-processing and food production industries. Biodigesters available in SSA for household, community, and institutional installations include variations of fixed dome, plug flow, and floating cover digesters. Commercial digester designs applicable to the region include continuously stirred tank reactors and fixed film digesters. The key factors that need to be considered in selecting suitable biodigester designs for specific applications include: feedstock availability, water supply, energy demand, local materials and labour, and the level of commitment to operate and maintain the biodigester effectively.

Biogas technology has the potential to provide benefits to three priority areas in Sub-Saharan Africa (SSA): energy supply, sanitation, and food security. Despite this, uptake of biogas systems has been slow and sporadic in the region. This review paper investigates what has prevented widespread dissemination of the technology in SSA by looking at the key barriers in the region, as well as identifying the main opportunities and the lessons that can be learned from successful biogas dissemination experiences in Rwanda, Tanzania, China, India, and Nepal. Installation costs, limited awareness and training for biogas users and insufficient follow-up services were recognised as being among the key barriers. SSA has favourable conditions for biogas technology, namely a suitable tropical climate in most parts of the region, a dominance of agricultural activities, and interest in alternatives to expensive conventional energy services. The region's favourable conditions therefore provide opportunities for increasing uptake of the technology. Experiences in other regions highlighted the importance of the government in supporting the biogas sector through suitable policies and incentives. Collaboration between research institutions, governmental departments, and biogas users, both current and future, was also recognised as being vital to improve the technology's dissemination and appropriate, long-term use.

This paper presents a broad assessment of the energy production potential available from solid organic wastes when treated with anaerobic digestion in Sub-Saharan Africa (SSA). Energy production potentials were estimated by calculating the methane (CH4) production potential based on data from the Food and Agricultural Organization (FAO), studies done in urban centres on the organic fraction of municipal solid waste (OFMSW), livestock manure, livestock food waste, crop residues normally burned, and crop primary equivalent waste. The total CH4 production potential of organic solid wastes in SSA was estimated to be 12.8 billion m3/yr, equivalent to 133 million GWh/yr of heat energy. Given that current domestic biogas programmes in SSA focus on cattle manure as the main feedstock, the large energy production potential from other organic waste streams highlights the opportunity to improve waste management practices through harnessing these abundant waste resources in biogas systems.