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Keeping global warming from evolving into irreversible climate disaster requires immediate and sustained decarbonization of global energy systems. Of urgent priority are the energy systems in low- and middle-income countries (LMICs) where billions of people are projected to gain energy access in the next several decades. Therefore, leapfrogging traditional fossil fuel-based electricity production in favor renewable energy technologies is a critical issue area for sustainability. In the Democratic Republic of the Congo, political and economic challenges mean $44B in external investment is required to achieve its 2030 emissions reduction targets. Additionally, RETs are often more expensive. This study sought to generate, evaluate, and recommend possible national policies for the DRC government to implement to most effectively boost growth and investment in RETs. Financial incentives were identified as the policy type most practical for DRC. Modeling the resulting energy systems for policy pathways involving a 16% RET subsidy, a 70% fossil fuel tax, and both in combination relative to no-policy baseline scenarios, the scenarios including the tax had the lowest net costs and the highest proportion of RETs (above 90%). Additionally, despite current reliance on hydropower to fulfill 98% of its energy needs, hydropower plays a very minor role in all modeled scenarios. Finally, a post-modeling market potential assessment was performed on the technology that dominated off-grid supply across policy pathways: the 0.3 kW small solar home system (SHS). Based on learning rates for solar PV, demand for the small SHS system in DRC (>160 million units in total) was found to be sufficient to substantially reduce the unit cost as deployment scales. Putting results into context, emissions reductions for the policy pathways were higher than a past study focused on distributed RETs in DRC, and system costs were 15% higher than estimated in other analysis. These results provide a novel contribution to the literature by demonstrating how financial incentive policies can influence RET uptake in DRC specifically. Ultimately, this study yielded four policy recommendations for the DRC government: 1. Pursue financial incentives to catalyze DRC’s renewable energy supply 2. Tax fossil fuel energy production 3. Re-evaluate focus on hydropower 4. Promote DRC as a healthy market for solar home systems

Responding to the Paris agreement and climate change mitigation, Indonesia aims to reach Net Zero by 2060 or sooner. Due to Indonesia's dependence on coal and growing consumption, alternative sources of clean energy are imperative for meeting its rising energy needs and reducing energy-related greenhouse gas emissions to achieve the energy transition. This project aims to examine Indonesia's challenges, opportunities and potential to achieve low carbon ambition in the energy sector and identify alternative pathways for the energy transition in Indonesia. Cost-effective scenarios are developed by the Open Source Energy Modelling System (OSeMOSYS), providing comprehensive data analysis. OSeMOSYS is a least-cost model that enables long-term energy system modelling and its related intensive analysis. Indonesia energy data and OSeMOSYS input are obtained from an Indonesia starter data kit. In this study, a comparison of electricity generation, technology, investment, and carbon dioxide emissions is made between business-as-usual scenarios and model scenarios. The results show that NZ50 scenario is more cost-effective than others in meeting Indonesia's future energy demand at the lowest implementation cost. Although NZ50 and NZ60 are possible ways to reach carbon neutrality, NZ50 emits fewer CO2 emissions at a similar cost to NZ60. This paper's insights emphasise that large-scale renewable energy deployment and coal retirement are critical pathways to reaching carbon neutrality and achieving the energy mix transition.

Integration of alternative technological concepts such as switching to alternative fuels, advanced energy efficiency, and carbon capture and storage in existing industrial energy systems can prove highly effective at minimizing emissions; however, their adoption is low since solutions using these concepts raise costs considerably. The hypothesis of this work is a hierarchical combination of these concepts can reduce mitigation cost. To this end a mixed method approach is applied combining energy simulation with a novel Mixed Integer Linear Programming model developed to explore 48 alternative solutions to make industrial energy systems more sustainable. The method was applied to the most common industrial energy systems configurations. Results show that the added cost of integrating alternative technological concepts are lowered when energy efficiency via direct heat recovery is explored first in an optimization-based hierarchy of options. The hierarchy is advanced energy efficiency before fuel and technology switching or integrating carbon capture and storage. This means process integration can pay for steeper reductions in carbon emissions. Integrating alternative technological concepts optimally and hierarchically reduced emissions by 61%, and costs by 55.7% compared to a partial integration for a heat-only business-as-usual industrial energy systems. Even though switching to an alternative fuel (blue hydrogen) reduces carbon emissions by 72%, costs increase by at least 3% compared to a system using fuel gas and fuel oil. A hierarchical integration of blue hydrogen reduces cost by 47% and carbon emissions by 88.7%. Partial integration of carbon capture and storage reduces carbon emissions by 36% but costs increase by 89%, with full integration using optimization and the hierarchy costs only increase by 6.3%. Therefore, the cost-effectiveness of integrating alternative technological concepts is highly influenced by the hierarchy which seeks to minimize demand for energy from industrial processes first, then increase the supply efficiency of industrial energy systems, and before switching to alternative fuels and technologies.

This paper proposes a bottom-up method to estimate the technical capacity of solid oxide fuel cells to be installed in wastewater treatment plants and valorise the biogas obtained from the sludge through an efficient conversion into electricity and heat. The methodology uses stochastic optimisation on 200 biogas profile scenarios generated from industrial data and envisages a Pareto approach for an a posteriori assessment of the optimal number of generation unit for the most representative plant configuration sizes. The method ensures that the dominant role of biogas fluctuation is included in the market potential and guarantees that the utilization factor of the modules remains higher than 70% to justify the investment costs. Results show that the market potential for solid oxide fuel cells across Europe would lead up to 1,300 MW of installed electric capacity in the niche market of wastewater treatment and could initiate a capital and fixed costs reduction which could make the technology comparable with alternative combined heat and power solutions.

Waste heat exploitation improves the energy efficiency of process sites, ensuring lower costs and lower CO2 emissions. Technologies such as organic Rankine cycles, absorption chillers, mechanical heat pumps, absorption heat transformers and absorption heat pumps exist to utilize waste heat. Though these technologies make waste heat re-use technically feasible, selection of technologies based on different heat source temperatures still needs to be addressed. In this work, a novel screening approach is proposed to compare technologies considering the waste heat source quality. A methodology is also presented to select technologies for a process site based on the screening results. Since multiple energy form interactions occur, the screening criterion considers the deviation of the actual performance from the ideal performance of technology options, taking into account irreversibilities as a result of finite temperature heat transfer. The tool is applied to screen and select technologies for waste heat sources below 265 °C. Results identify the temperature ranges where technologies have minimum exergy degradation. The framework systematically matches heat source temperatures with technology options compared to a trial and error approach. The framework was applied to an industrial case study to recover 45,660 kW of useful energy from the available waste heat.

In the last couple of years there has been increasing recognition by key players in the European gas industry that to mitigate the risk of terminal decline in the context of a decarbonising energy system, there will need to be rapid scale up of decarbonised gas. This has led to several projections of the scale of decarbonised gas which could potentially be supplied by 2030, 2040 or 2050. This paper, joint with the Sustainable Gas Institute at Imperial College, London, considers the very significant rate of scale up and the significant cost reductions contemplated by such projections. Based on a database of actual announced projects (both committed and in earlier stages of development) for production of decarbonised gas, it then considers the extent to which project activity is consistent with meeting the ambitious projections. It identifies a significant gap in current levels of activity, largely because there is not yet sufficient economic incentive for investors to develop the required projects. It is intended that this paper will form the basis of continued tracking of the level of activity over the coming years, to help inform industry players of further actions which may be required.

Thermodynamic cycles such as organic Rankine cycles, absorption chillers, absorption heat pumps, absorption heat transformers, and mechanical heat pumps are able to utilize wasted thermal energy in process sites for the generation of electrical power, chilling and heat at a higher temperature. In this work, a novel systematic framework is presented for optimal integration of these technologies in process sites. The framework is also used to assess the best design approach for integrating waste heat recovery technologies in process sites, i.e. stand-alone integration or a systems-oriented integration. The developed framework allows for: (1) selection of one or more waste heat sources (taking into account the temperatures and thermal energy content), (2) selection of one or more technology options and working fluids, (3) selection of end-uses of recovered energy, (4) exploitation of interactions with the existing site utility system and (5) the potential for heat recovery via heat exchange is also explored. The methodology is applied to an industrial case study. Results indicate a systems-oriented design approach reduces waste heat by 24%; fuel consumption by 54% and CO2 emissions by 53% with a 2 year payback, and stand-alone design approach reduces waste heat by 12%; fuel consumption by 29% and CO2 emissions by 20.5% with a 4 year payback. Therefore, benefits from waste heat utilization increase when interactions between the existing site utility system and the waste heat recovery technologies are explored simultaneously. The case study also shows that the novel methodology can select and design optimal solutions for waste heat exploitation which are technically, economically and environmentally feasible from a range of technology options, heat sources and end-uses of recovered energy.

Technologies such as mechanical heat pumps, absorption heat pumps and absorption heat transformers allow low-temperature waste heat to be upgraded to higher temperatures. This work develops a comprehensive Mixed Integer Linear Program (MILP) to integrate such technologies into existing process sites. The framework considers interactions with the associated cogeneration system (in order to exploit end-uses of upgraded heat within the system and determine their true value), temperature and quantity of waste heat sources and of sinks for the heat upgraded as well as process economics and the potential to reduce carbon dioxide (CO2) emissions. The methodology is applied to an industrially relevant case study. Integration of heat upgrading technologies has potential to reduce total costs by 23%. Sensitivity analysis is also performed to illustrate the effect of changing capital costs and energy prices on the results, and demonstrate the model functionality.

The need for high efficiency energy systems is of vital importance, due to depleting reserves of fossil fuels and increasing environmental problems. Industrial operations commonly feature the problem of rejecting large quantities of low-grade waste heat to the environment. The aim of this work is to develop methods for the conceptual screening and incorporation of low-temperature heat upgrading technologies in process sites. The screening process involves determination of the best technology to upgrade waste heat in process sites, and the combination of waste heat source and sink temperatures for a technology. Novel simplified models of mechanical heat pumps, absorption heat pumps and absorption heat transformers are proposed to support this analysis. These models predict the ratio of the real performance to the ideal performance in a more accurate way, than previous simplified models, taking into account the effect of changing operating temperatures, working fluids non-ideal behaviour and the system component inefficiencies. A novel systems-oriented criterion is also proposed for conceptual screening and selection of heat pumps in process sites. The criterion (i.e. the primary fuel recovery ratio) measures the savings in primary fuel from heat upgraded, taking into account power required to drive mechanical heat pumps and missed opportunities for steam generation when absorption systems are used. A graphical based methodology is also developed for applying the PRR in process sites and applied to a medium scale petroleum refinery. Results show that applying the PRR yields 9.2% additional savings in primary fuel compared to using the coefficient of performance to screen and incorporate heat pumps.

Coupling the electricity and heat sectors is receiving interest as a potential source of flexibility to help absorb surplus renewable electricity. The flexibility afforded by power-to-heat systems in dwellings has yet to be quantified in terms of time, energy and costs, and especially in cases where homeowners are heterogeneous prosumers. Flexibility quantification whilst accounting for prosumer heterogeneity is non-trivial. Therefore in this work a novel two-step optimization framework is proposed to quantify the potential of prosumers to absorb surplus renewable electricity through the integration of air source heat pumps and thermal energy storage. The first step is formulated as a multi-period mixed integer linear programming problem to determine the optimal energy system, and the quantity of surplus electricity absorbed. The second step is formulated as a linear programming problem to determine the price a prosumer will accept for absorbing surplus electricity, and thus the number of active prosumers in the market. A case study of 445 prosumers is presented to illustrate the approach. Results show that the number of active prosumers is affected by the quantity of absorbed electricity, frequency of requests, the price offered by aggregators and how prosumers determine the acceptable value of flexibility provided. This study is a step towards reducing the need for renewable curtailment and increasing pricing transparency in relation to demand-side response.

This paper presents a ranking criterion for evaluating opportunities that utilize recovered energy from the available waste heat in process sites. The ranking criterion takes into account the energy performance of waste heat recovery technologies associated with each opportunity, their potential to reduce greenhouse gas emissions (namely CO2) and the economics (costs and benefits). Mathematical modelling of the opportunities using the ranking criterion is developed to allow for systematic evaluation of opportunities, for example within an optimization framework. A methodology using the ranking criterion to design site waste heat recovery systems is also proposed. The methodology is applied to a case study of a petroleum refinery. Hierarchy and performance of waste heat utilization opportunities depends on the temperature of the heat available, amongst other factors. The site operating cost and CO2 emissions reduce by 26% and 18% respectively when opportunities to use the recovered energy from waste heat within and outside the process site boundaries are explored. Sensitivity of the ranking to energy prices is studied, to explore the outlook for waste heat utilization in the future. The methodology can be applied to the process industries and other facilities producing waste heat.

Wastewater treatment plants (WWTP) are one of the most energy intensive public utilities. The valorization of the biogas produced from the sludge in combined heat and power (CHP) systems allows important energy and emissions reduction, particularly if highly efficient engines, like solid-oxide fuel cells (SOFCs) are used. This paper proposes a two-stage stochastic optimization approach to assess the market potential for SOFCs in WWTPs in Europe. Despite the biogas availability is a challenge to guarantee continuity of operation, the results show that the WWTP is a promising market to pave the way for SOFC cost reduction and further technological learning.

In this paper a novel multi-period MILP model is developed, and applied to show how: (1) integrating thermal energy storage with ASHP (i.e. power to heat storage) reduces the ASHP peak and total electricity demand by 78.2 % and 8.4 % respectively, and (2) proper sizing of the ASHP reduced its total electricity demand by 35%. The accuracy of the model is improved by using fewer time slices to capture technology and energy demand characteristics. Storage size and operation are determined based on the energy demand and economic price signals.