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This book provides an in-depth study of the management of standards and regulation in sustainable and radical innovation development. It considers the case of micro Combined Heat and Power (mCHP) technology. The developers of this radical innovation in the European heating sector encountered major conflicts when attempting to create or adapt standards when bringing the technology to market. Utilising rich research data and interviews with key actors, the author uses this case to derive a grounded theory on the management of standards and regulation during an innovation process. The results also have important implications for innovators, which are reflected in clear advice for practice.

This manuscript proposes elephant clan optimization (ECO) to address heat and electric power scheduling in remote microgrids (MGs) under three distinct scenarios, considering fuel constraints. ECO is a population‐based approach influenced by the behavior and social structure of elephants. The MG consists of wind turbine generators (WTGs), biomass‐fuel‐fired micro‐cogeneration (BMC) units, diesel generators (DGs), battery energy storage systems (BESS), solar micro‐cogeneration (SMC) units, and plug‐in electric vehicles (PEVs). BMC units and SMC units are alternately integrated into the MG. Numerical results of a standard system are contrasted with those derived from a hierarchical particle swarm optimizer with time‐varying acceleration coefficients (HPSO‐TVAC), as well as gray wolf optimization (GWO). The analysis demonstrates that ECO offers an improved solution. This manuscript proposes ECO (elephant clan optimization) to address heat and electric power scheduling in remote MG (microgrids) under three distinct scenarios, considering fuel constraints. ECO is a population‐based approach influenced by the behavior and social structure of elephants. The microgrid (MG) constitutes WTGs (wind turbine generators), BMC (biomass‐fuel‐fired micro‐cogeneration) units, DGs (diesel generators), BESS (battery energy storage systems), SMC (solar micro‐cogeneration) units, and PEVs (plug‐in electric vehicles). BMC units and SMC units are alternately integrated into MG. Numerical results of a standard system contrasted with those derived from HPSO‐TVAC (hierarchical particle swarm optimizer with time‐varying acceleration coefficients) as well as GWO (gray wolf optimization). The analysis demonstrates ECO offers an improved solution.

In this research, the simulation of an existing 31.5 MW steam power plant, providing both electricity for the national grid and hot utility for the related sugar factory, was performed by means of ProSimPlus® v. 3.7.6. The purpose of this study is to analyze the steam turbine operating parameters by means of the exergy concept with a pinch-based technique in order to assess the overall energy performance and losses that occur in the power plant. The combined pinch and exergy analysis (CPEA) initially focuses on the depiction of the hot and cold composite curves (HCCCs) of the steam cycle to evaluate the energy and exergy requirements. Based on the minimal approach temperature difference (∆Tlm) required for effective heat transfer, the exergy loss that raises the heat demand (heat duty) for power generation can be quantitatively assessed. The exergy composite curves focus on the potential for fuel saving throughout the cycle with respect to three possible operating modes and evaluates opportunities for heat pumping in the process. Well-established tools, such as balanced exergy composite curves, are used to visualize exergy losses in each process unit and utility heat exchangers. The outcome of the combined exergy–pinch analysis reveals that energy savings of up to 83.44 MW may be realized by lowering exergy destruction in the cogeneration plant according to the operating scenario.

The current global context, marked by crises such as climate change, the pandemic, and the depletion of fossil fuel resources, underscores the urgent need to minimize waste. Cogeneration technology, which enables simultaneous production of electricity and thermal energy from electricity generation waste, offers a promising solution to enhance energy efficiency. Its widespread adoption, particularly in the European Union, where several cogeneration systems are in place, demonstrates its growing popularity. Italy alone has 1865 high-efficiency cogeneration units, contributing significantly to total cogeneration energy generation. Micro-cogeneration, specifically, has attracted attention for its potential to reduce energy waste and environmental impact. This study focuses on assessing the technical and financial feasibility of a micro-cogeneration plant using natural gas-fuelled internal combustion engines, considering different scenarios of plant operating strategies in order to optimize energy production, minimize waste, and mitigate environmental footprints associated with conventional methods. Additionally, it provides valuable guidance for policymakers, industry stakeholders, and decision-makers invested in sustainable energy solutions. By advancing micro-cogeneration technology, this study aims to promote a more sustainable and environmentally conscious approach to energy production. The methodology applied is based on the development of a numerical model via RETScreen Expert 8 and it was calibrated with one-year energy bills. The study was performed by focusing on the analysis of the annual energy savings, greenhouse gas emission savings, tonnes of oil equivalents savings, and financial parameters such as Net Present Value (NPV), Internal Rate of Return (IRR), Profitability Index (PI) and Payback time (PBT). The results show, using a micro-cogeneration system in a big complex of buildings, that the financial parameters can continually increase with the plant’s capacity with the electrical load following, but with a loss of the recovered heat from the cogenerator because it may reach values that are not necessary for the users. When the thermal load variation is much more significant than the electrical load variation, it will be useful to design the plant to follow the thermal load variation which allows the full utilization of the thermal and energy production from the plant without any waste energy and choosing a system capacity that can optimize the energy, emissions and financial aspects.

The subseasonal-to-seasonal (S2S) predictive time scale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this time scale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a “knowledge—value” gap, where a lack of evidence and awareness of the potential socioeconomic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development—demonstrating both skill and utility across sectors—this dialogue can be used to help promote and accelerate the awareness, value, and cogeneration of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable, and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting time scale.

Nuclear cogeneration to produce electricity and process heat for nonelectric applications such as desalination, district heating or cooling or hydrogen production can play an important role in reducing dependence on fossil fuels. The implementation of nuclear cogeneration projects is inherently complex and such projects require a clear understanding of actions and responsibilities during the design, operation and management phases. This publication focuses on analysing the requirements and responsibilities of users and vendors and correspondence between them through the life cycle to of a nuclear cogeneration project, highlighting experience and lessons learned from retrofit and new build projects.