• Energy Research

AbstractThe structural integrity of offshore wind turbine (OWT) support structures is affected by one of the most severe damage mechanisms known as pitting corrosion‐fatigue. In this study, the structural reliability of such structures subjected to pitting corrosion‐fatigue is assessed using a damage tolerance modelling approach. A probabilistic model that ascertains the reliability of the structure is presented, incorporating the randomness in cyclic load and corrosive environment as well as uncertainties in shape factor, pit size and aspect ratio. A non‐intrusive formulation is proposed consisting of a sequence of steps. First, a stochastic parametric Finite Element Analysis (FEA) is performed using SMART© crack growth and Design Xplorer© facilities within the software package ANSYS. Secondly, the results obtained from the FEA are processed using an Artificial Neural Network (ANN) response surface modelling technique. Finally, the First Order Reliability Method (FORM) is used to calculate the reliability indices of components. The results reveal that for the inherent stochastic conditions, the structure becomes unsafe after the 18th year, before the attainment of the design life of 20 years. The FEA results are in very good agreement with results obtained from analysis steps outlined in design standard BS 7910 and other references designated as ‘theoretical analysis methods’ in this study. The results predict, for the case study, that the pit growth life is approximately 56% of the total pitting corrosion fatigue life. Sensitivity analysis results show that the aspect ratio of pits at critical size plays a significant role on the reliability of the structure.

Abstract A growing literature highlights the presence of spatial differences in solar photovoltaic (PV) adoption patterns. Central to forward planning is an understanding of what affects PV growth, yet insights into the determinants of PV adoption in the literature are limited. What factors do drive the adoption at local level? Are the effects of these factors geographically uniform or are there nuances? What is the nature of these nuances? Existing studies so far use aggregate macro datasets with limited ability to capture the role of peer effects. This paper considers some established variables but also broadens the base of variables to try to identify new indicators relating to PV adoption. Specifically, it analyses domestic PV adoption in the UK at local level using data on the number of charities as a proxy to capture the opportunities to initiate social interactions and peer effects. A geographically weighted regression model that considers the spatially varying relationship between PV adoption and socio-economic explanatory variables reveals significantly more variability than the global regression. Our results show that charities and self-employment positively influence PV uptake while other socio-economic variables such as population density has bidirectional impacts.

Private investments are critical enablers to achieving energy access for over 770 million people worldwide. Despite decreasing capital costs, investments in renewable energy (RE) projects in developing countries are low due to unattractive risk-return profiles. Through understanding key risks drivers and their interactions, actionable insights can be drawn to mitigate investment risks, making energy more accessible. This paper reviews RE risks and methods used for risk assessment and mitigation for developed and developing countries with a focus on Sub-Saharan Africa countries (SSA). The review finds that while risk analysis and evaluation mainly employed semi-quantitative multicriteria decision analysis (MCDA) and system dynamics (SD) methods for developing countries, qualitative methods were used to identify mitigations. The methods assessed technical and economic risks at a minimum, while MCDA and SD methods can assess social, political, and policy risks. The efficacies of mitigations were tested using SD and quantitative methods such as agent-based modelling and Monte Carlo simulation. The paper further introduces a ‘holistic multi-dimensional investor risk management framework’ which can be used to identify actions to improve investment risks in a structured manner. The framework addresses four fundamental limitations observed in the existing literature, recognising that RE risks are complex and involve multidisciplinary perspectives having interactions and feedbacks with other risks, actors, and their actions. This review provides a valuable reference to investors, policymakers, and researchers, providing a catalogue of risks, methods deployed in literature, including a framework to identify impactful actions to improve risk levels.

Abstract During a period of transition towards decarbonised energy networks, maintaining a reliable and secure energy supply whilst increasing efficiency and reducing cost will be key aims for all energy supply chain (ESC) networks. Renewable energy sources, such as biomass, will play an important role in future ESCs as climate change mitigation becomes an increasingly important priority. This paper seeks to address these requirements by presenting an optimisation model for the design and planning of biomass integration into the ESC networks. A supply chain model was derived and the governing equations were solved using the General Algebraic Modelling System software (GAMS) to achieve an optimal solution. The results of the study indicate that a reduction in the emissions cost of up to 4.32% is achievable on integration of 5–8% of biomass into the ESC network. However, a 4.57% increase in the total cost of the ESC network was recorded at the biomass fraction in the mixed fuel of 7.9%, with the fixed assets cost having the largest impact on the total cost of the ESC network. It has been shown that the cost increment in the assets and operational costs of a biomass and coal co-fired combined heat and power plant can be offset by the cost reductions obtained from reduced carbon dioxide emissions. Economic arguments for dual-fuel plants, therefore, require the introduction of effective carbon pricing legislation. It is concluded that such policy implementations can be effective at mitigating the effects of climate change and would assist in achieving a global carbon neutral economy.

The lifetime of offshore foundations is governed by a combination of harsh environmental conditions and complex service loads. The fatigue limit state (FLS) analysis needs to be performed in the time domain to capture the complex phenomenon. This study aims to investigate different parameters and design modifications that can impact the design life of an offshore jacket foundation. An OC4 jacket foundation is designed in industrial software from DNV and reduced to a super-element model. The super-element model is connected to an NREL 5-MW wind turbine designed in Bladed. The time-series loads are used to compute the fatigue damages faced by the foundation during the service life. The impact of soil non-linearity, marine growth, scour size, the mass of the transition piece, and the grouted connection’s design on the dynamic response and fatigue damages are compared. A 30% increase in life was observed by replacing the concrete transition piece with a lightweight steel configuration. The fatigue damages were considerably greater for the inclined pile in the leg grouted connection than for the leg in the pile concept. The study provides a different perspective by analysing the effect of design parameters and design changes in the complex and computationally expensive time-series domain.

Abstract Since buildings account for more than one-third of final energy use, it is important to integrate renewable energy sources for new housing developments to reduce demand for grid energy and carbon emissions. This research investigates the potential of solar PV, energy storage, and electric vehicles in new housing developments and their associated grid impacts by taking the UK’s Cambridge, Milton Keynes, Oxford arc as a case study. Using published data on electrical loads for different types of dwellings, energy demands for new housing developments with and without renewable and low carbon technologies are analysed using techno-economic modelling frameworks. Technical analysis includes sizing and optimisation of PV and storage while economic analysis covers cost-benefit analyses, by considering a range of existing and future tariffs and subsidy schemes including Standard, Economy 7 (cheaper electricity for 7 h at night), Feed-in tariff, and the Smart Export Guarantee. Results show that installing PV panels and storage systems not only reduces the dwellings’ grid energy demand by 31% in January but also helps the dwellings to become net exporters of green electricity to the grid in July and hence saves a substantial amount of money by taking advantage of Feed-in and Economy 7 tariffs.

This research paper aims to propose a through-life cost analysis model for estimating the profitability of renewable concentrated solar power (CSP) technologies. The financial outputs of the model include net present value (NPV) and benefit-cost ratio (BCR) of the project, internal rate of return (IRR) and discounted payback period (DPBP) of the investment, and levelized cost of energy (LCoE) from the CSP technology. The meteorological data for a specific location in the city of Tucson in Arizona is collected from a network of automated weather stations, and the NREL System Advisor Model (SAM) is applied to simulate hourly energy output of the CSP plant. An Excel spreadsheet tool is designed to calculate, in a bottom-up approach, the financial metrics required for approval of CSP projects. The model is tested on a 50 MW parabolic trough CSP plant and the results show an annual energy production of 456,351,232 kWh, NPV of over $64 million and LCoE of 0.16 $/kWh. Finally, a sensitivity analysis is performed to identify the factors which have the most significant effect on the economic performance of CSP technologies. The proposed model can provide valuable guidance to support the strategic planning and investment decision-making in CSP projects.