Generation Portfolio Research Articles

Impact Assessment of Green Port Practices on the Triple Bottom Line of Sustainability: The Case of South Asia Pakistan Terminals (SAPT)

The sustainable operation of ports plays an important and valuable role in achieving overall product reach and logistics. Sustainable port operations ensure production efficiency, profitable business growth and increase customer satisfaction. In developing countries, these practices are neglected and not widely recognized in the literature. The inadequate implementation of these practices in SAPT contributes significantly to greenhouse gas (GHG) emissions, creating problems for the environment and climate change. Therefore, this study examines the implementation of green port practices and answers the question of how these practices contribute to the environmental problems at South Asian Pakistan Terminals (SAPT) and recommends specific practices to transform SAPT into a green terminal. This study is based on a quantitative approach for which data was collected from 172 respondents using a questionnaire on a five-point Likert scale through random sampling. Respondents were selected based on their qualifications, experience and knowledge of green port practices. The model was analyzed using PLS-SEM via Smart PLS 4. PLS-SEM was chosen as the data analysis technique as it can handle complex models in a single trial and provides more generalized results. The results showed that IEM positively and significantly affects GO (p<0.05, β=0.356) and ED (p<0.05, β=0.277). Similarly, ED influences GO (p<0.05, β=0.305), while GO influences ENVIROPER (p<0.05, β=0.398), followed by ECONOPER (p<0.05, β=0.303) and SP (p<0.05, β=0.276). The results imply that Karachi Port Trust (KPT) and Hutchisons Port Holding (HPH) need to address the best practices of green ports in SAPT such as diversification of power generation portfolio, installation of electric Rubber-Tired Gantry (RTG) cranes and electric Internal Transfer Vehicle (ITV) around the port and consideration of Scope III emissions in the value chain of SAPT for sustainable growth and development. The results identify ways to improve the port's sustainability by implementing Green Port Practices (GPPs) that are best suited for SAPT. This study makes a novel contribution to the implementation and achievement of sustainable port performance in the context of developing countries. In the future, other practices such as green purchasing, investment recovery and supplier audits can be operationalized to expand the study.

A Method for Calculating the Optimal Size of Energy Storage for a GENCO

Market liberalization and the growth of renewable energy sources have enabled the rise of generation companies (GENCOs) managing diverse generation portfolios, creating a dynamic market environment that necessitates innovative energy management strategies to enhance operational efficiency and economic viability. Investing in the energy storage system (ESS), which, in addition to participating in the energy and ancillary services markets and in joint operations with other GENCO facilities, can mitigate the fluctuation level from renewables and increase profits. Besides the optimal operation and bidding strategy, determining the optimal size of the ESS aligned with the GENCO’s requirements is significant for its market success. The purpose of the ESS impacts both the sizing criteria and the sizing techniques. The proposed sizing method of ESS for a GENCO daily operation mode is based on the developed optimization operation model of GENCO with utility-scale energy storage and a cost-benefit analysis. A GENCO operates in a market-oriented power system with possible penalties for undelivered energy. The proposed method considers various stochastic phenomena; therefore, the optimization calculations analyze the GENCO operation over a long period to involve multiple potential combinations of uncertainties. Numerical results validate the competencies of the presented optimization model despite many unpredictable parameters. The results showed that both the battery storage system and the pumped storage hydropower plant yield a higher net income for a specific GENCO with a mixed portfolio, regardless of the penalty clause. Considering the investment costs, the optimal sizes for both types of ESS were obtained.

An integrated binary metaheuristic approach in dynamic unit commitment and economic emission dispatch for hybrid energy systems

The current generation portfolio is obligated to incorporate zero-emissions energy sources, predominantly wind and solar, due to the depletion of fossil fuels and the alarming rate of global warming. In the current scenario, power engineers must devise a compromised solution that not only advocates for the adoption of renewable energy sources (RES) but also efficiently schedules all conventional power generation units to balance the increasing load demand while simultaneously minimizing fuel costs and harmful emissions that are currently addressed by Unit Commitment (UC) and Combined Economic Emission Dispatch (CEED) problem solutions. However, the integration of renewable energy resources (RES) further complicates the UC-CEED problem due to their intermittent nature. Recently, metaheuristic algorithms are acquiring momentum in resolving constrained UC-CEED problems due to their improved global solution ability, adaptability, and derivative-free construction. In this research, a computationally efficient binary hybrid version of crow search algorithm and improvised grey wolf optimization is proposed, namely Crow Search Improved Binary Grey Wolf Optimization Algorithm (CS-BIGWO) by inclusion of nonlinear control parameter, weight-based position updating, and mutation approach. Statistical results on standard mathematical functions prove the supremacy of the proposed algorithm over conventional algorithms. Further, a novel optimization strategy is devised by integrating enhanced lambda iteration with the CS-BIGWO algorithm (CS-BIGWO-λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}) to solve a day-ahead UC-CEED problem of the hybrid energy system incorporating cost functions of RES. For the model, a day-ahead forecast of wind power and solar photovoltaic power is obtained by using the Levy-Flight Chaotic Whale Optimization Algorithm optimized Extreme Learning Machines(LCWOA-ELM). The proposed algorithm is tested for the UC-CEED solution of an IEEE-39 bus system with two distinct cases: (1) without RES integration and (2) with RES integration. Several independent trial runs are executed, and the performance of the algorithms is assessed based on optimal UC schedules, fuel cost, emission quantization, convergence curve, and computational time. For case 1, the proposed algorithm resulted in a percentage reduction of 0.1021% in fuel cost and 0.7995% in emission. In contrast, for test case 2, it resulted in a percentage reduction of 0.12896% in fuel cost and 0.772% in emission with the proposed algorithm. The results validate the dominance of the proposed methodology over existing methods in terms of lower fuel costs and emissions.

Electricity system optimisation based on python model for renewable electricity generation portfolio

Electricity system optimisation based on python model for renewable electricity generation portfolio

Pathway for a fully renewable power sector of Africa by 2050: Emphasising on flexible generation from biomass

The climate crisis coupled with energy poverty and injustice in Africa requires strategic measures to proffer sustainable solutions. A transition to a defossilised power sector is obtained for Africa by 2050, evolutionarily developed to fulfil the Paris Agreement. With the LUT Energy System Transition Model, the role of biomass in a least-cost power sector for Africa is investigated from 2020 to 2050 in five-year time steps. Techno-economic assumptions of employed technologies are applied. The study considers the current generation portfolio, lifespan of power plant technologies, and the current and future electricity demand to ascertain the best generation mix by 2050. Biomass potential of 334 TWh (17.5%) of the total African biomass potential of 1911 TWh is applied to the African power sector to develop two Best Policy Scenarios: a scenario without bioenergy (BPS-1) and a scenario with bioenergy (BPS-2). The results indicate a positive impact of bioenergy on the power sector: The total generation, total installed capacity, grid utilisation, levelised cost of electricity, and storage output decreased by 8.6%, 8.4%, 12.9%, 10.2%, 47.1% by 2050 respectively in BPS-2 relative to the BPS-1. In addition, flexible generation from biomass offers balancing to enhance variable renewable energy resources integration onto the power sector.

Assessing the Complementarity of Wind and Solar Energy in Kentucky

Recently, there has been a push by countries to diversify their energy mix considering various factors. In this regard, there have been several studies conducted to assess the potential for using sources such as wind and solar to generate supplemental energy to the already present energy generation setup. In this regard, this study explores the potential of wind for the Commonwealth of Kentucky. To perform this study, wind data were sourced for eight locations across Kentucky from the publicly accessible wind speed information present at Weather Underground for the years 2020–2021 (two years). An analysis was performed concerning the seasonal, monthly, and hourly variation in the wind speed so as to identify the expected times of sufficient wind energy generation. Moreover, a comparison of the collected data was performed with data from a home-based weather station as well as a deployed wind turbine to validate the variation pattern of the publicly sourced data. Finally, in order to investigate the variation patterns of wind and solar energy sources, a comparative analysis was also performed using data from a solar power generation plant in Kentucky. A seasonal and monthly complementarity was observed between the wind and solar energy. However, when considering daily patterns, the wind was found to follow solar generation with an offset. While further research is required, this analysis indicates that it is possible to deploy wind energy power generation projects in the Commonwealth of Kentucky. The seasonal complementary behavior of wind and solar energy can be used along with battery storage in conjunction with natural gas to provide a diversified electricity generation portfolio.

An integrated planning framework for optimal power generation portfolio including frequency and reserve requirements

AbstractElectricity system decarbonisation poses several challenges to network stability and supply security, given renewables' intermittency and possible reduction of system inertia. This manuscript presents a novel integrated system framework to determine optimal generation investments for addressing decarbonisation challenges and achieving cost‐effective electricity systems while ensuring frequency stability and reserve requirements are met at the operational level in a net‐zero system. The novel planning framework is a mixed‐integer bilinear programming problem accurately modelling clustered variables for the on/off status of generation units and seconds‐timescale frequency requirements at an operational and planning level. The benefits of the decision framework and effects of dispatch decisions in a year are illustrated using the Great Britain case study. The results provide optimal trade‐offs and cost‐effective investment portfolios for including detailed modelling of unit‐commitment and frequency stability constraints versus not including them in the planning model. Making investment decisions for a net‐zero electricity system without these constraints can lead to very high system costs due to significant demand curtailment. Although the model's computation burden was increased by these constraints, complexity was managed by formulating them tightly and compactly. Non‐convex quadratic nadir constraints were efficiently solvable to global optimality by applying McCormick relaxations and branching techniques in an advanced solver.

Future role of wave power in Seychelles: A structured sensitivity analysis empowered by a novel EnergyPLAN-based optimisation tool

Mitigating climate change requires a variety of energy technologies and energy simulation approaches to evaluate the best possible system structures. Screening whether novel technologies are a viable solution for a particular country within a cost-optimised system setup is usually simulation- and time-intensive. This study introduces the novel add-on optimisation tool EP-ALISON-LUT for use in combination with EnergyPLAN applied to the test case of wave power in the case of Seychelles in 2030 and 2050 within a structured sensitivity analysis. The tool enables a high number of possible system setups and scenarios, including the import and domestic production of electricity-based fuels, to be modelled, allowing for an in-depth view of the system impacts of integrating wave power. The results indicate a limited role for wave power due to its relatively low yield, especially in 2030. However, in 2050, up to 500 MW of wave power capacity is possible with a lower or similar levelised cost of final energy compared to the reference scenario in 2019, which can benefit the diversification of the power generation portfolio. Thus, this novel tool is fast and effective in technology screening studies requiring a fast optimisation algorithm.

Speeding Up Renewable Energy Integration with Invisible Hands: Ancillary Service Market and the COVID-19 Natural Experiment

Sustaining a high-renewable electricity generation portfolio has proved to be difficult due to grid flexibility constraints. We utilize the abrupt decline in electricity demand due to the COVID-19 lockdown in China as a policy experiment to study the role of ancillary service markets (ASMs) in promoting intermittent renewable energy integration. Our results reveal that provinces with ASMs sustained a significantly higher generation of intermittent renewable energy during the COVID-19 demand shock, which amounts to 9.7 percent of average monthly intermittent renewable energy generation during the shock. A back-of-envelope analysis further shows that annual carbon emission offset from establishing ASMs in all provinces of China could amount to 13 to 17 percent of annual carbon emissions from Britain in the near future when renewable energy penetration continues to go up. JEL Classification: Q20, Q42, Q53, O13

Electricity Demand, Forecasting the Peaks: Development and Implementation of C-EVA Method

Price spikes in electricity markets are very frequent, posing tremendous burden on household income and on manufacturing cost. Electricity demand (load) can be divided in two parts, energy (MWh) and peak (MW) and most of time peak is responsible for the price spikes. Literature review while devoting most of the discussion to energy, lags in the investigation of peak. In this research, a model for peak demand analysis and forecasting is developed. The model is based on a portfolio of cluster and extreme value analysis (C-EVA) methods using unit invariant knee, extremum distance estimator, and weighted scale load innovations for the optimal determination of clusters and the daily peaks divulgence. The C-EVA method consists of the Clustering part for optimal number of clusters determination and classification of day and month of peak, and the part of Extreme Value Analysis for computation of the statistical confidence interval for the load maxima. C-EVA after using all the currently available load maxima, estimates statistically the expected worst-case scenario for peaks of loads. Load peaks will be determined by EVA based on an estimated bimodal distribution while a signaling method will prompt the probability of extremes. The added value of the proposed method is that does not reject the extreme values as most methodologies do. Extreme Value Analysis for maxima and minima provide estimators for highest and lowest expected hourly load, while giving the confidence interval of the return level using an optimization method for the selection of a rolling time window, as the return period. It was found that distributed generation of renewables create a camel effect on the load peaks which increases sharpness. The proposed methodology solved this issue while opening the ground for future research for the role of storage, batteries as well as for virtual power plants as an integrated portfolio of renewables generation. Received: 18 December 2023 | Revised: 18 February 2024 | Accepted: 19 May 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The database that supports the findings of this study will be made available by the authors upon request only in a specific Excel format. Author Contribution Statement Petros Theodorou and Demetris Theodoros Christopoulos: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration.

The effect of the 2022 energy crisis on electricity markets ashore the North Sea

The effect of the 2022 energy crisis on electricity markets ashore the North Sea

Power System Decarbonization Assessment: A Case Study from Taiwan

The first global stocktake (GST) at 2023 UN Climate Change Conference (COP28) pointed out that accelerating the phasing down of fossil fuels has become an important mitigation policy to maintain a maximum temperature limit of 1.5 °C. The optimal power portfolio for achieving Taiwan’s net-zero emissions by 2050 is evaluated from the perspective of sustainable development. This study is enhances the 2021 research findings of Wang et al. on the sustainable power model, incorporating homogenized cost and technical constraints for empirical analysis. The results indicated that renewable energy sources play a pivotal role in achieving net-zero emissions. Gas power generation requires careful consideration, including early decommissioning or the adoption of carbon capture and storage (CCS) technology to prevent carbon lock-in and compete with hydrogen energy technology. Notably, coal combined with CCS technology offers a viable option for a cost-effective roadmap for a decarburized power generation portfolio by 2050, serving as a reference for national planning strategies for promoting net-zero emissions.

Deep neural network for investment decision planning on low-carbon transition in power grid

AbstractWith the urgency of mitigating global warming, the low-carbon transformation of power grid systems has emerged as a pivotal industry upgrade for sustainable development. We proposed a novel deep neural network-based approach for investment decision planning in the low-carbon transformation of power grids, which aimed to address multidimensional key indicators related to power grid transformation and provided reliable electricity industry layouts and investment plans for power system investment decisions. To achieve this, three targeted investment branch models were established, encompassing investment behavior, electricity production and consumption, and predictions of new capacity investment. These models effectively tackled challenges associated with power distribution, electricity price scheduling, power carbon quotas, and the feasibility of low-carbon power generation technologies. Subsequently, a global investment decision planning model was constructed, employing spatiotemporal neural networks and recurrent neural networks, which integrated the aforementioned branch models and incorporated existing low-carbon transformation data. A comparative analysis was conducted, examining the predicted results against actual values from three perspectives: power generation portfolio, grid economy, and overall investment decision plans. The results demonstrated the effectiveness of our method in accurately predicting future installed capacity of diverse low-carbon power generation technologies, sustainability indices, and investment returns. Notably, our method achieves an impressive forecasting accuracy of over 90% compared to actual values of investment decision planning over the past 4 years.

Reducing the carbon footprint of Whisky production through the use of a battery and heat storage alongside renewable generation

This paper presents an analysis of providing a typical distillery with low carbon energy through the combination of local wind energy, solar PV, electricity storage and heat storage.The aim of this is to increase the sustainability of the energy-intensive whisky industry. Using hourly local renewable resource data and typical distillery consumption information, the local energy generation is balanced against the demand at the time of use. This followed by load shifting using a battery and heat storage. Results show that significant carbon savings can be achieved by a carefully designed portfolio of hybrid generation, battery storage and heat storage.

On the impact of tidal generation and energy storage integration in PV-rich electric distribution systems

On the impact of tidal generation and energy storage integration in PV-rich electric distribution systems

High temporal resolution generation expansion planning for the clean energy transition

High temporal resolution generation expansion planning for the clean energy transition

A Pragmatic Approach to the Economic Assessment of Green Synthetic Methane Power in the Baltics

The synthesis of methane from hydrogen and carbon dioxide creates an energy resource that is suitable for long-term storage. Once this process is powered by renewable electricity, it produces a clean fuel for producing electricity and heat and supports large-scale renewable energy deployment, energy transition and climate change mitigation. This paper proposes a pragmatic approach to assessing the economic potential of synthetic methane-based power. Today, natural gas plays an important role in the Baltic region due to the existing infrastructure, which includes a transmission and distribution pipeline network, gas power plants and a large underground storage reservoir. Replacing natural gas with synthetic methane would fulfil carbon emission reduction ambitions. In this paper, we simulate electricity producers’ actions at market conditions and consider the generation portfolio in the Baltics and the interconnections with Scandinavia and Poland operating in the NORDPOOL electricity market. As a result of these calculations, we obtain the volume of the synthetic gas, the production costs, the volume of gas storage, the installed capacity of the gas power plant, and the investments required to ensure energy transition and system adequacy. These results are essential for the informed decisions made by policymakers, investors and system operators.

Optimal investment portfolio strategy for carbon neutrality of power enterprises

Optimal investment portfolio strategy for carbon neutrality of power enterprises

The state of energy in sub-Saharan Africa and the urgency for small hydropower development

There exist several renewable energy resources within the African continent. Quite a lot of attempts have been made to study these small hydroelectric sites and ways to harness them. Nevertheless, the majority of these potential sites remain undeveloped. Several countries within the African region such as Togo, Tanzania, Kenya, Ghana, and many others continue to experience a cyclical national power crisis, which is mostly attributable to insufficient power output to meet the continuously rising demand. An increase in electricity demand is unavoidable as the nation works to grow its economy, and more electricity generation will be required to power both established and new sectors. Several villages within the sub-Saharan region have lived with no electrical energy access for several decades now. The majority of these nation's current power generation portfolio is made up of a combination of hydro and thermal power plants, and for a while now, any temporary increase in generation has been achieved by the addition of new thermal power plants, even though these fossil fuels are occasionally in short supply. The country enters a constant cycle of power rationing with serious negative effects on industry and homes due to seasonal reductions in water inflows into hydropower facilities and occasionally difficulty obtaining crude oil or natural gas. Potential problems of this energy crisis are the high demand for electricity caused by certain factors its supply challenges and the lack of structural supply of electricity to consumers.it is therefore important for the entire globe particularly the developed countries to alleviate Africa from the high energy demand and poverty as a result of the energy crisis.

A new era for rural electric cooperatives: New clean energy investments, supported by federal incentives, will reduce rates, emissions, and reliance on outside power

A new era for rural electric cooperatives: New clean energy investments, supported by federal incentives, will reduce rates, emissions, and reliance on outside power