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This paper presents a survey of the literature on the strategies to enhance the resilience of power systems while shedding lights on the research gaps. Using a deductive methodology on the literature covering the resilience of power systems, we reviewed more than two hundred peer-reviewed articles spanning the 2010–2019 decade. We find that there is vacuum on the level of integration that considers the interdependence of local or decentralized decision making in an adaptive power system. This gap is widened by the absence of policies to enhance resilience in power networks. While there is significant coverage and convergence of research on algorithms for solving the multi-objective problem in optimization routines, there are still uncharted territories on how to incorporate system degradation while designing these self-restoration systems. We posit that a shift to a smarter, cleaner and more resilient power network requires sustained investments rather than disaster-induced responses.
Ekundayo Shittu; Abhijai Tibrewala; Swetha Kalla; Xiaonan Wang. Meta-analysis of the strategies for self-healing and resilience in power systems. Advances in Applied Energy 2021, 4, 100036 .
AMA StyleEkundayo Shittu, Abhijai Tibrewala, Swetha Kalla, Xiaonan Wang. Meta-analysis of the strategies for self-healing and resilience in power systems. Advances in Applied Energy. 2021; 4 ():100036.
Chicago/Turabian StyleEkundayo Shittu; Abhijai Tibrewala; Swetha Kalla; Xiaonan Wang. 2021. "Meta-analysis of the strategies for self-healing and resilience in power systems." Advances in Applied Energy 4, no. : 100036.
Dam removal is gaining both support and resistance in different communities and political circles in the Pacific Northwest of the United States; given its sensitive environmental and economic consequences. The Columbia River Basin (CRB) offers a unique opportunity to examine to what extent the replacement of hydroelectric dams affects reliability and adequacy of the power system given long-standing proposals to remove the four Lower Snake River dams to improve the survival of the endangered salmon species. Key results show that replacing the four dams leads to an inadequate energy supply necessitating the need for more capacity to satisfy requirements. Although the four dams have higher nameplate capacity, they provide a much lower effective capacity. Thus, the debate about removing dams should be an opportunity for CRB managers to consider investment options in new ecosystem services and energy solutions that maintain adequate performance.
Dor Hirsh Bargai; Ekundayo Shittu. Salmon Versus Power: Dam Removal and Power Supply Adequacy. IEEE Engineering Management Review 2021, 49, 126 -133.
AMA StyleDor Hirsh Bargai, Ekundayo Shittu. Salmon Versus Power: Dam Removal and Power Supply Adequacy. IEEE Engineering Management Review. 2021; 49 (2):126-133.
Chicago/Turabian StyleDor Hirsh Bargai; Ekundayo Shittu. 2021. "Salmon Versus Power: Dam Removal and Power Supply Adequacy." IEEE Engineering Management Review 49, no. 2: 126-133.
This research analyzes cost account-level detail from ten similar satellite programs to assess the relationship between cost and schedule variances. A model is defined to break activity into two types: level of effort (LOE), in which cost is directly proportional to the cost account’s duration and discrete, where the cost is independent of the schedule. Primary data collected by the authors from the ten satellite programs are split into these two categories and analyzed separately. Marginal distributions for schedule and cost for each of the two databases are built using the generalized two-sided power distribution (GTSP). Correlations between cost and schedule variance are calculated for the LOE and discrete cost accounts. Finally, joint distributions are created for each database using generalized diagonal band copulas. The results show that the GTSP effectively modeled the marginal distributions and the generalized diagonal band copula with a slope generating function successfully representing the observed joint distribution. The analysis, resulting from the correlation values, show that the cost and schedule variance for discrete cost accounts are not correlated. However, the LOE cost accounts show a correlation well below the projected perfect correlation. The models were validated by removing one program’s data from the database, regenerating the models, and assessing the accuracy of the model against the program excluded from the model. The model derived from nine programs successfully modeled the results from the tenth program. These results provide both a modeling method and guidance for modeling parameters for joint cost and schedule risk analysis.
Andy Lewin; Ekundayo Shittu; Thomas Mazzuchi; Rene van Dorp. The correlation of cost and schedule variance in satellite programs: level of effort versus discrete cost accounts. Environment Systems and Decisions 2021, 41, 248 -266.
AMA StyleAndy Lewin, Ekundayo Shittu, Thomas Mazzuchi, Rene van Dorp. The correlation of cost and schedule variance in satellite programs: level of effort versus discrete cost accounts. Environment Systems and Decisions. 2021; 41 (2):248-266.
Chicago/Turabian StyleAndy Lewin; Ekundayo Shittu; Thomas Mazzuchi; Rene van Dorp. 2021. "The correlation of cost and schedule variance in satellite programs: level of effort versus discrete cost accounts." Environment Systems and Decisions 41, no. 2: 248-266.
This article investigates the relationship between firms’ carbon intensity, carbon management practices, and their financial performance. The extant literature on firms’ financial performance and their environmental performance has mostly considered a single dimension of firms’ environmental performance leading to restricted, and often, mixed outcomes. With panel data collected on financial statements and climate change related activities from 136 corporate firms in the U.S. between 2011 and 2018, this article integrates a process dimension based on an environmental management score with an outcome dimension represented by firms’ carbon emissions intensity. A regression model is employed to investigate the relationships between corporate environmental performance and corporate financial performance. We find evidence of a nonlinear relationship between corporate firms’ environmental performance and financial performance across both high and low-carbon intensive sectors. Specifically, we find that for firms in the high-carbon intensive sector, a U-shaped relationship exists between firms’ corporate environmental performance outcome dimension and their financial performance while for the low-carbon intensive sector, the converse is the case. The results show that the interaction between the outcome dimension of environmental performance and financial performance is moderated by the process dimension of environmental performance for firms in the low- and high-carbon intensive sectors.
Olawale Ogunrinde; Ekundayo Shittu; Kanwalroop Kathy Dhanda. Distilling the Interplay Between Corporate Environmental Management, Financial, and Emissions Performance: Evidence From U.S. Firms. IEEE Transactions on Engineering Management 2020, PP, 1 -29.
AMA StyleOlawale Ogunrinde, Ekundayo Shittu, Kanwalroop Kathy Dhanda. Distilling the Interplay Between Corporate Environmental Management, Financial, and Emissions Performance: Evidence From U.S. Firms. IEEE Transactions on Engineering Management. 2020; PP (99):1-29.
Chicago/Turabian StyleOlawale Ogunrinde; Ekundayo Shittu; Kanwalroop Kathy Dhanda. 2020. "Distilling the Interplay Between Corporate Environmental Management, Financial, and Emissions Performance: Evidence From U.S. Firms." IEEE Transactions on Engineering Management PP, no. 99: 1-29.
This paper focuses on the interdependent relationship of power generation, transportation and CO2 emissions to evaluate the impact of electric vehicle deployment on power generation and CO2 emissions. The value of this evaluation is in the employment of a large-scale, bottom-up, national energy modeling system that encompasses the complex relationships of producing, transforming, transmitting and supplying energy to meet the useful demand characteristics with great technological detail. One of such models employed in this analysis is the BUEMS model. The BUEMS model provides evidence of win-win policy options that lead to profitable decarbonization using Turkey’s data in BUEMS. Specifically, the result shows that a ban on diesel fueled vehicles reduces lifetime emissions as well as lifetime costs. Furthermore, model results highlight the cost-effective emission reduction potential of e-buses in urban transportation. More insights from the results indicate that the marginal cost of emission reduction through e-bus transportation is much lower than that through other policy measures such as carbon taxation in transport. This paper highlights the crucial role the electricity sector plays in the sustainability of e-mobility and the value of related policy prescriptions.
Gürkan Kumbaroğlu; Cansu Canaz; Jonathan Deason; Ekundayo Shittu. Profitable Decarbonization through E-Mobility. Energies 2020, 13, 4042 .
AMA StyleGürkan Kumbaroğlu, Cansu Canaz, Jonathan Deason, Ekundayo Shittu. Profitable Decarbonization through E-Mobility. Energies. 2020; 13 (16):4042.
Chicago/Turabian StyleGürkan Kumbaroğlu; Cansu Canaz; Jonathan Deason; Ekundayo Shittu. 2020. "Profitable Decarbonization through E-Mobility." Energies 13, no. 16: 4042.
The construction of a continuous family of distributions on a compact set is demonstrated by concatenating, in a continuous manner, three probability density functions with bounded support using a modified mixture technique. The construction technique is similar to that of generalized trapezoidal (GT) distributions, but contrary to GT distributions, the resulting density function is smooth within its bounded domain. The construction of Generalized Trapezoidal Ogive (GTO) distributions was motivated by the COVID-19 epidemic, where smoothness of an infection rate curve may be a desirable property combined with the ability to separately model three stages and their durations as the epidemic progresses, being: (1) an increasing infection rate stage, (2) an infection rate stage of some stability and (3) a decreasing infection rate stage. The resulting model allows for asymmetry of the infection rate curve opposite to, for example, the Gaussian Error Infection (GEI) rate curve utilized early on for COVID-19 epidemic projections by the Institute for Health Metrics and Evaluation (IHME). While other asymmetric distributions too allow for the modeling of asymmetry, the ability to separately model the above three stages of an epidemic’s progression is a distinct feature of the model proposed. The latter avoids unrealistic projections of an epidemic’s right-tail in the absence of right tail data, which is an artifact of any fatality rate model where a left-tail fit determines its right-tail behavior.
Johan René Van Dorp; Ekundayo Shittu; Thomas A. Mazzuchi. Generalized trapezoidal ogive curves for fatality rate modeling. Chaos, Solitons & Fractals: X 2020, 5, 100043 -100043.
AMA StyleJohan René Van Dorp, Ekundayo Shittu, Thomas A. Mazzuchi. Generalized trapezoidal ogive curves for fatality rate modeling. Chaos, Solitons & Fractals: X. 2020; 5 ():100043-100043.
Chicago/Turabian StyleJohan René Van Dorp; Ekundayo Shittu; Thomas A. Mazzuchi. 2020. "Generalized trapezoidal ogive curves for fatality rate modeling." Chaos, Solitons & Fractals: X 5, no. : 100043-100043.
Dor Hirsh Bar Gai; Olawale Ogunrinde; Ekundayo Shittu. Self-Reporting Firms: Are Emissions Truly Declining for Improved Financial Performance? IEEE Engineering Management Review 2020, 48, 163 -170.
AMA StyleDor Hirsh Bar Gai, Olawale Ogunrinde, Ekundayo Shittu. Self-Reporting Firms: Are Emissions Truly Declining for Improved Financial Performance? IEEE Engineering Management Review. 2020; 48 (1):163-170.
Chicago/Turabian StyleDor Hirsh Bar Gai; Olawale Ogunrinde; Ekundayo Shittu. 2020. "Self-Reporting Firms: Are Emissions Truly Declining for Improved Financial Performance?" IEEE Engineering Management Review 48, no. 1: 163-170.
To address the gross deficit in electricity demand and supply in Nigeria requires a pragmatic and sequential approach to expanding generation capacity. Numerous studies have expatiated on the underlying problems with solution strategies that are comprehensive. However, many of those suggested solutions are either too steep cost-wise or the system is limited in the adaptive capacity to incorporate them. This paper proffers a stepped approach at expanding the capacity of supply as a function of the energy locational distance of the states and regions in the country. In this research, we interpret energy locational distance as a measure that is derived from the answer to two questions. First, how much is generation below the output capacity of the existing generating plants that are stationed across the country serving the national grid? Second, what is the minimum threshold of capacity expansion to achieve a set energy density or energy per person index across the regions of the country differentiated by energy poverty? With this exploration, energy planners in Nigeria, rather than seeking to address the dearth of electricity supply in the country in one step, could consider a piecemeal approach that indeed offers tremendous and relatively significant expansions in capacity. This outcome offers guidance to policy makers and investors on how to craft their investment efforts in a manner that is akin to viewing the problem at the proverbial context of effecting changes at the tree level rather than seeking to change the forest.
Olawale Ogunrinde; Ekundayo Shittu; Mobolaji Bello; Innocent Davidson. Exploring the Demand-Supply Gap of Electricity in Nigeria: Locational Evaluation for Capacity Expansions. 2019 IEEE PES/IAS PowerAfrica 2019, 587 -592.
AMA StyleOlawale Ogunrinde, Ekundayo Shittu, Mobolaji Bello, Innocent Davidson. Exploring the Demand-Supply Gap of Electricity in Nigeria: Locational Evaluation for Capacity Expansions. 2019 IEEE PES/IAS PowerAfrica. 2019; ():587-592.
Chicago/Turabian StyleOlawale Ogunrinde; Ekundayo Shittu; Mobolaji Bello; Innocent Davidson. 2019. "Exploring the Demand-Supply Gap of Electricity in Nigeria: Locational Evaluation for Capacity Expansions." 2019 IEEE PES/IAS PowerAfrica , no. : 587-592.
While the role of organizational learning in improving firm performance is well documented, there are still questions on what drives technological learning. This is evident in the electricity industry where the growth of renewable energy technologies has been pervasive. Vicarious learning contributes to the adoption of emerging technologies through successful inter-firm knowledge sharing and transfer. However, there is hesitation to adoption that characterizes vicarious learning especially in the context of intra-firm learning. This paper investigates the differences in knowledge acquisition within and across electricity firms in the U.S. The learning curve model is applied to a longitudinal study of 5573 plants belonging to 1542 U.S. electricity firms between 1998 and 2010. This study finds: (i) The capacity growth of the solar photovoltaic technology is positively associated with intra-firm knowledge acquisition; (ii) The effect of financial incentives on the adoption of solar and wind technologies is higher under inter-firm learning; (iii) The higher the stringency of policy mandates, the more varied is the progress on technological change across technologies; (iv) Knowledge sharing between firms are higher for wind technology than for solar technology. These findings combine to show disparities in the learning trends of technologies across and within firms’ boundaries.
Ekundayo Shittu; Bruno G. Kamdem; Carmen Weigelt. Heterogeneities in energy technological learning: Evidence from the U.S. electricity industry. Energy Policy 2019, 132, 1034 -1049.
AMA StyleEkundayo Shittu, Bruno G. Kamdem, Carmen Weigelt. Heterogeneities in energy technological learning: Evidence from the U.S. electricity industry. Energy Policy. 2019; 132 ():1034-1049.
Chicago/Turabian StyleEkundayo Shittu; Bruno G. Kamdem; Carmen Weigelt. 2019. "Heterogeneities in energy technological learning: Evidence from the U.S. electricity industry." Energy Policy 132, no. : 1034-1049.
To address the effects of climate change, it is imperative for economies to proactively invest in, and deploy, low carbon energy technologies to meet current energy demands. To this effect, several states in the U.S. have implemented policies to incentivize the growth of renewable energy technologies. One of these policies is the renewable portfolio standards (RPS) which mandates that a certain percentage of the total electricity sales of utilities be sourced from renewable energy sources. This paper examines the effectiveness of these policies in driving the growth of specific renewable technologies across different regional transmission organizations (RTOs). It evaluates the adoption of renewable energy technologies across these RTOs to provide insights on the varying successes of these policies. The paper develops a ranking system for the correlations between the strength of RPS and renewable energy capacity growth across the RTOs. Two central observations emerge. First, despite the presence of positive correlations between RPS and renewable energy capacity additions, the capacity growth of renewable energy is not monotonic in time as technological differences characterize regional attributes. Second, the technology returns on RPS mandates are location-specific.
Olawale Ogunrinde; Ekundayo Shittu; Kanwalroop Kathy Dhanda. Investing in Renewable Energy: Reconciling Regional Policy With Renewable Energy Growth. IEEE Engineering Management Review 2018, 46, 103 -111.
AMA StyleOlawale Ogunrinde, Ekundayo Shittu, Kanwalroop Kathy Dhanda. Investing in Renewable Energy: Reconciling Regional Policy With Renewable Energy Growth. IEEE Engineering Management Review. 2018; 46 (4):103-111.
Chicago/Turabian StyleOlawale Ogunrinde; Ekundayo Shittu; Kanwalroop Kathy Dhanda. 2018. "Investing in Renewable Energy: Reconciling Regional Policy With Renewable Energy Growth." IEEE Engineering Management Review 46, no. 4: 103-111.
This paper presents an extension and application of the two-stage stochastic optimization methodology to determine electricity generation technology choices and capacity additions under sequential and multiple uncertainties. Specifically, the model presented in this paper addresses how uncertainties in electricity demand, capacity factor of wind and solar technologies, and environmental policy combine to affect the capacity additions of electricity generation technologies. This study unpacks the impact of these uncertainties to find that, on the one hand, when policy uncertainty is isolated from uncertainties in demand and capacity factor, neither of the two uncertainties dominates the other; instead they are complementary. Capacity factor uncertainty will dictate the types of technologies to be deployed while demand uncertainty will determine the amount of capacity to be installed or purchased. On the other hand, a combination of the three dimensions of uncertainty highlights intriguing insights that demonstrate the dominance of one uncertainty over the other. Under two different environmental policies, emissions standards and carbon taxes, the optimal prescription of generation technology combinations with respect to capacity additions are varied. However, we find that carbon tax will be more efficient at reducing CO2.
Ilka DeLuque; Ekundayo Shittu. Generation capacity expansion under demand, capacity factor and environmental policy uncertainties. Computers & Industrial Engineering 2018, 127, 601 -613.
AMA StyleIlka DeLuque, Ekundayo Shittu. Generation capacity expansion under demand, capacity factor and environmental policy uncertainties. Computers & Industrial Engineering. 2018; 127 ():601-613.
Chicago/Turabian StyleIlka DeLuque; Ekundayo Shittu. 2018. "Generation capacity expansion under demand, capacity factor and environmental policy uncertainties." Computers & Industrial Engineering 127, no. : 601-613.
The objective of this paper is to identify strategies to improve the resilience of interagency communication between relief organizations and the community when dealing with an emergency. This research draws from frameworks including information theory, organization design, and how the private sector has learned and evolved from the challenges of information flow to provide guidance to disaster relief agencies. During times of emergency, private organizations as well as public authorities must coordinate in real time to create an effective response. When coordination is absent, failure results, as was seen after Hurricane Katrina and the Haiti Earthquake. Using data that the authors collected immediately after these disasters, two case studies of systemic failure are presented to extract lessons that might be used to improve communication resilience through coordination between parties in humanitarian relief operations. Recent emergency response trends are identified, and the paper argues that the persistence of response failures is not surprising, in part because response organizations normally operate independently, and their operations evolve at different rates. As a result, the organizational interfaces that enable rapid integration during a disaster naturally degrade and may be weak or absent. Integrating the literature on information processing theory and organization design with the data from the two case studies, the paper proposes that increasing the resilience of disaster response systems can be achieved by (1) improving the interoperability and information flow across organizational boundaries; (2) increasing the synergies between organizations on adapting new technology such as social media for the coordination of structured and unstructured data for use in decision-making, and (3) increasing the flexibility of relief organizations to use external resources from areas not affected by disasters on an opportunistic basis. The paper concludes by discussing resilience enhancing solutions including boundary spanning investments and argues that effective emergency response does not result from sporadic or intermittent efforts but rather requires sustained investment, continuous monitoring, and data collection.
Ekundayo Shittu; Geoffrey Parker; Nancy Mock. Improving communication resilience for effective disaster relief operations. Environment Systems and Decisions 2018, 38, 379 -397.
AMA StyleEkundayo Shittu, Geoffrey Parker, Nancy Mock. Improving communication resilience for effective disaster relief operations. Environment Systems and Decisions. 2018; 38 (3):379-397.
Chicago/Turabian StyleEkundayo Shittu; Geoffrey Parker; Nancy Mock. 2018. "Improving communication resilience for effective disaster relief operations." Environment Systems and Decisions 38, no. 3: 379-397.
Many developing countries still face the prevalence of preventable childhood diseases because their vaccine supply chain systems are inadequate by design or structure to meet the needs of their populations. Currently, Nigeria is evaluating options in the redesign of the country’s vaccine supply chain. Using Nigeria as a case study, the objective is to evaluate different regional supply chain scenarios to identify the cost minimizing optimal hub locations and storage capacities for doses of different vaccines to achieve a 100% fill rate. First, we employ a shortest-path optimization routine to determine hub locations. Second, we develop a total cost minimizing routine based on stochastic optimization to determine the optimal capacities at the hubs. This model uses vaccine supply data between 2011 and 2014 provided by Nigeria’s National Primary Health Care Development Agency (NPHCDA) on Tuberculosis, Polio, Yellow Fever, Tetanus Toxoid, and Hepatitis B. We find that a two-regional system with no central hub (NC2) cut costs by 23% to achieve a 100% fill rate when compared to optimizing the existing chain of six regions with a central hub (EC6). While the government’s leading redesign alternative – no central three-hub system (Gov NC3) – reduces costs by 21% compared with the current EC6, it is more expensive than our NC2 system by 3%. In terms of capacity increases, optimizing the current system requires 42% more capacity than our NC2 system. Although the proposed Gov NC3 system requires the least increase in storage capacity, it requires the most distance to achieve a 100% coverage and about 15% more than our NC2. Overall, we find that improving the current system with a central hub and all its variants, even with optimal regional hub locations, require more storage capacities and are costlier than systems without a central hub. While this analysis prescribes the no central hub with two regions (NC2) as the least cost scenario, it is imperative to note that other configurations have benefits and comparative tradeoffs. Our approach and results offer some guidance for future vaccine supply chain redesigns in countries with similar layouts to Nigeria’s.
Dor Hirsh Bar Gai; Zachary Graybill; Paule Voevodsky; Ekundayo Shittu. Evaluating scenarios of locations and capacities for vaccine storage in Nigeria. Vaccine 2018, 36, 3505 -3512.
AMA StyleDor Hirsh Bar Gai, Zachary Graybill, Paule Voevodsky, Ekundayo Shittu. Evaluating scenarios of locations and capacities for vaccine storage in Nigeria. Vaccine. 2018; 36 (24):3505-3512.
Chicago/Turabian StyleDor Hirsh Bar Gai; Zachary Graybill; Paule Voevodsky; Ekundayo Shittu. 2018. "Evaluating scenarios of locations and capacities for vaccine storage in Nigeria." Vaccine 36, no. 24: 3505-3512.
This paper seeks to quantify the benefits of a flexible energy system in the context of enabling higher levels of variable renewable energy on the grid. We explore a nuclear hybrid energy system (NHES) consisting of a 300 MW small modular reactor, wind generation, battery storage, and a reverse osmosis desalination plant. A dispatch rule is constructed within the Risk Analysis Virtual Environment (RAVEN) to model the system. Stochastic optimization and parametric analysis are utilized to explore how increased volatility in the net demand resulting from higher levels of wind penetration affect the optimal solution, and the stability of the system’s levelized cost of electricity (LCOE). In this study, net demand is the demand minus wind generation. This work contributes multi-objective analysis implemented through a supply-demand mismatch penalty to illustrate the financial stability and operational reliability benefits of the flexible energy system. In this context, we find that the additional up front cost of flexible loads and energy storage result in greater stability in LCOE as volatility in the demand increases. Additionally, the flexibility results in increased reliability in terms of meeting the demand. Although the analysis is conducted on a NHES, we emphasize the flexibility of the method applied here, in that the RAVEN platform and the multi-objective strategy are widely applicable to the analysis of energy systems faced with uncertainties in supply and demand.
T.E. Baker; A.S. Epiney; C. Rabiti; E. Shittu. Optimal sizing of flexible nuclear hybrid energy system components considering wind volatility. Applied Energy 2018, 212, 498 -508.
AMA StyleT.E. Baker, A.S. Epiney, C. Rabiti, E. Shittu. Optimal sizing of flexible nuclear hybrid energy system components considering wind volatility. Applied Energy. 2018; 212 ():498-508.
Chicago/Turabian StyleT.E. Baker; A.S. Epiney; C. Rabiti; E. Shittu. 2018. "Optimal sizing of flexible nuclear hybrid energy system components considering wind volatility." Applied Energy 212, no. : 498-508.
This paper develops a decision evaluation framework to assess how the treatment of risk affects the reliability of, and investment into, electricity generation infrastructure. First, portfolios of electricity generation technologies that comprise the energy supply systems in the US are evaluated using a mean-variance approach. Second, this research assesses the reliability of the portfolios with the aid of loss of load expectation and loss of energy expectation metrics. The methodology considers the least-cost technology mix coupled with the reduction of market and system risks. The variation in the portfolio cost is based on the prevailing policies in the geographic locations. Overall, the current mix of technologies evaluated along the cost-risk latitudes shows an inefficient electricity technology portfolio system. First, investments in renewable technologies may create a bifurcation. On the one hand, the portfolios with significant proportions of the high-cost intermittent technologies exhibit low market risks. On the other hand, these portfolios have less desirable system reliability measures. Second, policy makers will find it instructive that a more diverse electricity technology mix offers the potential to migrate to the efficient frontier in the near term. However, it is imperative to craft policies in support of the transition with the caveat that technology diversity is not always a panacea for improving system reliability even if the portfolio is on the efficient frontier. This work projects some intriguing insights and offers guidance for policy makers.
Ilka Deluque; Ekundayo Shittu; Jonathan Deason. Evaluating the reliability of efficient energy technology portfolios. EURO Journal on Decision Processes 2018, 6, 115 -138.
AMA StyleIlka Deluque, Ekundayo Shittu, Jonathan Deason. Evaluating the reliability of efficient energy technology portfolios. EURO Journal on Decision Processes. 2018; 6 (1-2):115-138.
Chicago/Turabian StyleIlka Deluque; Ekundayo Shittu; Jonathan Deason. 2018. "Evaluating the reliability of efficient energy technology portfolios." EURO Journal on Decision Processes 6, no. 1-2: 115-138.
Bruno G. Kamdem; Ekundayo Shittu. Optimal commitment strategies for distributed generation systems under regulation and multiple uncertainties. Renewable and Sustainable Energy Reviews 2017, 80, 1597 -1612.
AMA StyleBruno G. Kamdem, Ekundayo Shittu. Optimal commitment strategies for distributed generation systems under regulation and multiple uncertainties. Renewable and Sustainable Energy Reviews. 2017; 80 ():1597-1612.
Chicago/Turabian StyleBruno G. Kamdem; Ekundayo Shittu. 2017. "Optimal commitment strategies for distributed generation systems under regulation and multiple uncertainties." Renewable and Sustainable Energy Reviews 80, no. : 1597-1612.
We study the interplay between regulatory mandates and competition on a focal firm’s new resource investments. While prior literature has separately pointed to the influence of competition and regulatory policy on a focal firm’s resource decisions, less is known about how the policy effect interacts with the competitive effect. Studying how regulatory mandates moderate the effect of competition on a focal firm’s new resource investments, we show that resource redeployment is not simply a function of internal firm decisions but a response to external forces. We find that regulatory mandates dampen the effect of competitors’ new resource investments on a focal firm’s new resource investments. Distinguishing between different clean technology types, we show that this dampening effect is the stronger, the more distant the new resource is from incumbents’ old resource base, and the more established the mandate is. We test our hypotheses in the context of renewable energy investments in waste-to-energy, wind, and solar in the U.S. electricity industry. Our data comprise 1542 utilities and private energy firms and their renewable investments from 1999 to 2010.
Carmen Weigelt; Ekundayo Shittu. Competition, Regulatory Policy, and Firms’ Resource Investments: The Case of Renewable Energy Technologies. Academy of Management Journal 2016, 59, 678 -704.
AMA StyleCarmen Weigelt, Ekundayo Shittu. Competition, Regulatory Policy, and Firms’ Resource Investments: The Case of Renewable Energy Technologies. Academy of Management Journal. 2016; 59 (2):678-704.
Chicago/Turabian StyleCarmen Weigelt; Ekundayo Shittu. 2016. "Competition, Regulatory Policy, and Firms’ Resource Investments: The Case of Renewable Energy Technologies." Academy of Management Journal 59, no. 2: 678-704.
Highlights•Developed a worst-case oriented variability modeling called envelope method.•Characterized variability of renewables across multiple time scales.•Characterized capacity – QoS tradeoffs.•Proposed two QoS-based capacity definitions and compared with existing ones.•Implemented envelope analysis with 1-min data from CAISO and gained new insights. AbstractTo unify the analysis of both renewable and conventional fossil-fuel generating resources in electricity systems, we develop an envelope-based modeling method. Built on Network Calculus theory (NetCal) for deterministic queuing systems from the field of telecommunications engineering, this method characterizes the variability of electricity supply and demand by upper and lower envelopes and their respective Legendre conjugates. Differing from all other modeling methods, this method not only quantifies variability across different time scales, but also captures the intrinsic tradeoff between capacity and the corresponding Quality-of-Service (QoS) performance. In particular, the QoS measures represent matching/mismatching patterns between power supply and demand and provide an intuitive interpretation of the role of storage resources. The concept of QoS leads to two QoS-based capacity metrics – guaranteed capacity and best-effort capacity – whose conceptual and numerical properties are analyzed and compared against existing capacity metrics for validation purpose. As illustration, the proposed methods are applied to data from the California Independent System Operator (CAISO), which allows us to explicitly quantify the capacity contribution (via the notion of best-effort capacity) of wind during peak hours and its negative system impact at night, and demonstrates the positive capacity contribution of storage resources even though they are net energy consumer.
Xiaoyue Jiang; Geoffrey Parker; Ekundayo Shittu. Envelope modeling of renewable resource variability and capacity. Computers & Operations Research 2016, 66, 272 -283.
AMA StyleXiaoyue Jiang, Geoffrey Parker, Ekundayo Shittu. Envelope modeling of renewable resource variability and capacity. Computers & Operations Research. 2016; 66 ():272-283.
Chicago/Turabian StyleXiaoyue Jiang; Geoffrey Parker; Ekundayo Shittu. 2016. "Envelope modeling of renewable resource variability and capacity." Computers & Operations Research 66, no. : 272-283.
One of the major problems facing Nigeria’s vaccine supply chain is the lack of adequate vaccine storage facilities. Despite the introduction of solar-powered refrigerators and the use of new tools to monitor supply levels, this problem persists. Using data on vaccine supply for 2011–14 from Nigeria’s National Primary Health Care Development Agency, we created a simulation model to explore the effects of variance in supply and demand on storage capacity requirements. We focused on the segment of the supply chain that moves vaccines inside Nigeria. Our findings suggest that 55 percent more vaccine storage capacity is needed than is currently available. We found that reorganizing the supply chain as proposed by the National Primary Health Care Development Agency could reduce that need to 30 percent more storage. Storage requirements varied by region of the country and vaccine type. The Nigerian government may want to consider the differences in storage requirements by region and vaccine type in its proposed reorganization efforts.
Ekundayo Shittu; Melissa Harnly; Shanta Whitaker; Roger Miller. Reorganizing Nigeria’s Vaccine Supply Chain Reduces Need For Additional Storage Facilities, But More Storage Is Required. Health Affairs 2016, 35, 293 -300.
AMA StyleEkundayo Shittu, Melissa Harnly, Shanta Whitaker, Roger Miller. Reorganizing Nigeria’s Vaccine Supply Chain Reduces Need For Additional Storage Facilities, But More Storage Is Required. Health Affairs. 2016; 35 (2):293-300.
Chicago/Turabian StyleEkundayo Shittu; Melissa Harnly; Shanta Whitaker; Roger Miller. 2016. "Reorganizing Nigeria’s Vaccine Supply Chain Reduces Need For Additional Storage Facilities, But More Storage Is Required." Health Affairs 35, no. 2: 293-300.
The goal of this paper was to develop a better understanding of how energy firms might respond to competitive pressures in the context of regulatory risk. We model how competitive pressures affect capacity investments that firms make into their portfolio of technologies. Using comparative statics, we characterize energy firms’ incentives to invest in different energy technologies under imperfect competition in outputs and prices and within different environmental regulatory regimes. We find that under Cournot competition, firms that invest in renewable technologies benefit from both strategic and spillover effects on their overall profits. Under Bertrand competition, these benefits are enjoyed only by firms that invest in conventional technologies. Our findings can provide guidance for policy makers. Notably, even relatively weak targets set by regulators are likely to spur additional investment into renewable technologies. Regardless of policy type, strategic interactions and spillover benefits drive the optimal management of energy technology R&D activities. Our results also suggest ways for regulators to exploit the inherent benefits of imperfections in competitive markets to stimulate firms’ efforts at improving on the technologies in their portfolios. Overall, our results describe how technology investment incentives are shaped by the strategic interactions between firms, market structures, and environmental policy choices.
Ekundayo Shittu; Geoffrey Parker; Xiaoyue Jiang. Energy technology investments in competitive and regulatory environments. Environment Systems and Decisions 2015, 35, 453 -471.
AMA StyleEkundayo Shittu, Geoffrey Parker, Xiaoyue Jiang. Energy technology investments in competitive and regulatory environments. Environment Systems and Decisions. 2015; 35 (4):453-471.
Chicago/Turabian StyleEkundayo Shittu; Geoffrey Parker; Xiaoyue Jiang. 2015. "Energy technology investments in competitive and regulatory environments." Environment Systems and Decisions 35, no. 4: 453-471.