Uncertainty in Unit Commitment in Power Systems: A Review of Models, Methods, and Applications

The unit commitment problem (UCP) is one of the key and fundamental concerns in the operation, monitoring, and control of power systems. Uncertainty management in a UCP has been of great interest to both operators and researchers. The uncertainties that are considered in a UCP can be classified as technical (outages, forecast errors, and plugin electric vehicle (PEV) penetration), economic (electricity prices), and “epidemics, pandemics, and disasters” (techno-socio-economic). Various methods have been developed to model the uncertainties of these parameters, such as stochastic programming, probabilistic methods, chance-constrained programming (CCP), robust optimization, risk-based optimization, the hierarchical scheduling strategy, and information gap decision theory. This paper reviews methods of uncertainty management, parameter modeling, simulation tools, and test systems.

Risk response incorporating risk preferences in international construction projects

PurposeThe objective of this research is to develop a decision method that can generate appropriate risk response strategies for international construction project managers (PMs) and allow these strategies to reflect their different risk preferences.Design/methodology/approachThe optimal model approach is adopted. A credibility-based fuzzy chance constrained programming (CFCCP) model is developed, which simultaneously minimizes the expected losses of risk events and total costs of risk response. To solve this multi-objective model, a fuzzy interactive solution method is used. Moreover, the model performance is demonstrated by a real international industrial plant project. In addition, a sensitivity analysis of the model is conducted.FindingsThe result of the sensitivity analysis indicates that PMs with a greater risk aversion can lead to a higher mitigation ratio of expected losses of risk events and a higher total cost of risk response.Practical implicationsThis research provides contractors with an effective decision-making model to develop a project risk response plan, and it will assist contractors to minimize risk losses and enhance the project performance in the international construction market.Originality/valuePrevious studies overlook the risk preference, which is an important behavioral factor influencing decisions in risk response strategy selection. This research proposed a novel risk response strategy selection decision method that considers different attitudes toward risk among decision makers.

Analyzing the Trade-Offs between Meeting Biorefinery Production Capacity and Feedstock Supply Cost: A Chance Constrained Approach

Commercial-scale switchgrass production for cellulosic biofuel remains absent in U.S. A well-recognized difficulty is the steady provision of high-quality feedstock to biorefineries. Switchgrass yield is random due to weather and growing conditions, with low yields during establishment years. Meeting biorefinery production capacity requirements 100% of the time or at any other frequency requires contracting sufficient amount of agricultural land areas to produce feedstock. Using chance-constrained programming, the trade-offs between the degree of certainty that refinery demand for feedstock and the cost of contracting production acreage is assessed. Varying the certainty from 60% to 95%, we find the costs of production, logistics and transportation ranged from 27% to 96% of the cost of 100% certainty. Investors and managers need to consider the cost of certainty of biomass acquisition when contracting for production acreage.