Two-settlement Systems for Electricity Markets under Network Uncertainty and Market Power

We analyze welfare and distributional properties of a two-settlement system consisting of a spot market over a two-node network and a single energy forward contract. We formulate and analyze several models which simulate joint dispatch of energy and transmission resources coordinated by a system operator. The spot market is subject to network uncertainty, which we model as a random capacity derating of an important transmission line. Using a duopoly model, we show that even for small probabilities of congestion (derating), forward trading may be substantially reduced, and the market power mitigating effect of forward markets (as shown in Allaz and Vila 1993) may be nullified to a great extent. There is a spot transmission charge reflecting transportation costs from location of generation to a designated hub whose price is the underlying for the forward contract. This alleviates some of the incentive problems associated with the forward market in which spot-market trading is residual. We find that the reduction in forward trading is due to the segregation of the markets in the constrained state, and the absence of natural incentives for generators to commit to more aggressive behavior in the spot market (the strategic substitutes effect). In our analysis, we find that the standard assumption of no-arbitrage across forward and spot markets leads to very little contract coverage, even for the case with no congestion. We present an alternative view of the market where limited intertemporal arbitrage enables temporal price discrimination by competing duopolists. In this framework, we assume that all of the demand shows up in the forward market (or that the market is cleared against an accurate forecast of the demand), and the forward price is determined using a market clearing condition.     

Automatic extraction of 1D barcodes from video scans for drone-assisted inventory management in warehousing applications

The widespread use of barcodes has significantly contributed to accurate, efficient and economic inventory management in warehouses and distribution centres. However, its efficiency has always been limited by the primary method of reading barcodes with a handheld laser scanner. Compared with this reading by line-of-sight at close proximity, vision-based barcode reading algorithms can further improve efficiency, particularly if accompanied by automated data collection platforms such as drones. This paper introduces algorithms that are able to automatically extract barcodes from video data, and verifies their feasibility and promise for inventory management in warehousing applications. Three key techniques corresponding to different recognition levels are proposed: For a known barcode region, a Harris corner detector and Hough transform-based algorithm is applied to quickly estimate the angle by which the frame area needs to rotate to orient the bars vertically for information extraction. Then, the idea of exploiting connectivity and geometry property of barcode areas is proposed to directly recognise multiple barcode regions in a single video frame to eliminate reading difficulties resulting from interactive influence of multiple juxtaposed barcodes, and to save computation time by only processing frame areas of interest for valid barcodes. In addition, a histogram difference-based fast extraction strategy is designed to further improve efficiency by reducing duplicate information processing. Finally, the performance of each technique is evaluated by analysing video data from a large logistics warehouse, demonstrating satisfactory performance in inventory management applications.     

Cost-effectiveness of aripiprazole once-monthly compared with paliperidone palmitate once-monthly injectable for the treatment of schizophrenia in the United States

Objective:

To develop a decision-analytic model to estimate the cost-effectiveness of initiating maintenance treatment with aripiprazole once-monthly (AOM) vs paliperidone long-acting injectable (PLAI) once-monthly among patients with schizophrenia in the US.

Methods:

A decision-analytic model was developed to evaluate a hypothetical cohort of patients initiating maintenance treatment with AOM or PLAI. Rates of relapse, adverse events (AEs), and direct medical costs were estimated for 1 year. Patients either remained on initial treatment or discontinued treatment due to lack of efficacy, AEs, or other reasons, including non-adherence. Data from placebo-controlled pivotal trials and product prescribing information (PI) were used to estimate treatment efficacy and AEs. Analyses were performed assuming dosing of clinical trials, real-world practice, PIs, and highest therapeutic dose available, because of variation in practice settings. The main outcome of interest was incremental cost per schizophrenia hospitalization averted with AOM vs PLAI.

Results:

Based on placebo-controlled pivotal trials’ dosing, AOM improved clinical outcomes by reducing schizophrenia relapses vs PLAI (0.181 vs 0.277 per person per year [pppy]) at an additional cost of US$1276 pppy, resulting in an incremental cost-effectiveness ratio (ICER) of US$13,280/relapse averted. When PI dosing was assumed, this ICER increased to US$19,968/relapse averted. When real-world dosing and highest available dosing were assumed, AOM was associated with fewer relapses and lower overall treatment costs vs PLAI.

Conclusions:

AOM consistently provided favorable clinical benefits. Under various dosing scenarios, AOM results indicated fewer relapses at lower overall costs or a reasonable cost-effectiveness threshold (i.e., less than the cost of a hospitalization relapse) vs PLAI. Given the heterogeneous nature of schizophrenia and variability in treatment response, health plans may consider open access for treatments like AOM. Since model inputs were based on data from separate placebo-controlled trials, generalization of results to the real-world setting is limited.     

Networks and farsighted stability

We provide a new framework for the analysis of network formation and demonstrate the existence of farsightedly consistent directed networks. Our framework extends the standard notion of a network and also introduces the notion of a supernetwork. A supernetwork is made up of a collection of directed networks (the nodes) and represents (via the arcs connecting the nodes) preferences and rules governing network formation. By extending Chwe's 1994 result on the nonemptiness of farsightedly consistent sets, we show that for any supernetwork there exists a nonempty subset of farsightedly consistent directed networks.     

Rational Buyer Meets Rational Seller: Reserves Market Equilibria under Alternative Auction Designs

We examine efficiency properties and incentive compatibility of alternative auction formats that an electricity network system operator may use for the procurement of ancillary services required for real-time operations. We model the procurement auction as a hierarchical multiproduct auction, and study several designs such as a uniform price auction minimizing revealed social cost, a uniform price auction minimizing the system operator's cost and a pay as bid auction minimizing revealed social cost. We take into account that rational bidders will respond to any market design so as to maximize their expected benefit from participating in that market. Under the assumptions of our model, we show that the uniform price auction minimizing revealed social cost is the only one that guarantees productive efficiency. We also find that expected revenue (payment in our case) equivalence between pay as bid and uniform price auctions does not extend to the hierarchical products case and the ranking of these auctions is ambiguous and depends on the data. For the procurement auction minimizing the system operator's cost, we show that misrepresentation of capability may result in capacity shortages if there are capacity constraints. For the case where only higher capability resources are constrained, this will result in random price spikes decreasing in frequency with the price cap (this is the amount paid to capacity in demand states with shortages). When lower type resources are capacity constrained as well, price spikes will be seen for both type of resources. Such artificial shortages result in reduced reliability in real-time operations.