An Integrated Market for Electricity and Natural Gas Systems with Stochastic Power Producers

In energy systems with high shares of weather-driven renewable power sources, gas-fired power plants can serve as a back-up technology to ensure security of supply and provide short-term flexibility. Therefore, a tighter coordination between electricity and natural gas networks is foreseen. In this work, we examine different levels of coordination in terms of system integration and time coupling of trading floors. We propose an integrated operational model for electricity and natural gas systems under uncertain power supply by applying two-stage stochastic programming. This formulation co-optimizes day-ahead and real-time dispatch of both energy systems and aims at minimizing the total expected cost. Additionally, two deterministic models, one of an integrated energy system and one that treats the two systems independently, are presented. We utilize a formulation that considers the linepack of the natural gas system, while it results in a tractable mixed-integer linear programming (MILP) model. Our analysis demonstrates the effectiveness of the proposed model in accommodating high shares of renewables and the importance of proper natural gas system modeling in short-term operations to reveal valuable flexibility of the natural gas system. Moreover, we identify the coordination parameters between the two markets and show their impact on the system's operation and dispatch

An Agent-Based Simulation for Water Sharing Between Different Users

Water sharing has become a serious problem in France. One of the objectives of 1992 and 2000 directives proposed by the European Union was to reduce both the frequency and the extent of water conflicts through the establishment of multilateral negotiations, where different public and private interests can be represented in a structured institutional environment. In France, many negotiations take place at local level between farmers, water supplies, public services and environmental lists to allocate water resources between users. We suggest that Agent-Based Modelling (ABM) using a multi-agent approach could help negotiations between different players by showing the consequences of water allocation rules and taking in consideration the players' respective attitudes and their ability to change their behaviour.Multiagent-based simulation, user and agent modelling, conflict resolution and negotiation, irrigation application, Resource /Energy Economics and Policy,

A Study of Neighborhood Level Effects on the Likelihood of Reporting to the Police

Research on reporting crime to the police on the individual- and incident- levels has received much attention over the years. However, many studies examining neighborhood-level effects on reporting are limited in scope. The current study examines the relationship between neighborhood characteristics central to social disorganization theory and police notification. Data for this study were derived from Warner’s (2004) study entitled “Informal Social Control of Crime in High Drug Use Neighborhoods in Louisville and Lexington, Kentucky, 2000.” The analysis uses OLS regression models to isolate how different neighborhood characteristics impact reporting. Findings indicate that disadvantage and mobility have a positive effect on reporting but are mediated by social cohesion. Social cohesion has a negative effect on reporting while confidence in police had no significant effects. Suggestions for future research are also discussed

Dakota Sioux objects

This article is a study of certain syntactic and morphological processes in Dakota Sioux within the Relational Grammar framework. There are three main topics dealt with as they relate to verb agreement: advancements to direct object, Possessor Ascensions, and Clause Union. All three of these topics distinguish between direct objects, indirect objects and obliques. Verb agreement is examined and shown to consist of two distinct systems: person agreement and number agreement. These two systems give empirical evidence to the support of the multilevel relational network of Unaccusative and Reflexive clauses. It is also shown that an analysis which posits advancements to direct object allows for concise generalizations, whereas an analysis which does not include advancement to direct object cannot capture these generalizations. There are two types of Possessor Ascension attested cross-linguistically: one in which the possessor assumes the grammatical relation of the host, and one in which the possessor assumes a grammatical relation other than the host. This article shows that Dakota Sioux has both constructions. The last topic dealt with is Clause Union, in particular Causative Union. This article presents evidence that a union construction in Sioux is superficially monoclausal yet contains two predicates. After the evidence for the multipredicate clause is presented, verb agreement is again examined since both predicates may show person and number agreement

Using conditional kernel density estimation for wind power density forecasting

Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind power generation. However, most research has focused on point forecasting of wind power. In this paper, we develop an approach to producing density forecasts for the wind power generated at individual wind farms. Our interest is in intraday data and prediction from 1 to 72 hours ahead. We model wind power in terms of wind speed and wind direction. In this framework, there are two key uncertainties. First, there is the inherent uncertainty in wind speed and direction, and we model this using a bivariate VARMA-GARCH (vector autoregressive moving average-generalized autoregressive conditional heteroscedastic) model, with a Student t distribution, in the Cartesian space of wind speed and direction. Second, there is the stochastic nature of the relationship of wind power to wind speed (described by the power curve), and to wind direction. We model this using conditional kernel density (CKD) estimation, which enables a nonparametric modeling of the conditional density of wind power. Using Monte Carlo simulation of the VARMA-GARCH model and CKD estimation, density forecasts of wind speed and direction are converted to wind power density forecasts. Our work is novel in several respects: previous wind power studies have not modeled a stochastic power curve; to accommodate time evolution in the power curve, we incorporate a time decay factor within the CKD method; and the CKD method is conditional on a density, rather than a single value. The new approach is evaluated using datasets from four Greek wind farms

Calculating Launch Vehicle Flight Performance Reserve

This paper addresses different methods for determining the amount of extra propellant (flight performance reserve or FPR) that is necessary to reach orbit with a high probability of success. One approach involves assuming that the various influential parameters are independent and that the result behaves as a Gaussian. Alternatively, probabilistic models may be used to determine the vehicle and environmental models that will be available (estimated) for a launch day go/no go decision. High-fidelity closed-loop Monte Carlo simulation determines the amount of propellant used with each random combination of parameters that are still unknown at the time of launch. Using the results of the Monte Carlo simulation, several methods were used to calculate the FPR. The final chosen solution involves determining distributions for the pertinent outputs and running a separate Monte Carlo simulation to obtain a best estimate of the required FPR. This result differs from the result obtained using the other methods sufficiently that the higher fidelity is warranted