Development and demonstration of a renewable energy based demand/supply decision support tool for the building design profession

Future cities are likely to be characterised by a greater level of renewable energy systems deployment. Maximum impact will be achieved when such systems are used to offset local energy demands in contrast to current philosophy dictating the grid connection of large schemes. This paper reports on the development of a software tool, MERIT, for demand/ supply matching. The purpose of MERIT is to assist with the deployment of renewable energy systems at all scales. This paper describes the procedures used to match heterogeneous supply technologies to a set of demand profiles corresponding to the different possible fuel types

The bullhead Cottus gobio , a versatile and successful fish

A series of studies on the ecology of the bullhead, Cottus gobio is described. Habitat choice, growth rate and longevity, population density, biomass and production, reproduction, life history and feeding is compared at 8 sites in England and 1 site in Wales. Evidence suggests that in Cottus gobio the prevailing environmental conditions result in considerable modifications in longevity, growth rate and egg production. It also indicates that the advantages of fast growth and high reproductive effort in favourable habitats are offset, at least partially by increases in mortality

Mathematical algorithm to transform digital biomass distribution maps into linear programming networks in order to optimize bio-energy delivery chains

Many linear programming models have been developed to model the logistics of bio-energy chains. These models help to determine the best set-up of bio-energy chains. Most of them use network structures built up from nodes with one or more depots, and arcs connecting these depots. Each depot is source of a certain biomass type. Nodes can also be a storage point for a certain biomass type or a production facility (e.g. power plant) where the biomass is used. Arcs represent transport between depots. To be able to combine GIS spatial studies with linear programming models it is necessary to build a network from a digital map. In this work a mathematical calculation method is developed to select the actual points on the map where to collect biomass that will then be considered as biomass sources in a network model

Development of a simulation-based decision support tool for renewable energy integration and demand-supply matching

This paper describes a simulation-based decision support tool, MERIT, which has been developed to assist in the assessment of renewable energy systems by focusing on the degree of match achievable between energy demand and supply. Models are described for the prediction of the performance of PV, wind and battery technologies. These models are based on manufacturers' specifications, location-related parameters and hourly weather data. The means of appraising the quality of match is outlined and examples are given of the application of the tool at the individual building and community levels

PROCUREMENT PROCESS IN POWER ENERGY ENTERPRISE

The supply and procurement processes are extremely important for properfunctioning of power plants, especially for continuous production process because anybreaks have negative effects on the costs linked to idle time.supply management, procurement process

Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

In this work, we have attempted to solve two problems concerning the planning and scheduling of crude oil operations: first, on the upstream production planning of crude oil from offshore sources and second, on the scheduling of downstream processing of crude oil at the refinery front-end. The first part is on the offshore oilfield infrastructures planning under both exogenous uncertainty and endogeneous decision-dependent uncertainty. A model representative of the oilfield that is able to select the best routes to obtain the desired objective function is considered. The methodology used is by firstly developing a deterministic model andmodeling it with GAMS, followed by a stochastic one. The results obtained show a high accuracy representation in which the uncertainties in both the exogenous and endogeneous uncertainties in planning are accounted for. The stochastic model is a more thorough representation of the problem because it considers all the uncertainties along with the associated probabilities. Having validated the model formulation and solution obtained with results for standard problems reported in the literature, we believe that the model can be a tool to assist upper-level management in preliminary decision-making on an optimal plan for crude oil production from an offshore operation. The second part is onthe scheduling of crude oiloperations at a refinery front-end. A technique for obtaining globally optimal schedules for the flow of crude is developed. Acontinuous time model based on transfer events is used to represent the scheduling problem and this model is a nonconvex MINLP model which presents multiple local optima. We implement a branch-and-contract algorithm that aims at reducing the size of the search region. In order to obtain a global optimum solution of the problem, an outer-approximation algorithm is proposed, whereby lower and upper bounds on the global optimum are generated, which are converged to a specified tolerance. The solution obtained from the LB-MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB-NLP. This solution is the upper bound solution. The application of the proposed algorithm shows significant reduction in the computational effort involved in solving the problem. Slack variables are introduced to overcome the integer infeasibility problem. The optimization model is developed using GAMS and an optimal solution is found with no logical constraints conflicts or error. The main contribution on this work in the first part is to conduct an extensive study onthe implementation ofthe model formulation in Iyer et al. (1998). As well, in the second part, we are focused on investigating effective implementation strategies of the model formulation and solution strategy in Karuppiah et al. (2008) using our choice of the modeling platform GAMS and the best numerical solvers that are available. Hence, most of the exposition on the model formulation and solution algorithms are taken directly from the original papers so as to provide the readers with the most accurate information possible. V

Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

In this work, we have attempted to solve two problems concerning the planning and scheduling of crude oil operations: first, on the upstream production planning of crude oil from offshore sources and second, on the scheduling of downstream processing of crude oil at the refinery front-end. The first part is on the offshore oilfield infrastructures planning under both exogenous uncertainty and endogeneous decision-dependent uncertainty. A model representative of the oilfield that is able to select the best routes to obtain the desired objective function is considered. The methodology used is by firstly developing a deterministic model and modeling it with GAMS, followed by a stochastic one. The results obtained show a high accuracy representation in which the uncertainties in both the exogenous and endogeneous uncertainties in planning are accounted for. The stochastic model is a more thorough representation of the problem because it considers all the uncertainties along with the associated probabilities. Having validated the model formulation and solution obtained, we believe that the model can be a useful basic tool to assist upper-level management in deciding on an optimal plan for crude oil production from an offshore operation. The second part is on the scheduling of crude oil operations at a refinery front-end. A technique for obtaining globally optimal schedules for the flow of crude is developed. A continuous time model based on transfer events is used to represent the scheduling problem and this model is a nonconvex MINLP model which presents multiple local optima. We implement a branch-and-contract algorithm that aims at reducing the size of the search region. In order to obtain a global optimum solution of the problem, an outer-approximation algorithm is proposed, whereby lower and upper bounds on the global optimum are generated, which are converged to a specified tolerance. The solution obtained from the LB–MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB–NLP. This solution is the upper bound solution. The application of the proposed algorithm shows significant reduction in the computational effort involved in solving the problem. Slack variables are introduced to overcome the integer infeasibility problem. The optimization model is developed using GAMS and an optimal solution is found with no logical constraints conflicts or error. The main contribution on this work in the first part is to conduct an extensive study on the implementation of the model formulation in Iyer et al. (1998). As well, in the second part, we are focused on investigating effective implementation strategies of the model formulation and solution strategy in Karuppiah et al. (2008) using our choice of the modeling platform GAMS and the best numerical solvers that are available. Hence, most of the exposition on the model formulation and solution algorithms are taken directly from the original papers so as to provide the readers with the most accurate information possible

A synthetic biochemistry platform for cell free production of monoterpenes from glucose.

Cell-free systems designed to perform complex chemical conversions of biomass to biofuels or commodity chemicals are emerging as promising alternatives to the metabolic engineering of living cells. Here we design a system comprises 27 enzymes for the conversion of glucose into monoterpenes that generates both NAD(P)H and ATP in a modified glucose breakdown module and utilizes both cofactors for building terpenes. Different monoterpenes are produced in our system by changing the terpene synthase enzyme. The system is stable for the production of limonene, pinene and sabinene, and can operate continuously for at least 5 days from a single addition of glucose. We obtain conversion yields >95% and titres >15 g l-1. The titres are an order of magnitude over cellular toxicity limits and thus difficult to achieve using cell-based systems. Overall, these results highlight the potential of synthetic biochemistry approaches for producing bio-based chemicals