Business cycle asymmentries: An investment cost approach

In this paper, investment cost asymmetry is introduced in order to test wheter this kind of asymmetry can account for asymmetries in business cycles. By using a smooth transition function, asymmetric investment cost is modeled and introduced in a canonical RBC model. Simulations of the model with Perturbations Method (PM) are very close to simulations through Parameterized Expectations Algorithm (PEA), which allows the use of the former for the sake of time reduction and computational costs. Both symmetric and asymmetric models were simulated and compared. Deterministic and stochastic impulse-response excersices revealed that it is possible to adequately reproduce asymmetric business cycles by modeling asymmetric investment costs. Simulations also showed that higher order moments are insu_cient to detect asymmetries. Instead, methods such as Generalized Impulse Response Analysis (GIRA) and Nonlinear Econometrics prove to be more e_cient diagnostic tools.

Randomised controlled trial comparing hospital at home care with inpatient hospital care. II: cost minimisation analysis

Objectives: To examine the cost of providing hospital at home in place of some forms of inpatient hospital care.

Hospital at home or acute hospital care? A cost minimisation analysis

Objective: To compare, from the viewpoints of the NHS and social services and of patients, the costs associated with early discharge to a hospital at home scheme and those associated with continued care in an acute hospital.

Optimisation of environmental gas cleaning routes for solid wastes cogeneration systems. Part II - Analysis of waste incineration combined gas/steam cycle

In the first paper of this paper (Part I), conditions were presented for the gas cleaning technological route for environomic optimisation of a cogeneration system based in a thermal cycle with municipal solid waste incineration. In this second part, an environomic analysis is presented of a cogeneration system comprising a combined cycle composed of a gas cycle burning natural gas with a heat recovery steam generator with no supplementary burning and a steam cycle burning municipal solid wastes (MSW) to which will be added a pure back pressure steam turbine (another one) of pure condensation. This analysis aims to select, concerning some scenarios, the best atmospheric pollutant emission control routes (rc) according to the investment cost minimisation, operation and social damage criteria. In this study, a comparison is also performed with the results obtained in the Case Study presented in Part I. (c) 2007 Elsevier Ltd. All rights reserved.

Reactive power planning under conditional-value-at-risk assessment using chance-constrained optimisation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Artisanal canoe fishing industry of the Rivers State: its economic viability and investment potentials

Consequent upon the present national call in Nigeria for all to go back to agriculture including fishing, most retrenched workers and unemployed youths from the riverine areas are taking up fishing as a legitimate and gainful livelihood. To sustain this tempo and attract more investment, the economic viability of such projects must be known. This study is an attempt to document the profitability and investment potential of artisanal canoe fishing. Socio-economic information including catches, operational cost and returns were obtained through a personal interview questionnaire survey of 240 randomly selected artisanal canoe fishermen from Bonny, Brass and Degema Local Government Areas (LGA) of the State and analyzed. With an investment cost of about 8,135, 8,490 and 6,571 and operation cost of 750, 776 and 627, the analysis showed an average monthly gross income of 1,869, 3,221 and 1,775 for the three local government areas respectively. A benefit-cost-ratio of 1:8, net present value of 400, 603 and internal rate of return greater than 50% were obtained. Since capital invested in fisheries is not tied up for long before benefits start flowing, coupled with the high IRR, it is concluded that artisanal canoe fishing would be an economically viable venture if well managed

Optimal Investment in Energy Efficiency under Uncertainty

41 p.

Interconnector Investment for a Well-Functioning Internal Market: What EU regime of regulatory incentives? Bruges European Economic Research (BEER) Papers 18/October 2010

Sufficient cross‐border electricity transmission infrastructure is a pre‐requisite for a functioning European internal market for electricity. Also, the achievement of the EU’s energy policy objectives – sustainability, competitiveness and security of supply – critically depends on adequate investment in physical interconnections between the member states. Mainly focusing on the “regulatory path”, this paper assesses different ways to achieve a sufficient level of interconnector investment. In a first step, economic analysis identifies numerous impediments to interconnector investment adding up to an “interconnector investment failure”. Reflecting on the proper regulatory design of an EU framework able to overcome the interconnector investment failure, a number of recommendations are put forward:  All congestion rents should be channeled into interconnector building. Unused rents should be transferred to a European interconnector fund supervised by an EU agency.  Even though inherently sub‐optimal, merchant transmission investment can be used as a means to put pressure on regulated transmission system operators (TSO) that do not deliver. An EU agency should have exclusive competence on merchant interconnector exemptions.  A European TSO organization should be entrusted with supra‐national network planning, supervised by an EU agency.  The agency should decide on investment cost reallocation for interconnector projects that yield strong externalities. Payments could be settled via a European interconnector fund.  In case of non‐compliance with the supra‐national network plan, the EU agency should have the right to organize a tender – financed by the European interconnector fund – in order to get the “missing link” built. Assessing the existing EU regulatory framework, the efforts of the 2009 “third energy package” to fill the “regulatory gap” with new EU bodies – ACER and ENTSO‐E – are acknowledged. However, striking holes in regulatory framework are spotted, notably with regard to the use of congestion rents, interconnector cost allocation, and the distribution of decision making powers on new infrastructure exemptions A discussion of the TEN‐E interconnector funding scheme shows that massive funding can be an interim solution to the problem of insufficient interconnection capacities while overcoming the political deadlock on sensible regulatory topics such as interconnector cost allocation. The paper ends with policy recommendations.

A new method for improving reliability and line loss in distribution networks

In this paper, both Distributed Generators (DG) and capacitors are allocated and sized optimally for improving line loss and reliability. The objective function is composed of the investment cost of DGs and capacitors along with loss and reliability which are converted to the genuine dollar. The bus voltage and line current are considered as constraints which should be satisfied during the optimization procedure. Hybrid Particle Swarm Optimization as a heuristic based technique is used as the optimization method. The IEEE 69-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate that the lowest cost planning is found by optimizing both DGs and capacitors in distribution networks.

Optimal control of distributed generators and capacitors by hybrid DPSO

In this paper, a comprehensive planning methodology is proposed that can minimize the line loss, maximize the reliability and improve the voltage profile in a distribution network. The injected active and reactive power of Distributed Generators (DG) and the installed capacitor sizes at different buses and for different load levels are optimally controlled. The tap setting of HV/MV transformer along with the line and transformer upgrading is also included in the objective function. A hybrid optimization method, called Hybrid Discrete Particle Swarm Optimization (HDPSO), is introduced to solve this nonlinear and discrete optimization problem. The proposed HDPSO approach is a developed version of DPSO in which the diversity of the optimizing variables is increased using the genetic algorithm operators to avoid trapping in local minima. The objective function is composed of the investment cost of DGs, capacitors, distribution lines and HV/MV transformer, the line loss, and the reliability. All of these elements are converted into genuine dollars. Given this, a single-objective optimization method is sufficient. The bus voltage and the line current as constraints are satisfied during the optimization procedure. The IEEE 18-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate the unavoidable need for optimal control on the DG active and reactive power and capacitors in distribution networks.

Planning of distribution networks for medium voltage and low voltage

Determination of the placement and rating of transformers and feeders are the main objective of the basic distribution network planning. The bus voltage and the feeder current are two constraints which should be maintained within their standard range. The distribution network planning is hardened when the planning area is located far from the sources of power generation and the infrastructure. This is mainly as a consequence of the voltage drop, line loss and system reliability. Long distance to supply loads causes a significant amount of voltage drop across the distribution lines. Capacitors and Voltage Regulators (VRs) can be installed to decrease the voltage drop. This long distance also increases the probability of occurrence of a failure. This high probability leads the network reliability to be low. Cross-Connections (CC) and Distributed Generators (DGs) are devices which can be employed for improving system reliability. Another main factor which should be considered in planning of distribution networks (in both rural and urban areas) is load growth. For supporting this factor, transformers and feeders are conventionally upgraded which applies a large cost. Installation of DGs and capacitors in a distribution network can alleviate this issue while the other benefits are gained. In this research, a comprehensive planning is presented for the distribution networks. Since the distribution network is composed of low and medium voltage networks, both are included in this procedure. However, the main focus of this research is on the medium voltage network planning. The main objective is to minimize the investment cost, the line loss, and the reliability indices for a study timeframe and to support load growth. The investment cost is related to the distribution network elements such as the transformers, feeders, capacitors, VRs, CCs, and DGs. The voltage drop and the feeder current as the constraints are maintained within their standard range. In addition to minimizing the reliability and line loss costs, the planned network should support a continual growth of loads, which is an essential concern in planning distribution networks. In this thesis, a novel segmentation-based strategy is proposed for including this factor. Using this strategy, the computation time is significantly reduced compared with the exhaustive search method as the accuracy is still acceptable. In addition to being applicable for considering the load growth, this strategy is appropriate for inclusion of practical load characteristic (dynamic), as demonstrated in this thesis. The allocation and sizing problem has a discrete nature with several local minima. This highlights the importance of selecting a proper optimization method. Modified discrete particle swarm optimization as a heuristic method is introduced in this research to solve this complex planning problem. Discrete nonlinear programming and genetic algorithm as an analytical and a heuristic method respectively are also applied to this problem to evaluate the proposed optimization method.

Optimal sitting and sizing of distributed generators considering plug-in electric vehicles

Some uncertainties such as the stochastic input/output power of a plug-in electric vehicle due to its stochastic charging and discharging schedule, that of a wind unit and that of a photovoltaic generation source, volatile fuel prices and future uncertain load growth, all together could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distributed systems. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal sitting and sizing problem of DGs. First, a mathematical model of CCP is developed with the minimization of DGs investment cost, operational cost and maintenance cost as well as the network loss cost as the objective, security limitations as constraints, the sitting and sizing of DGs as optimization variables. Then, a Monte Carolo simulation embedded genetic algorithm approach is developed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is employed to verify the feasibility and effectiveness of the developed model and method. This work is supported by an Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Project on Intelligent Grids Under the Energy Transformed Flagship, and Project from Jiangxi Power Company.