Hybrid agent-based simulation for policy evaluation of solar power generation systems

To encourage the adoption of solar power as well as new technological improvements in solar industry, state and federal governments have employed various kinds of incentives over the past decades, such as rebates, tax return opportunities, and Net Metering credits. At the same time, however, the governments concern regulations to avoid highly steep growth of solar energy without considering necessary supporting structure such as storage components, which will increase the electricity price and threaten the stability of existing transmission systems. The goal of this research is to develop a decision support tool to analyze the effectiveness of various policies (both incentives as well as regulations) on the proper growth rate of distributed photovoltaic (PV) systems avoiding the instability of the transition system or steep rising of the electricity price. To this end, we propose a hybrid two-level simulation modeling framework, which is significantly more detailed than the simplified structures commonly used in most policy evaluations. The lower-level model concerns the calculation of PV system payback period of individual household based on hourly electricity generation (PV) and consumptions, incentive levels, PV module price, and hourly electricity price (grid). The higher-level model, running on a weekly basis for 20 years, concerns the household adoption behaviors of the PV systems influenced by various factors, including payback period, household income, word-of-mouth effect and advertisement effect. Agent-based and system dynamics modeling techniques are leveraged in both levels. The proposed models have been developed for residential areas at two different regions in the US based on real data, which have been used to illustrate the impact of policies in different regions.     

Hybrid neuro-swarm optimization approach for design of distributed generation power systems

The global energy sector faces major challenges in providing sufficient energy to the worlds ever-increasing energy demand. Options to produce greener, cost effective, and reliable source of alternative energy need to be explored and exploited. One of the major advances in the development of this sort of power source was done by integrating (or hybridizing) multiple different alternative energy sources (e.g., wind turbine generators, photovoltaic cell panels, and fuel-fired generators, equipped with storage batteries) to form a distributed generation (DG) power system. However, even with DG power systems, cost effectiveness, reliability, and pollutant emissions are still major issues that need to be resolved. The model development and optimization of the DG power system were carried out successfully in the previous work using particle swarm optimization (PSO). The goal was to minimize cost, maximize reliability, and minimize emissions (multi-objective function) subject to the requirements of the power balance and design constraints. In this work, the optimization was performed further using Hopfield neural networks (HNN), PSO, and HNN-PSO techniques. Comparative studies and analysis were then carried out on the optimized results.     

Evaluation of solar aided biomass power generation systems with parabolic trough field

Solar and biomass are both renewable energy resources.Using biomass as fuel is becoming more and more attractive after governments increase the tariff for the electricity from the renewable sources.However the costs of power from a biomass power generation plant depend greatly on the availability and quality of the biomass resource.The commercialization of solar alone thermal power generation is hindered by its high initial investment and low thermal efficiency.In this paper,a concept of integrating solar i...     

太阳能热发电蓄热系统的混杂建模与仿真

蓄热系统是太阳能热发电站中保证电站可靠性和经济性的重要组成部分,其工作状况直接影响到太阳能热发电站的正常运行。本文针对单罐式蓄热系统,分析了系统在蓄热和放热模式下的动态数学模型,在此基础上,提出了蓄热系统的混杂动态系统模型。该模型将蓄热和放热模式统一在一个框架下,能够对蓄热系统的各种操作模式及其循环交替过程进行动态模拟。混杂模型采用MATLAB软件进行仿真,仿真结果:表明了模型的有效性。     

Hybrid least-squares algorithms for approximate policy evaluation

The goal of approximate policy evaluation is to “best” represent a target value function according to a specific criterion. Different algorithms offer different choices of the optimization criterion. Two popular least-squares algorithms for performing this task are the Bellman residual method, which minimizes the Bellman residual, and the fixed point method, which minimizes the projection of the Bellman residual. When used within policy iteration, the fixed point algorithm tends to ultimately find better performing policies whereas the Bellman residual algorithm exhibits more stable behavior between rounds of policy iteration. We propose two hybrid least-squares algorithms to try to combine the advantages of these algorithms. We provide an analytical and geometric interpretation of hybrid algorithms and demonstrate their utility on a simple problem. Experimental results on both small and large domains suggest hybrid algorithms may find solutions that lead to better policies when performing policy iteration.     

A systematic approach for new service concept generation: Application of agent-based simulation

In new service development (NSD), a concept design that influences the direction of other activities is considered as a crucial stage. Although several methods exist, most of them cannot reflect responses of future potential customers because they assume that customers have the same responses in the future. Therefore, by using agent-based simulation (ABS) that can understand the future status of a service system, this paper suggests a new approach to creating the most promising service concept. The proposed approach considers the future trends of various customer responses and service concept strategies of firms by using ABS, generating a more accurate concept. By applying the suggested approach to a healthcare industry, its practicability and utility are verified. The novel approach based on the agent-based simulation method, which has customer, service provider, and competitor agents, is expected to be useful for service providers in a competitive market.     

Designing a benchmark for the performance evaluation of agent-based simulation applications on HPC

The Journal of Supercomputing - Agent-based modeling and simulation (ABMS) is a class of computational models for simulating the actions and interactions of autonomous agents with the goal of...     

Hybrid modeling of central receiver solar power plants

With the forecast exhaustion of fossil fuels, governments are promoting renewable power plants as a viable alternative for electricity generation. One of the disadvantages of this kind of power generation facilities is the need to have a backup fuel, because the primary renewable resource is uncontrollable and discontinuous. From a modeling point of view, a power station with more than one source of supply changes its dynamical behavior according to Boolean events, thus mixing continuous and discrete dynamics in the system. The main contribution of this work is the modeling of a renewable power plant with two energy sources using a Mixed Logical Dynamical (MLD) representation, which is a modeling tool for the representation of hybrid systems. The advantages of using this modeling approach are discussed in the paper.     

H∞ switching fuzzy control of solar power generation systems with asymmetric input constraint

This paper aims at presenting a maximum power point tracking (MPPT) controller for photovoltaic (PV) systems subject to asymmetric input constraint. Indeed, the output voltage of the DC‐DC converter used for adjusting the photovoltaic output power can be controlled by means of variation of duty ratio limited between 1 and 0. The control design goal is to improve the efficiency of PV systems under asymmetric saturation of duty ratio. To achieve this goal, first, a Takagi‐Sugeno (T‐S) fuzzy model is used to represent the nonlinear behavior of the PV system. A T–S reference model is employed to give the ideal state direction which must be followed. To achieve a good steady state tracking, the integral of the state tracking error is used to define an extended system state vector. Second, the input characteristic is partitioned into several regions. In each region, the asymmetric saturation function can be considered as a symmetric saturation function. Furthermore, H∞ stabilization conditions for the resulting switching fuzzy control of the PV system under actuator saturation are formulated in term of linear matrix inequalities (LMI) using the Lyapunov approach. Simulation results are exhibited to demonstrate the effectiveness of the proposed design method.     

Multi-driver agent-based traffic simulation systems for evaluating the effects of advanced driver assistance systems on road traffic accidents

A recent investigation revealed that there is a substantiated need for the development of a micro-simulation system designed for traffic safety assessment. This paper describes the development of a road traffic simulation system, which uses a ‘nanoscopic model’ of driver behaviour and an integrated analysis-evaluation system designed for traffic safety assessment. The primary focus is on estimating the effects of an advanced driver assistance system thereby reducing traffic accidents. The effectiveness and validity of the present system are demonstrated through comparison with measured traffic data. This paper also proposes algorithms embedded in a ‘driver-agent’, for recognising driver’s intentions regarding choosing steering-control modes, lateral control tasks, and the driving mood. This is because the driver assistance systems need to recognise the driver’s intention when choosing steering-control. The results of a simulation study, using the data drawn from actual driving, show that the systems would achieve a high recognition capability. As an example of how driving mood recognition applies to driver assistance systems, an advanced steering system and the adaptability to the driver’s mood, have also been presented.     

多起重机节能混杂系统模型及其仿真*

为了保证多起重机节能系统中设备的正常运行并取得较好节能效果,构造多起重机节能系统的等效电路,针对系统复杂难以建模问题,引入混杂系统理论,建立基于混杂自动机的电网整流装置模型,将离散事件活动周期图建模方法推广至混杂系统构建受控功率源的活动周期图模型,从而得到系统整体模型。仿真研究了系统直流母线的功率和电压,验证了所建模型的合理性。为更深入地开展多电机节能系统的研究提供仿真平台。     

Hybrid simulation of adaptive open loop control for parabolic systems

The “adaptive open loop control” is a compromise between the open loop and the closed loop controls. It consists in estimating the state of the system periodically in such a way that the control can be corrected, taking into account the estimated state, the final desired state and the criterion to be minimized. For a hybrid simulation, a linear parabolic system has been considered, with homogeneous boundary conditions and unknown initial condition. The purpose is to reach, in a finite time, a desired state profile, by minimising an energy criterion. The control is applied through a finite number of actuators (pointwise or by zones); the observation is made through a finite number of sensors. By using the eigenfunction method, it is possible to transform the original model into an infinite dimension set of decoupled ordinary differential equations. A hybrid simulation was carried out in real time, involving a truncated differential system simulated on the analog computer; the state estimation and the control being computed on the digital computer.     

Methods for a network design problem in solar power systems

We consider the problem of minimizing cable connections between a central computer and a field of heliostats in the design of solar power systems. This practical task can be modeled as a p-median problem with additional constraints in a weighted graph. We compare an exact branch-and-bound method with two approximate algorithms. For the latter two methods, estimations of time complexity and accuracy are presented. Computational results are shown which should be useful in the design of such large-scale power systems.     

Experimental investigation on a parabolic trough solar collector for thermal power generation

Developing solar thermal power technology in an effective manner is a great challenge in China.In this paper an experiment platform of a parabolic trough solar collector system(PTCS) was developed for thermal power generation,and the performance of the PTCS was experimentally investigated with synthetic oil as the circulate heat transfer fluid(HTF).The solar collector's efficiency with the variation of the solar flux and the flow rate of the HTF was identified.The collector efficiency of the PTCS can be in ...     

Performance evaluation for manufacturing systems under control-limit maintenance policy

Maintenance decision-making in large manufacturing systems is complex as it requires the integration of various information. A control-limit policy is popular in practice, where maintenance is carried out when the degradation state of a machine reaches a threshold value. In this paper, by developing a framework based on discrete-time Markov chain models, we evaluate the system performance under the control-limit policy, in manufacturing systems that consist of multi-state machines and intermediate buffers. An exact analysis is performed for a two-machine-one-buffer system and an approximation method based on system decomposition is developed for multi-stage systems. Both steady-state and transient performance is analyzed. Numerical examples are presented to demonstrate the accuracy of the proposed method and the impact of different parameters (e.g., buffer capacity, uncertainty in the maintenance duration) on the system performance.     

Towards a theory of delegation for agent-based systems

In this paper a theory of delegation is presented. There are at least three reasons for developing such a theory. First, one of the most relevant notions of “agent” is based on the notion of “task” and of “on behalf of”. In order to found this notion a theory of delegation among agents is needed. Second, the notion of autonomy should be based on different kinds and levels of delegation. Third, the entire theory of cooperation and collaboration requires the definition of the two complementary attitudes of goal delegation and adoption linking collaborating agents.

After motivating the necessity for a principled theory of delegation (and adoption) the paper presents a plan-based approach to this theory. We analyze several dimensions of the delegation/adoption (on the basis of the interaction between the agents, of the specification of the task, of the possibility to subdelegate, of the delegation of the control, of the help levels). The agent's autonomy and levels of agency are then deduced. We describe the modelling of the client from the contractor's point of view and vice versa, with their differences, and the notion of trust that directly derives from this modelling.

Finally, a series of possible conflicts between client and contractor are considered: in particular collaborative conflicts, which stem from the contractor's intention to help the client beyond its request or delegation and to exploit its own knowledge and intelligence (reasoning, problem solving, planning, and decision skills) for the client itself.     

Automated test generation and evaluation for real-time expert systems

This paper describes a method for automated test generation and evaluation for real-time expert systems. This method supports dynamic testing, where test inputs are generated randomly within the constraints specified by a Test Specification Language. This allows the discovery of “unintended functionalities,” which may not be possible either through static testing or expert-supplied test cases. Automated test generation also allows rapid regeneration of test suites as the system evolves through various prototypes and versions. the Test Specification Language provides constructs for dealing with real-time constraints. Sample specifications and results implemented within the Activation Framework software development tool are also described. © 1994 John Wiley & Sons, Inc.