Designing and managing ERP systems for virtual enterprise strategy:a conceptual framework for innovative strategic thinking

The business environment today is transforming towards a collaborative context compounded by multi-organizational cooperation and related information system infrastructures. This chapter aims to examine Enterprise Resource Planning (ERP) systems development and emerging practices in the management of multi-organizational enterprises and identify the circumstances under which the so-called ‘ERPIII' systems fit into the Virtual Enterprise paradigm; and vice versa. An empirical inductive study was conducted using case studies from successful companies in the UK and China. Data were collected through 48 semi-structured interviews and analyzed using the Grounded-Theory based Methodology (GTM) to derive a set of 29 tentative propositions which were then validated via a questionnaire survey to further propose a novel conceptual framework referred to as the ‘Dynamic Enterprise Reference Grid for ERP (DERG-ERP)'; which can be used for innovative decision-making about how ERP information systems and multi-organizational enterprises – particularly the Virtual Enterprise may be co-developed

Online-Computation Approach to Optimal Control of Noise-Affected Nonlinear Systems with Continuous State and Control Spaces

© 2007 EUCA.A novel online-computation approach to optimal control of nonlinear, noise-affected systems with continuous state and control spaces is presented. In the proposed algorithm, system noise is explicitly incorporated into the control decision. This leads to superior results compared to state-of-the-art nonlinear controllers that neglect this influence. The solution of an optimal nonlinear controller for a corresponding deterministic system is employed to find a meaningful state space restriction. This restriction is obtained by means of approximate state prediction using the noisy system equation. Within this constrained state space, an optimal closed-loop solution for a finite decision-making horizon (prediction horizon) is determined within an adaptively restricted optimization space. Interleaving stochastic dynamic programming and value function approximation yields a solution to the considered optimal control problem. The enhanced performance of the proposed discrete-time controller is illustrated by means of a scalar example system. Nonlinear model predictive control is applied to address approximate treatment of infinite-horizon problems by the finite-horizon controller

Integrating Energy Storage into the Smart Grid: A Prospect Theoretic Approach

In this paper, the interactions and energy exchange decisions of a number of geographically distributed storage units are studied under decision-making involving end-users. In particular, a noncooperative game is formulated between customer-owned storage units where each storage unit's owner can decide on whether to charge or discharge energy with a given probability so as to maximize a utility that reflects the tradeoff between the monetary transactions from charging/discharging and the penalty from power regulation. Unlike existing game-theoretic works which assume that players make their decisions rationally and objectively, we use the new framework of prospect theory (PT) to explicitly incorporate the users' subjective perceptions of their expected utilities. For the two-player game, we show the existence of a proper mixed Nash equilibrium for both the standard game-theoretic case and the case with PT considerations. Simulation results show that incorporating user behavior via PT reveals several important insights into load management as well as economics of energy storage usage. For instance, the results show that deviations from conventional game theory, as predicted by PT, can lead to undesirable grid loads and revenues thus requiring the power company to revisit its pricing schemes and the customers to reassess their energy storage usage choices.Comment: 5 pages, 4 figures, conferenc