Ivo Bouwmans

Agent-Based Control of Distributed Electricity Generation with Micro Combined Heat and Power: Cross-Sectoral Learning for Process and Infrastructure Engineers

For the distributed control of an electricity infrastructure incorporating clusters of residential combined heat and power units (micro-CHP or ?CHP) a Multi-Agent System approach is considered. The network formed by households generating electricity with ?CHP units and the facilitating energy supplier can be regarded as an electricity production system, analogous to a (flexible) manufacturing system. Next, the system boundary is extended by allowing the trade of electricity between networks of households and their supplier. A methodology for designing an agent-based system for manufacturing control is applied to both cases, resulting in a conceptual design for a control system for the energy infrastructure. Because of the analogy between production systems and infrastructures Process Systems Engineering (PSE) approaches for optimisation and control can be applied to infrastructure system operations. At the same time we believe research on socio-technical infrastructure systems will be a valuable contribution to PSE management strategies.

Socio-Technical Complexity in Energy Infrastructures Conceptual Framework to Study the Impact of Domestic Level Energy Generation, Storage and Exchange

Household level energy conversion, storage and exchange technologies are assumed to pervade the energy infrastructure in the future. These novel technologies will influence the total infrastructure in a bottom-up way; both technically and socially. Not only the physical networks, but also the social actor network consisting of households, network managers, energy suppliers and producers is influenced. This paper describes and conceptualizes a complex systems approach towards energy infrastructures based on a large penetration of decentralized technologies. Households thereby contain an energy hub; an interface between a number of energy sources and loads. Households can interact with each other and with other actors via their hubs. Our approach paves the way for modelling the socio-technical complexity via agent-based modelling (ABM) and for subsequent exploratory simulations.

Innovation in networked infrastructures: coping with complexity

Institutional and technological changes concerning networked infrastructures, and increasing interdependency between these infrastructures necessitate a different view on their design and management. Responsibilities are no longer in one hand as they often used to be, and failures in systems may impact larger parts of the infrastructures, leading to serious service disruptions. This paper describes the research framework that is being developed within the Next Generation Infrastructures research programme, to cope with the increasing complexity.

Deciding on Micro-CHP; A Multi-Level Decision-Making Approach

Micro combined heat and power (micro-CHP) is a promising, more fuel efficient, technology that could change the energy infrastructure as a whole. This paper describes the possible decision-making that results from micro-CHP introduction. The focus lies on the supplier-household interaction. Decisions made by supplier (price of electricity to/from households) influence decisions of households (1. micro-CHP power level and 2. amount of discharged heat) and determine the suppliers operational costs. When the supplier takes into account the cost optimization of households (that is based on the suppliers decision) in making his price-setting decisions, the problem can be described as a multi-level decision-making (MLDM) problem. We describe how the problem can be modelled and present a solution strategy which considers a combination of two objective functions that are subject to a set of constraints. Results of supplier price-setting are presented as well. Solving the problem via the MLDM approach is expected to lead to improved decision-making and a better performance of the supplier. Applying MLDM to the decision problem presented here is novel and can contribute to dealing with decision-making complexity in the energy infrastructure in general

Modelling an electricity infrastructure as a multi-agent system — Lessons learnt from manufacturing control

Abstract To model the control of an electricity infrastructure incorporating domestic level combined heat and power units (micro-CHP) a Multi-Agent System (MAS) approach is considered. This approach has already successfully been used to control manufacturing systems in the process industry. Because similarities between manufacturing and electricity generation exist it is interesting to investigate how a MAS methodology designed for manufacturing systems is applied to an electricity infrastructure. The interaction between energy companies and households is viewed here in a novel way, namely as a production process. By using an existing methodology for manufacturing control to design an agent-based controller for an electricity infrastructure, issues can be identified that have to be addressed in a control methodology specific for infrastructures.

Lessons Learned from Introducing a Skills Line into a Systems Engineering Curriculum

Academic skills refer to a broad set of capabilities that students need to acquire as part of their engineering program to be able to work effectively within a professional or scientific environment. Despite the importance, skills are underemphasized in many educational and engineering programs. In this paper the development of a new skills line within the System Engineering, Policy Analysis and Management (SEPAM) bachelor and master program is presented. The skills line in the bachelor program consists of nine different skills, in the categories: project skills, personal skills and academic skills. In contrast, the skills line of the master program focuses on a set of skills categorized into design, professional and academic skills. The introduction of the skills line has helped students not only to acquire the necessary skills, but external parties also better understand the program when the typical skills are presented. Evaluation results from an Alumni survey show that the skills are important to their current jobs and the skills are treated well in the program. It is important that the relationship between education and practice is explicitly addressed.

Improving short-term planning by incorporating scheduling consequences

Abstract Decisions in short-term planning and scheduling in multi-product multi-purpose plants are often taken in isolation from each other and may be based on conflicting objectives. This may results in decisions that are sub-optimal for the plant as a whole. A more integral perspective on the decision-making could lead to a better overall performance. This paper describes a mathematical reformulation of the short-term planning and scheduling decisions in a bi-level top-down program. It is based on a recursive formula and a smart definition of the cutting rules, which greatly reduces the complexity of the optimization. A practical case shows that the reliability of the planning results increases significantly.

Supporting the electricity network operator in the allocation process

In the current design of the electricity sector in the Netherlands, network operators daily receive data from measurement companies about the electricity consumption of their customers for each quarter of an hour. The network operator sorts the data per combination of Program Responsible Party (PRP) and network district region and sends the allocated data to the PRPs. The measurement series sometimes appear to contain errors. These errors need to be corrected in a short time. To avoid forwarding wrong data to the PRPs, the network operator would like to check the data on errors before they are sent. This paper shows that the electricity consumption can easily be predicted because the first-order autocorrelation of the data is very high. A simple prediction method is compared with the use of exponential smoothing models which give only slightly better results at best, but are much more complex to use.

Dealing with complexities in networked systems

Infrastructures are of vital importance for our society. They constitute the backbone of the economic and spatial structure, the nerve system that enables communication, and the arterial and digestive systems that supply and transform vital energy and material flows. It is not until recently that our trust in the adequacy and robustness of our infrastructures to meet present and future needs has started to crumble, as we have become more conscious of their critical role. Terrorist attacks; Internet viruses and large-scale power blackouts have contributed to a new awareness of the crucial need to ensure the well functioning of OUI infrastructures. However, various types of complexity found in infrastructure systems limit our understanding of infrastructures and their dynamic behaviour, and our options to control and steer that behaviour.