William D'haeseleer

The impact of the implementation of cogeneration in a given energetic context

In order to evaluate the value of cogeneration, usually static-simplified criteria are used, neglecting the entire energetic context and the dynamic interaction between cogeneration and the centralized electric system. Therefore, a dynamic method, based on simulation of scenarios, is proposed. For a given demand for heat and electricity, two scenarios are worked out: a scenario where no additional cogeneration is installed and a scenario where cogeneration is added, possibly also resulting in a more moderate expansion of the central power system. To correctly portray the dynamic response of the central power system, it is simulated. The use of this method on concrete possibilities for cogeneration in Belgium, demonstrates the need for this dynamic method. For industrial cogeneration, the static simplified method seems valid because of the high and constant utilization of this form of cogeneration. In the case of cogeneration in the commercial sector, however, where the heat demand is only present during a limited period of time, the static method is not valid and the environmentally friendly nature of this kind of cogeneration is less obvious. As a general conclusion, it can be stated that every specific possibility for cogeneration has to be evaluated separately in its own overall energetic context, including the entire electricity generation system.

Demand Side Management in a competitive European market: who should be responsible for its implementation?

Abstract Demand side management (DSM), more specifically energy efficiency, is standing in the spotlight due to the Kyoto commitments. An additional factor, the liberalization of the electricity markets, causes every country to review its own DSM activities. Especially in Europe, where the directive for opening the electricity market has a direct impact on the current DSM frameworks, governments will have to consider a change in this framework. In order to achieve this, much research has been done in the past years on how to change the DSM framework in a way that the requirements of both liberalization and the Kyoto Protocol will be met. In this paper, we review the current DSM activities and ongoing research from the starting point ‘who should be responsible for implementing DSM’. We conclude that countries have to make explicit choices on how to arrange their DSM activities for the different customers groups. They have to be aware of the fact that some combinations of DSM activities will lead to counter-productive results and therefore inefficiency. This paper also investigates which of these DSM activities fits best in the open market; a critical review of Integrated Resource Planning (IRP) is used as a starting point. We agree with various proponents of IRP that planning towards minimal societal costs is theoretically appropriate, looking from a societal point of view. We also indicate in this paper that the planning process IRP is partly applicable in the open market. But looking at the practical application of IRP in the past, we must conclude that there are better alternatives for achieving energy efficient goals in a liberalized market.

A General Solution of the Ripple-Averaged Kinetic Equation (GSRAKE)

A general solution of the ripple-averaged kinetic equation, GSRAKE, is presented and used to investigate neoclassical transport in the model magnetic field of a simple stellarator. No assumptions are made as to the relative sizes of the collision frequency, nu , and poloidal precessional frequency, as, so that the solution is valid throughout the entire long-mean-free-path regime. Separate but fully self-consistent treatments of both localized and non-localized particles are provided; the interaction between these two classes of particles is accounted for through a set of appropriate physical boundary conditions. All drift terms present within the framework of the ripple-averaged theory are included; in particular, for localized particles Omega theta = Omega E+ Omega Del B is comprised of both the E*B and Del B precessional frequencies. The solution is thus equally valid in the Omega E>> Omega Del B and the Omega E=0 limits of standard neoclassical theory. A detailed comparison of results with those of the FLOCS code is undertaken; estimates of neoclassical transport coefficients obtained from several codes are also presented. Agreement of results is found in all of these comparisons, GSRAKE requiring but a tiny fraction of the computational time necessary for the other codes.

An evaluation method for calculating the emission responsibility of specific electric applications

Abstract The potential implementation of measures intended for energy-efficiency or environmental purposes (such as the prohibition of electric heating, peak shaving and the installation of cogeneration amongst others) necessitates quantification methods to accurately estimate their assumed impact. Therefore, in this paper, a tool and a methodology are created to simulate and evaluate electric demand- and supply-side options. This way, the responsibility of a proposed measure with regard to emissions and energy use can be quantified.Throughout the years, many (often conflicting) views on the use of electricity have been advanced. Sometimes it was/is claimed that electricity use should be stimulated because electricity is a relatively clean source of energy (especially in countries with a lot of renewables and/or nuclear energy). Others claim that electricity use should be discouraged because it would be more efficient to use the primary energy sources directly, without the intermediate conversion into electricity and the associated transmission and distribution losses. Mostly, these statements cannot be justified without a detailed analysis of the local energy system. To fully grasp the impact of demand-side measures it is important to understand that incremental changes in demand instantaneously only affect the activation of a limited amount of plants, whereas the activation of all other plants remains unchanged. Therefore, only the parameters (emissions and energy use) of this limited amount of plants are relevant, whereas the average system is not. If the change in demand is large, also the evolution of the power system may have to be altered. Then, not only the impact of the demand-side measure, but also the choices made in the planning (i.e., investments) of the power system is important. In these cases, there are no obvious conclusions, and simulations are necessary for quantitative predictions. For simple demand-side options (without alteration of the power system), the results are often not conclusive. Most of the time the overall environmental gain or loss is small, especially when an electric option is compared to a fossil alternative. The result will then also depend on the efficiency of the fossil option. If the demand-side option, on the other hand, creates possibilities for substantial changes in the supply-side structure, the results are dominated by the supply side. If the measure triggers the construction of a cleaner plant (e.g., a combined cycle gas-fired plant), or prevents the commissioning of a polluting plant (e.g., a coal-fired plant), it provides positive results.

Long-term Unit Commitment optimisation for large power systems: unit decommitment versus advanced priority listing

Unit Commitment (UC) is a term used for the strategic choice whereby the available power plants have to be on-line every time. Most UC models described in the literature are specifically designed for the power utilities. They are typical short-term models for relatively small power-systems. Apart from practical use in the utilities themselves, UC is also implemented in the broader context of electricity-generation modelling. For these purposes, however, the power systems can be much larger and the time scale more extended. Since UC is only a minor part of these models, the calculation time dedicated to UC has to be limited, thereby possibly sacrificing somewhat on accuracy. Two methods are compared. Unit Decommitment (UD), which is considered completely accurate and Advanced Priority Listing, which is less accurate but also less complicated. Simulations demonstrate that UD is slightly more accurate (0.03-0.6%), but takes much more calculation time (5-10 times more) than Advanced Priority Listing.

Short-term demand response of flexible electric heating systems: The need for integrated simulations

Active Demand Response (ADR) can contribute to a more (cost-)efficient operation of and investment in the electrical power system as it provides the needed flexibility to cope with the intermittent character of renewables. One of the promising demand side technologies in terms of ADR are electric heating systems as they allow to modify their electrical load pattern without affecting the thermal energy service they deliver, due to the thermal inertia in the system. However, these systems are hard to describe with traditional demand side models, since the performance depends on boundary conditions (occupants behaviour, weather conditions). Therefore, in this paper, an integrated system approach is applied, taking into account the dynamics and constraints of both electricity supply and heating systems. Only such an integrated system approach is able to simultaneously consider all technical and comfort constraints present in the system. The effects not captured by traditional approaches - such as price elasticities and virtual generator models - are identified and quantified, enabling the reader to select a modelling approach, weighing the computational effort against the required accuracy. In extensive power system studies, this approach can be used to assess the technical potential and all effects of flexible demand side technologies.

SHORT-TERM CO2 ABATEMENT IN THE EUROPEAN POWER SECTOR: 2005–2006

This paper provides an estimate of short-term abatement of CO2 emissions through fuel switching in the European power sector in response to the CO2 price imposed by the EU Emissions Trading Scheme (EU ETS) in 2005 and 2006. The estimate is based on the use of a highly detailed simulation model of the European power sector in which abatement is the difference between simulations of actual conditions with and without the observed CO2 price. We estimate that the cumulative abatement over this period was about 53 million metric tons. The paper also explains the complex relationship between abatement and daily, weekly, and seasonal variations in load, relative fuel prices, and the price of CO2 allowances.

Coupling Pumped Hydro Energy Storage With Unit Commitment

Renewable electricity generation not only provides affordable and emission-free electricity but also introduces additional complexity in the day-ahead planning procedure. To address the stochastic nature of renewable generation, system operators must schedule enough controllable generation to have the flexibility required to compensate unavoidable real-time mismatches between the production and consumption of electricity. This flexibility must be scheduled ahead of real-time and comes at a cost, which should be minimized without compromising the operational reliability of the system. Energy storage facilities, such as pumped hydro energy storage (PHES), can respond quickly to mismatches between demand and generation. Hydraulic constraints on the operation of PHES must be taken into account in the day-ahead scheduling problem, which is typically not done in deterministic models. Stochastic optimization enhances the procurement of flexibility, but requires more computational resources than conventional deterministic optimization. This paper proposes a deterministic and an interval unit commitment formulation for the co-optimization of controllable generation and PHES, including a representation of the hydraulic constraints of the PHES. The proposed unit commitment (UC) models are tested against a stochastic UC formulation on a model of the Belgian power system to compare the resulting operational cost, reliability, and computational requirements. The cost-effective regulating capabilities offered by the PHES yield significant operational cost reductions in both models, while the increase in calculation times is limited.

Optimization and Allocation of Spinning Reserves in a Low-Carbon Framework

Low-carbon electric power systems are often characterized by high shares of renewables, such as wind power. The variable nature and limited predictability of some renewables will require novel system operation methods to properly size and cost-efficiently allocate the required reserves. The current state-of-the-art stochastic unit commitment models internalize this sizing and allocation process by considering a set of scenarios representing the stochastic input during the unit commitment optimization. This results in a cost-efficient scheduling of reserves, while maintaining the reliability of the system. However, calculation times are typically high. Therefore, in this paper, we merge a state-of-the-art probabilistic reserve sizing technique and stochastic unit commitment model with a limited number of scenarios in order to reduce the computational cost. Results obtained for a power system with a 30% wind energy penetration show that this hybrid approach allows to approximate the expected operational costs and reliability of the resulting unit commitment of the stochastic model at roughly one thirtieth of the computational cost. The presented hybrid unit commitment model can be used by researchers to assess the impact of uncertainty on power systems or by independent system operators to optimize their unit commitment decisions taking into account the uncertainty in their system.

A Mixed Integer Linear Programming Model for a Pulverized Coal Plant With Post-Combustion Carbon Capture

Carbon capture and storage (CCS) seems to be an indispensable technology to safeguard the future of fossil-fired generation in the context of global warming. The deployment of CCS has an impact on the functioning and balancing of the overall electricity generation system. In this paper a mixed integer linear programming (MILP) model is developed for an ultra super-critical pulverized coal plant with post-combustion capture. Emphasis is on an appropriate representation of the dynamic behavior of this power plant. Four operating modes are considered for the capture plant, i.e., normal, start-up, off, and stand-by. The model is illustrated by means of a methodological example.