Benjamin Dupont

LINEAR breakthrough project: Large-scale implementation of smart grid technologies in distribution grids

The LINEAR project (Local Intelligent Networks and Energy Active Regions) focuses on the introduction and implementation of innovative smart-grid technologies in the Flanders region, and aims at a breakthrough in the further development and deployment of these solutions. It consists of a research component and a large-scale residential pilot, both focusing on active demand-side management of domestic loads. This paper describes the unique approach, the main objectives and the current status of this project. Selected business cases and target applications are discussed in detail.

Automated residential demand response based on dynamic pricing

Against the background of more renewable energy, limited investment in power generation, ageing distribution and transmission infrastructure, and the electrification of energy, the demand side of the electricity system is gaining attention. Moreover, the increasing ability to automate household appliances allows to involve the demand side more easily. Therefore, this paper examines demand response of residential consumers possessing smart appliances. Starting from day ahead wholesale prices and renewable energy production, different cost reflective Real Time Pricing (RTP) schemes are developed. According to these schemes, white goods are scheduled to the lowest price period taking into account user preferences. These demand modifications bring about new insights in the impact of the introduction of RTP.

Short-term consumer benefits of dynamic pricing

Consumer benefits of dynamic pricing depend on a variety of factors. Consumer characteristics and climatic circumstances widely differ, which forces a regional comparison. This paper presents a general overview of demand response programs and focuses on the short-term benefits of dynamic pricing for an average Flemish residential consumer. It reaches a methodology to develop a cost reflective dynamic pricing program and to estimate short-term bill savings. Participating in a dynamic pricing program saves an average consumer 2.32 percent of his initial bill. While this result seems insufficient to justify implementation, it contains only a small proportion of a series of dynamic pricing benefits.

Measuring the “smartness” of the electricity grid

Awareness among policy makers that electricity grids need to become smarter is growing. To allow policy makers to design policies for improving the smartness of grids, discussion is needed on what makes an electricity grid smart and how that this smartness can be measured. This paper provides a methodology to measure the smartness of the electricity grid. The defined framework consists of six characteristics which a smart grid should meet. Progress in the development of each characteristic is assessed by several key performance indicators. This allows to track the status of smart grid development.

Feasibility of employing domestic active demand for balancing wind power generation

Wind power suffers from two problems: it is non-dispatchable and thus cannot be altered to coincide with power demand and the predictability of wind power is limited. Controllable flexible resources are thus crucial when managing a particular energy portfolio with a considerable share of wind power. This paper therefore assesses the feasibility of employing domestic active demand for balancing wind power generation in a BRP (Balancing Responsible Party) portfolio. The analysis starts from a BRP portfolio consisting of gas-fired power plants and generators of wind power on the generation side, and residential and industrial consumers on the consumption side. The optimal balancing options (upward/downward regulation of GFPPs, intraday market, active demand services or paying imbalance costs to the TSO) to be taken by the BRP to minimize imbalance volumes are determined for different wind scenarios and imbalance pricing schemes based on simulations. The paper describes the methodology used and discusses the potential profit for the BRP when active demand is employed as a supplementary balancing option within the different scenarios.

Optimizing the use of flexible residential demand for balancing wind power

Due to limited predictability of variable renewable energy sources such as wind energy, the balance between demand and supply in electricity systems is challenged. Market players integrating these technologies in their portfolio face increasing imbalances and are, consequently, charged with cost-reflective imbalance tariffs. In this paper, an optimization model is developed which aims to minimize wind power imbalances by means of combining different control options: thermal generators re-dispatch, intra-day market trading and shifting flexible residential demand. The model is applied to a case study on a representative market player in the Belgian market context. Simulation results show that flexible demand provides a significant share in the reduction of the imbalance volume.

Networked business model for dynamic pricing in the electricity market

In a liberalized electricity market, the introduction of dynamic pricing for residential consumers has consequences on the whole network structure. This structure consists out of all market participants and their interactions. To assess the impact of dynamic pricing, an accessible representation of the network structure is implemented in a networked business model applying the e3value methodology. The focus of the model is on the interaction and value exchanges between market participants. Hereby, an economic analysis for all market participants is performed. Using the networked business model reveals the shifts of economic values triggered by dynamic pricing and the resulting demand response for all market participants throughout the network. An indication for the feasibility of dynamic pricing can be given.