Customer sampling in a smart grid pilot

Abstract

Smart grid pilot projects require a representative subset of the total population to draw relevant conclusions from test results. However, customers willing to participate in such projects are not always representative to the whole population. Standard random sampling gives some problems because not all results can be scaled. Defining sub-populations or strata to random samples from is theoretically sound, but the definition of sub-populations is quite expensive. The paper presents a customer sampling technique based on quota. The domains for the quota are defined by machine learning algorithms and the quota themselves are based on realistic data. Sampling is done by an optimization algorithm, which eliminates the common 'human error'-factor in quota sampling. The approach is a cost efficient and convenient way of sampling that is able to balance the representativeness of the electricity consumption patterns for the population against sampling accuracy. The method has been applied and validated on a large customer data set.

On Scalability and Replicability of Smart Grid Projects—A Case Study

“…Although the solution proposed by a project might have overcome the regulatory and legal barriers (e.g., by adapting the regulatory framework), it is very important that other stakeholders accept the proposed solution. For example, the LINEAR project's field tests aim at quantifying the amount of flexibility that could be exploited from the customers [30,31]. An important barrier for the field tests arose from the fact that an important financial effort was required from the field test participants since they had to buy the smart appliances installed in their houses.…”

Voltage regulation strategies for flemish LV distribution grids utilizing single-phase PV inverters

“…Statistically, the load profiles represent residential load profiles and were generated in [19]. They provide only active power consumption per time step, hence, a random power factor distribution of [0.85-1] was assumed.…”

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

“…The results of this social investigation were linked to the consumption profiles of the customers. Customer sampling techniques were used to guarantee the representativeness of the consumption profiles [21]. This yielded a set of representative electricity and gas demand profiles, which is used in the simulations of the LINEAR project (see section V).…”

“…To investigate the scale and magnitude of these problems, load flow simulations have been performed on four typical Flemish feeders, from a rural to a city environment [24]. Important input of the simulations is the detailed structure of the feeders and the load profiles, which were provided by the industrial partners and analyzed within the LINEAR project [21].…”