CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

People or machines? Assessing the impacts of smart meters and load controllers in Italian office spaces

Government initiatives in several developed and developing countries to roll-out smart meters call for research on the sustainability impacts of these devices. In principle smart meters bring about higher control over energy theft and lower consumption, but require a high level of engagement by end-users. An alternative consists of load controllers, which control the load according to pre-set parameters. To date, research has focused on the impacts of these two alternatives separately. This study compares the sustainability impacts of smart meters and load controllers in an occupied office building in Italy. The assessment is carried out on three different floors of the same building. Findings show that demand reductions associated with a smart meter device are 5.2% higher than demand reductions associated with the load controller.

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

The Birmingham Urban Climate Laboratory: an open meteorological test bed and challenges of the smart city

Existing urban meteorological networks have an important role to play as test beds for inexpensive and more sustainable measurement techniques that are now becoming possible in our increasingly smart cities. The Birmingham Urban Climate Laboratory (BUCL) is a near-real-time, high-resolution urban meteorological network (UMN) of automatic weather stations and inexpensive, nonstandard air temperature sensors. The network has recently been implemented with an initial focus on monitoring urban heat, infrastructure, and health applications. A number of UMNs exist worldwide; however, BUCL is novel in its density, the low-cost nature of the sensors, and the use of proprietary Wi-Fi networks. This paper provides an overview of the logistical aspects of implementing a UMN test bed at such a density, including selecting appropriate urban sites; testing and calibrating low-cost, nonstandard equipment; implementing strict quality-assurance/quality-control mechanisms (including metadata); and utilizing preexisting Wi-Fi networks to transmit data. Also included are visualizations of data collected by the network, including data from the July 2013 U.K. heatwave as well as highlighting potential applications. The paper is an open invitation to use the facility as a test bed for evaluating models and/or other nonstandard observation techniques such as those generated via crowdsourcing techniques.