We are pleasured to have Mohammad who is from Chinese University of Hong Kong to present the first full paper in e-Energy 16′.
The title of the paper is “Online Microgrid Energy Generation Scheduling Revisited: The Benefits of Randomization and Interval Prediction”.
As compared to traditional grids, microgrid has recognized advantages in cost efficiency, environmental awareness, and power reliability. In microgrid, intelligent energy generation scheduling is a key mechanism aiming at minimize operation cost and simultaneously satisfy the demand which is composed of electricity and heat.
In this research, the online algorithm is implemented and compared to the performance of the offline algorithm. Two methodologies based on the CHASE are utilized in the research.
- Randomized CHASE
- Interval prediction type CHASE
Both methods are proven to beyond the best deterministic algorithm. Furthermore, the authors use the electric power data set from San Francisco combining with wind farm generation and a time-of-use scheme electricity price to evaluate their methodologies.
In summary, the paper investigates the potential benefits of randomization and interval prediction in online algorithm design for intelligent energy generation scheduling in microgrid. And their experimental study demonstrates that new design space of randomization and interval prediction can significantly improve the result of the previous deterministic algorithm and can achieve near offline-optimal performance.
The second presentation is given by Anamitra who is from IBM Research in India, and the title of the talk is “Supply Scheduling and Usage-Based Pricing for Shared Storage in Adaptive Dynamic Islanding”.
The authors point out that utilities face outages in power distribution due to systemic energy shortfall, device failures, faults in the network, weather condition or intentional electricity outage thus the islanding is a mean to supply backup power to a subset of the load by using local energy sources such as batteries or micro-generation during outages.
The islanding concept is implemented in their study, the main idea in the paper is to share batteries during outages, however, islanding is limited in capacity and not possible to supply all demand. The authors utilized Adaptive Dynamic Islanding (ADI) wherein the utility differentiates between the loads of the customers and supplies the limited energy by cycling it over the customers.
The challenge is that when a battery is used as a shared energy source among a set of customers during an outage, it is necessary to satisfy the demands as much as possible while taking into account the affect of the discharge rate which reduce the battery life.
The authors utilize the data from Irish Commission for Energy Regulation to evaluate their methodologies and the simulations show that their usage-based pricing mechanism (considering battery wear cost) is necessary and is able to capture the varying effects of customers on the lifetime and capacity of the shared battery.
The third talk is also presented by Anamitra, and the title of the paper is “A Network Calculus Foundation for Smart-Grids where Demand and Supply Vary in Space and Time”.
In this paper, the authors point out that energy distribution problem will vary in time and space when electric vehicles (EVs) are involved. The queueing policies which can be employed to systematically match demand and supply for EVs that capable of swapping the battery.
Two types of policies are used as queueing algorithm for EV to swap battery:
- Pure policies which displace demand in only one dimension (time or space):
- Higher priority is given to EVs that arrive earlier.
- Higher priority is given to EVs that arrive at earlier regions.
- Mixed policies
- Consider the total demand arriving in a space-window as a single arrival process, and the total supply available in a space- window as a single service process.
- Consider the total demand arriving and supply available in a time-window as single arrival and supply processes, respectively.
Quality- of-Service (QoS) metrics are used to evaluate the work. For any such policy, the authors compute QoS metrics, such as upper-bounds on buffer-length, delay, and the output arrival function, for all observable arrival and service functions. The authors design 4 scenario to compare different policies and they demonstrate the methods in analyzing QoS metrics in servicing EVs plying on a highway with batteries charged with solar chargers along the highway. In particular, they consider the metrics of worst-case delay and distance travelled by an EV before be- ing serviced with a charged battery.
Summary of the session:
This session includes three talks focus on the energy distribution in microgrid grid, battery sharing and EV battery swapping. The session covers a wide discussion among the energy distributions.
In this session, I am personally interested in the first talk which considers the online algorithm implemented in the microgrid system. Since it is really difficult to predict the future precisely, therefore, an online algorithm that provides acceptable solution is very practical.