Smart Grid Participants Research Articles

Model predictive control of a rotary kiln for fast electric demand response

Rotary kilns require large fans to induce drafts to support transformation of minerals. If fan controls can be modified to respond to rapid changes in electric demand, they can become valuable grid assets. Due to their considerable thermal inertia, kilns and the associated fans are traditionally operated continuously in a steady manner to avoid process disruption. However, advanced process control, such as model predictive control (MPC) can allow for the rigid process to be operated flexibly. Ultimately the flexible process can respond to grid demand requirements by ramping the induced draft fan. Process disturbances generated by a quick change in the kiln air flow rate are buffered by adjusting kiln operations using MPC. In this work, a through, dynamic kiln model was developed. On top of the model, a novel MPC algorithm is presented which leverages kiln rotation rate, stone feed rate, and coal feed rate to ensure successful calcination of limestone while the kiln simultaneously plays a crucial role in electric grid regulation. Four scenarios were explored, long and short term duration of both up and down regulation. The MPC algorithm reduced the number of hours of poor stone quality production to 0 during smart grid participation. The economic penalty of the grid responses was reduced by at least 65% using MPC, compared to steady-state optimized operation. For short-term participation, less than two hours, the MPC algorithm would reduce economic penalties by at least 77%. Minimized economic penalties and high stone quality improve the feasibility of smart grid participation.

Automated electrical demand peak leveling in a manufacturing facility with short term energy storage for smart grid participation

Demand side management of energy is a vital function in the smart grid that allows for greater integration of renewable energy resources, and is facilitated with economic incentives in energy and demand pricing schedules. Manufacturing systems can take advantage of these incentives to reduce their energy costs through active energy management. This paper is a simulation analysis on the implementation of a novel algorithm that levelizes the maximum power load of an industrial bakery that operates under an on-peak demand price structure. The algorithm takes advantage of an untapped thermal energy storage resource in the facility, a chilled glycol buffer tank, to level the short intra-day power oscillations that the facility experiences. One of the key advantages of the algorithm is that it does not require precise demand forecasting or complex control algorithms, such as model predictive control. Even with substantial error in peak power estimates (5%), the algorithm is expected to result in at least a 2% peak reduction. Under ideal prediction, the algorithm reduces the on-peak facility power maximum by 7.3% of the possible 9.0% reduction the storage can provide. Further, the algorithm uses very few facility specific inputs, and can readily be adapted for any facility with short intra-day oscillatory power profiles and untapped storage capacity. The key insight of the paper is the employment of a novel algorithm to leverage untapped energy storage in manufacturing facilities to transform them into smart grid participants with no major capital investment.

Privacy‐friendly and efficient secure communication framework for V2G networks

The vehicle-to-grid (V2G) technology enables electric vehicles to deliver electricity into power systems, providing them supplementary capacity. On the other hand, a new set of security threats are brought to smart grid participants by V2G networks. However, security and privacy in V2G networks have so far received little attention, despite a rich literature on the design of conceptual structures or the impact of V2G networks on the current grid. In this study, the authors explore the features of V2G communication networks and identify their security challenges for communication functions. The authors then establish a novel and secure communication framework for V2G networks to achieve a balance among security, privacy preservation, efficiency and accountability without relying on any trusted third party. The feasibility of the framework is demonstrated by experimental results.

Smart Community Based Solution for Energy Management: An Experimental Setup for Encouraging Residential and Commercial Consumers Participation in Demand Response Program

Smart grid technology development progression has created a possibility for the end users’ participation in the electricity market possible. Recently, the Singapore government has changed the rule for participation in the wholesale market. The Smart Community project, developed by NTU, DNV GL and Green Koncepts, will look into critical factors that will help retail consumers to participate in the demand responses (DR) program and time of use (TOU) pricing. This study reviews benefits for current retail consumer, the impact of DR and TOU on real-time energy consumption of the users, the impact of user experience-focus application toward smart grid participation program on participation reliability and contribution in power reduction during curtailment period. The DR program allows the users to become an active participant in the energy market. It also allows the government to plan better on the limited and costly energy resources, improve system reliability, and reduce transmission and distribution congestion, check and balance on the market power generation. A mobile-based user-experience focus on convenience application is to be developed for consumers to actively participate in the demand-side management programme, which make Singapore Wholesale Energy Market more resilient and reducing market power by introducing competition.

Quantifying economic benefits in the ancillary electricity market for smart appliances in Singapore households

The adoption of smart grid systems has been accelerating around the world, with many pilot projects initiated throughout the developed world. However, there has been a lack of studies quantifying appliance level economic benefits that are available to the end consumers. Through coupling historical market information with an agent based residential load model, this study has quantified the economic benefits of residential smart grid participation in ancillary electricity markets. In this study, we looked at the energy market of Singapore. The regulation and reserve ancillary electricity markets were examined and the associated economic benefits from market participation were assumed to be fully passed on to the consumers. A lesson is that the potential returns for consumer investment in smart appliance technology could be very low. No matter which market that the aggregator participates in, the corresponding credits that a single appliance can earn for the consumer through ancillary markets may not be attractive enough for the consumer. Although there could be other cost saving options such as dynamic electricity prices which could be complementary to such schemes; this result highlights the fact that economic benefits alone may not be attractive enough for smart appliance adoption in the current local policy climate.

Adding accurate timestamping capability to wireless networks for smart grids

Smart grids rely on bi-directional communications between energy production sites and utilization sites. Usually, different approaches are used for implementing the required Wide, Field, and Home Area Networks (WAN, FAN and HAN, respectively). These networks are realized using very different (hybrid) technologies, for instance wired for WAN and wireless for FAN and HAN. However, an accurate common sense of time must be guaranteed among all smart grid participants, as it happens in any other distributed systems. Satisfying this need is challenging for wireless networks, while mature time distribution technologies are available for wired networks. The major issue for wireless devices is to provide accurate timestamping of network events, the key element of any time synchronization protocol. The objective of this paper is to propose low-cost and low-complexity timestamping techniques that also maintain full compatibility with already existing (unlicensed) communication standard for wireless nodes used in smart grids. In addition, a suitable platform exploiting the Software Defined Radio paradigm for comparative evaluation of these techniques is also discussed. Simulation and experimental results confirm the feasibility of the proposed approach, with the standard deviation of the timestamping error scalable down to 5ns.