Project 2.1 Cost-Benefit Framework: Secondary Benefits and Ancillary Services MIKE QUASHIE AND GEZA JOOS (MCGILL UNIVERSITY)

Presentation outline Problem Identification Proposed Solution Methodology Results and Conclusion Future work and collaboration

Problem Identification Microgrids are often touted as a technology that can improve local system reliability and aid in the integration of renewable energy resources. However, to facilitate the additional control and operating modes associated with a Microgrid, additional equipment is needed. – The cost associated with this infrastructure can be quantified once the necessary elements are identified. – Contrarily, there may be certain costs, such as those associated with changes to operating protocol, training and new safety requirements, which may be more difficult to translate into a dollar figure. – For utilities and business owners, this analysis is required to develop the business case for a given technology. Many of the benefits of a Microgrid are also not tangible in the Canadian context and consequently require additional considerations to monetize. How can the assumptions made in the cost-benefit framework be tested?

Solution Previous work done in collaboration with CanmetEnergy and project 1.4, identified benefits of Microgrids and how the benefits impacts stakeholders. Benefits Identified: Technical: Network efficiency improvement(losses reduction), reliability improvement Economic: cost of energy Environmental: GHC emission reduction The natural step that follows is to developed a methodology to optimize the identified benefits. Historical data of wind speed and solar irradiance were obtained from CWEEDS through interaction with CANMET ENERGY.

Methodology The work done over the year is proposes a generalized methodology to determine the optimal configuration of microgrids that maximizes its benefits.

Methodology

Test System Figure 1. Cigre's North American medium Voltage DistributionNetwork Benchmark with DG connected to operate as Microgrid. (CIGRE TF C , “Benchmark systems for network integration of renewable and distributed energy resources,” technical brochure, version 21, pp25-39, August 2010.) Peak load of MW. The optimal configuration was also found to be 1.2 MW of wind turbine on node 7 and 30 KW solar panel on node 4.

RESULTS Figure 2. Comparison of Hourly Total Cost of Energy to the Distributed Network Operator for a Year (each 24hr represents a Season) A 16.1 percent decrease in the average cost of energy for the optimal case is observed in comparison to the base case

Results Seasons Average Losses(MWper hr) WinterSpringSummerFallAnnual(MWh) I. Base Case(No DG) II. Solar Only III. Wind Only IV. Wind and Solar TABLE I. LOSSES IN THE POWER NETWORK FOR VARIOUS SCENARIOS The efficiency of the network is also improved by 10 percent through loss minimization for the optimal case in comparison to the base case.

Conclusion Application of the methodology to the microgrid planning process resulted in significant decrease in the cost of energy to the distribution network operator. A significant improvement in the network’s efficiency (loss minimization) as well as reduction in CO 2 emissions is also observed in applying the methodology to the microgrid planning process. The economic, technical and environmental benefits of the microgid which are maximized through the use of the proposed methodology help offset the cost associated with microgrid’s implementation, building a better business case for microgrid advancement Results of the study was present at Power and Energy Society general meeting 2013 in Vancouver.

Future work Develop a framework for implementing and quantifying ancillary services. Application of the methodology to Microgrid demonstrations in existing and potential Microgrids (commercial, industrial and remote community settings). Potential collaboration with project 2.4 and 1.4 Future collaboration with 3.1 to have an accurate estimate of ICT infrastruture in Microgrids