www.smart-microgrid.ca

Project 2.1Cost-Benefit Framework: Secondary Benefits and Ancillary ServicesMIKE 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 improvementEconomic: cost of energyEnvironmental: 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.

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Methodology• The technique proposed herein,

incorporates a probabilistic modeling of variable loads and distributed generators into a deterministic power flow problem to solve an optimization problem

Subject to: (2)

(3)

• The losses (PLOSS) from the power flow problem is monetized and supplied to the objective function as one of its input multiple cost functions

(4)

Methodology• For GCC:

(5) (6)

(7) (8)

• For GHC:(21)

• The optimization problem then concatenates the monetized losses, monetized emission and the cost components of generation into a single objective and then minimizes it.

Test System

Figure 1. Cigre's North American medium Voltage DistributionNetwork Benchmark with DG connected to operate as Microgrid .(CIGRE TF C6.04.02, “Benchmark systems for network integration of renewable and distributed energy resources,” technical brochure, version 21, pp25-39, August 2010.)

Peak load of 12.775MW.

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

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Base Case

Optimal Case

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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)

Winter Spring Summer Fall Annual(MWh)

I. Base Case(No DG)

0.6757 0.6743 0.6770 0.6743 243.1123

II. Solar Only

0.6620 0.6605 0.6631 0.6605 238.1372

III. Wind Only

0.6037 0.5992 0.6160 0.6082 218.4336

IV. Wind and Solar

0.6035 0.5988 0.6155 0.6078 218.3088

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 CO2 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