Integrated Microgrid Expansion Planning and Policy Making under Uncertainty in Power Electricity Market



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An interconnected microgrid is a group of Distributed Energy Resources (DER) with the ability to operate in a grid connected mode. DERs include nondispatchable renewable generation such as wind and solar units as well as small scale dispatchable resources such as diesel generators, microturbines, and energy storage The penetration of microgrids to the energy portfolio across the world has been steadily increasing over the past few years. Several studies have predicted that this trend will continue in the future leading to large scale integration of microgrids into energy networks, which poses several principle challenges to be addressed.

First, deploying a microgrid on the main-grid depends on estimated profits for potential power investors in the electricity capacity market. Hence, there is a clear need for quantitative analysis tools that can help power investors in assessing monetary benefits of investment on microgrids in this competitive market. To address this need, this proposal proposes a mathematical model to help power investors to decide if they should invest in a microgrid installation. The proposed model integrates microgrid expansion planning with the conventional generation and transmission planning to study the potential advantages of the grid-connected microgrid system. Accordingly, the model provides an appropriate market price signal for power investors to determine the size, time, and type of new power resources required to satisfy reliability requirements and operation cost optimization.

Second, the power investors, in particular, face a number of important challenges in terms of uncertainties such as load growth and component power outage. To incorporate the uncertain parameters into the optimization model, a two-stage stochastic optimization approach is proposed. The objective of the model is to maximize the expected revenue from power companies, while ensuring the cost-effectiveness and reliability of the power system under those uncertain factors. The proposed model is solved based on Benders decomposition. Computational experiments are conducted on two IEEE-6 and -118 bus test systems to analyze the effectiveness of the proposed approach. Several further issues are of interest. The first issue is how to design an interconnected microgrid with intermittent renewable resources such that the resulting network is stable. To maintain the stability of such a network, this study presents some policies to be implemented in advance. These policies will provide insights for the power investors to design an interconnected microgrid having more renewable resources while ensuring the reliability of the network under these fluctuations or other obstacles. The second issue is the power planning problem with these uncertain factors is a large scale problem. Further study is needed to overcome the computational efforts. Finally, new regulations and policies have been implemented for power system network. It will be interesting to incorporate the new policies in the assessment of microgrid's benefits.

Moreover, recent hurricanes prove that our electric utilities as critical infrastructures are very vulnerable to extreme weather events. Therefore, there is a severe need for an alternative strategy to mitigate and adapt to the risks of these events. First, this study analyzes and simulates the high-impact low-probability events such as hurricanes on the power systems resiliency using hierarchical analytical process. Using this quantitative analysis, the proposed framework is suggested to enhance the resiliency by efficiently deploying the microgrids into power systems.



Adaptability, Benders decomposition, Black-start unit, Component outages uncertainty, Electricity markets, Fragility curve, Hurricanes, Microgrid expansion planning, Policy making, Power systems, Recovery, Resilience, Robustness, Rural electrification, Two-stage stochastic mixed-integer programming