10h30 - 10h55
Increasing electric vehicle adoption via strategic siting of charging stations
Governments everywhere have started setting ambitious goals for electric vehicle (EV) adoption for the next few decades. Today's charging infrastructure is, however, insufficient to service all these new EVs. Moreover, private investment in charging stations is unlikely while the number of EVs is small, and potential customers will not purchase EVs while these infrastructures are not widespread. Governments must therefore drive this investment during a first stage, thus promoting a higher EV adoption. We present a holistic optimization framework for the strategic siting and sizing of EV charging stations, which takes into account how new infrastructure impacts future EV demand.
10h55 - 11h20
Complementarity modeling of renewable energy credit (REC) and electricity markets to inform effective renewable energy policy formation
Across the United States (U.S.), at least 2,650 renewable energy incentives and regulations exist at the state level. The most common overarching policy instrument is the Renewable Portfolio Standard (RPS), also known as a Renewable Energy Target (RET), which mandates that a certain percentage of electricity be produced from renewable energy. The highest targets in the U.S. are currently 100% renewable energy production in Hawaii by 2045, and 50% in California, New York and Oregon. While the overarching goal of increasing renewable energy production is common among policies, the mechanisms for achieving a given RET vary widely. This study is one of the first to analyze whether an RET is best set as a single or multi-stage goal; at the state level (regionally), or at the firm-level; and whether the mechanism of trading the environmental benefits of renewable energy via Renewable Energy Credits (RECs) aids RET achievement. By modeling both the REC and electricity market, this study finds that an RET policy design of multi- stage targets at the firm-level, without an REC market, is optimal. It not only achieves the highest social surplus, but also the highest renewable investment, as well as the greatest reduction in greenhouse gas emissions.
11h20 - 11h45
A techno-economic optimisation model of the Greater Montreal Area transport sector
The objective of this research is to build a techno-economic optimisation model of the Greater Montreal Area transport sector, taking into account energy flows and environmental constraints. Scenarios implementing Quebec policies regarding technologies, greenhouse gases emissions and petroleum limits are computed over the growing demand of the next fifty years.
11h45 - 12h10
Flexibility scheduling for microgrids
A framework for flexibility management in microgrids is presented. This framework is based on robust optimization and the concept of the flexibility envelopes. It is formulated as a mixed-integer linear programming problem. Numerical experiments demonstrate that the proposed approach is capable of (a) reducing the operating cost of microgrids, (b) reaching high levels of reliability, and (c) maximizing the use of renewable generation.