This paper analyzes different models for evaluating investments in energy storage systems (ESS) in power systems with high penetration of renewable energy sources. First of all, two methodologies proposed in the literature are extended to consider ESS investment: a unit commitment model that uses the "system states" (SS) method of representing time; and another one that uses a "representative periods" (RP) method. Besides, this paper proposes two new models that improve the previous ones without a significant increase of computation time. The enhanced models are the "system states reduced frequency matrix" model which addresses short-term energy storage more approximately than the SS method to reduce the number of constraints in the problem, and the "representative periods with transition matrix and cluster indices" (RP-TM&CI) model which guarantees some continuity between representative periods, e.g., days, and introduces long-term storage into a model originally designed only for the short term. All these models are compared using an hourly unit commitment model as benchmark. While both system state models provide an excellent representation of long-term storage, their representation of short-term storage is frequently unrealistic. The RP-TM&CI model, on the other hand, succeeds in approximating both shortand long-term storage, which leads to almost 10 times lower error in storage investment results in comparison to the other models analyzed.Index Terms-Energy storage systems, power system planning, power system modeling, system states, representative days.
Climate action pledges have increasingly taken the form of commitments to net carbon neutrality. Higher education institutions (HEIs) are uniquely positioned to innovate in this area, and over 800 United States (U.S.) colleges and universities have pledged to achieve net carbon neutrality. We examine the approaches of 11 U.S. HEIs that have already announced achieving net carbon neutrality, highlighting risks associated with treating carbon offsets, unbundled renewable energy certificates, and bioenergy (collectively 77% of reductions across institutions) as best practice under current frameworks. While pursuing neutrality has led to important institutional shifts toward sustainability, the initial mix of approaches used by these HEIs appears out of alignment with a broader U.S. decarbonization roadmap; in aggregate, these early neutrality efforts underutilize electrification and new zero-carbon electricity. We conclude by envisioning how HEIs (and others) can refocus climate mitigation efforts toward decarbonization and actions that will help shift policy and markets at larger scales. CARBON-NEUTRALITY COMMITMENTS IN U.S. HIGHER EDUCATIONU.S. HEIs, like all parts of society in developed economies, have significant greenhouse gas (GHG) emissions that must be rapidly reduced to avoid dangerous anthropogenic climate change. Many HEIs function like small cities with their own heating, power, and transportation infrastructure. If all full-time students, faculty, and staff at HEIs in the U.S. were counted together, U.S. HEIs would be the second most populous U.S. state with over 29 million people. 12 ll
In this work, we compare the air quality benefits of a variety of future policy scenarios geared towards controlling EGU (electricity generating units) emissions between the present-day conditions and 2050. While these policies are motivated by reducing CO2 emissions, they also yield significant co-benefits for criteria pollutants, such as ozone and PM2.5. An integrated set of clean energy policies were examined to assess the time-varying costs and benefits of a range of decarbonization strategies, including business as usual and the Affordable Clean Energy plan, with a primary focus on others that look to achieve very low, if not zero, CO2 emissions from the EGU sector by 2050. Benefits assessed include mitigation of greenhouse gas emissions as well as air quality co-benefits. In this introductory work, we describe the potential air quality changes from various clean air policies, to set the stage for upcoming work looking at health and monetized benefits. Emission changes for key pollutants are forecast using the Integrated Planning Model (IPM), which are then transformed into emission inputs for the Community Multiscale Air Quality Model (CMAQ). For all primary scenarios considered that achieve large greenhouse gas decreases, significant reductions in ozone and PM are realized, mainly in the eastern US, and all policies produce air quality benefits.
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