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Deployment of high-penetration photovoltaic (PV) power is expected to have a range of effects – both positive and negative – on the distribution grid. The magnitude of these effects may vary greatly depending upon feeder topology, climate, PV penetration level, and other factors. In this paper we present a simulation study of eight representative distribution feeders in three California climates at PV penetration levels up to 100%, supported by a unique database of distributed PV generation data that enables us to capture the impact of PV variability on feeder voltage and voltage regulating equipment. We find that feeder location (i.e. climate) has a stronger impact than feeder type on the incidence of reverse power flow, reductions in peak loading and the presence of voltage excursions. On the other hand, we find that feeder characteristics have a stronger impact than location on the magnitude of loss reduction and changes in voltage regulator operations. We find that secondary distribution transformer aging is negligibly affected in almost all scenarios. [ABSTRACT FROM AUTHOR]

Abstract: Despite a clear need, little research has been carried out at the regional-level to quantify potential climate-related impacts to electricity production and delivery systems. This paper introduces a bottom-up study of climate change impacts on California''s energy infrastructure, including high temperature effects on power plant capacity, transmission lines, substation capacity, and peak electricity demand. End-of-century impacts were projected using the A2 and B1 Intergovernmental Panel on Climate Change emission scenarios. The study quantifies the effect of high ambient temperatures on electricity generation, the capacity of substations and transmission lines, and the demand for peak power for a set of climate scenarios. Based on these scenarios, atmospheric warming and associated peak demand increases would necessitate up to 38% of additional peak generation capacity and up to 31% additional transmission capacity, assuming current infrastructure. These findings, although based on a limited number of scenarios, suggest that additional funding could be put to good use by supporting R&D into next generation cooling equipment technologies, diversifying the power generation mix without compromising the system''s operational flexibility, and designing effective demand side management programs. [Copyright &y& Elsevier]

Global climate change is making California's mild Mediterranean climate significantly warmer, and a substantial impact on building energy usage is anticipated. Studies on building cooling and energy demand have been inaccurate and insufficient regarding the impacts of climate change on the peak load pattern shifts of different kinds of buildings. This study utilized archived General Circulation Model (GCM) projections and statistically downscaled these data to the site scale for use in building cooling and heating simulations. Building energy usage was projected out to the years of 2040, 2070, and 2100. This study found that under the condition that the cooling technology stays at the same level in the future, electricity use for cooling will increase by 50% over the next 100 years in certain areas of California under the IPCC (Intergovernmental Panel on Climate Change)'s worst-case carbon emission scenario, A1F1. Under the IPCC's most likely carbon emission scenario (A2), cooling electricity usage will increase by about 25%. Certain types of buildings will be more sensitive to climate change than others. The aggregated energy consumption of all buildings including both heating and cooling will only increase slightly. [ABSTRACT FROM AUTHOR]

There is value in DR, but it needs to be evaluated correctly. The pricing experiment in California showed that well-designed dynamic pricing programs can have a significant impact on critical peak loads, and California''s investor-owned utilities are using the experimental results to develop business cases for advanced metering. A key question in developing these business cases is how much value to attach to a kW of load that is curtailed during critical times. [Copyright &y& Elsevier]

Abstract: Tree canopy cover data from aerial photographs and building energy simulations were applied to estimate energy savings from existing trees and new plantings in California. There are approximately 177.3 million energy-conserving trees in California communities and 241.6 million empty planting sites. Existing trees are projected to reduce annual air conditioning energy use by 2.5% with a wholesale value of $ 485.8 million. Peak load reduction by existing trees saves utilities 10% valued at approximately $778.5 million annually, or $ 4.39/tree. Planting 50 million trees to shade east and west walls of residential buildings is projected to reduce cooling by 1.1% and peak load demand by 4.5% over a 15-year period. The present wholesale value of annual cooling reductions for the 15-year period is $ 3.6 billion ($ 71/tree planted). Assuming total planting and stewardship costs of $ 2.5 billion ($ 50/tree), the cost of peak load reduction is $ 63/kW, considerably less than the $ 150/kW benchmark for cost-effectiveness. Influences of tree location near buildings and regional climate differences on potential energy savings are discussed. [ABSTRACT FROM AUTHOR]

Given the crowded condition of most metropolitan freeways during rush hours in this country, the question of optimal pricing and investment policies for urban roads is a topic of some interest and controversy. It is the aim of this paper to derive a long-run model of highway pricing and investment to shed light on these issues. The model is developed and estimated, using data from a sample of freeways in the San Francisco Bay Area. In brief, the model is concerned with trading off the cost of providing urban expressway capacity against the value of travel time to minimize total system costs. Out of the model comes a set of long-run peak-load tolls (equal to optimal short-run tolls when investment is made correctly), as well as an optimal service level (as a function of time values and capacity costs). These results give some indication as to whether auto transportation in a given corridor is priced efficiently and whether capacity provided is appropriate. In Section I the model is set forth, consistent with the previously established theory of peak-load pricing, but particularly suited to highways. Sections II-V are concerned with empirical estimation of the parameters of this model. More specifically, Section II is concerned with the estimation of capital and maintenance costs and with determining returns to scale in the provision of freeway services. Section III is concerned with estimating the technological trade-off between travel time and capacity utilization. Section IV discusses briefly the issues involved in valuing travel time and presents the assumptions made in this study, as well as some evidence to support them. In Section V attention is directed to the peaking characteristics of demand for Bay Area freeway services. Section VI pulls together the theoretical and empirical work of the previous sections, discusses the optimization procedure used, and presents the results. Section VII presents a comparison of optimal and existing prices on servic... [ABSTRACT FROM AUTHOR]

• PV output can be temporally shaped through curtailment, tracking, and orientation. • We quantify the impact of output-shaping on day-ahead and real-time market revenues. • The 2017 California real-time market demonstrates the largest benefit from shaping. • Optimal azimuths for real-time revenue are ∼55° west of south in California in 2017. • The revenue benefit from temporal output-shaping increases with PV penetration. Large-scale deployment of solar photovoltaics (PV) contributes to the occurrence of depressed—and sometimes negative—electricity prices during daylight hours as PV displaces higher-cost generators in the merit-order dispatch stack. These changes in electricity price provide an opportunity to increase the wholesale energy revenue of PV generators through temporal shaping of PV output. Here, we explore the impact of three output-shaping strategies on PV wholesale energy revenue and capacity factor: utilization of 1-axis tracking, curtailment during negative-price hours, and modification of fixed-tilt array orientation. Utility-scale PV arrays are modeled at more than 10,000 pricing nodes across six United States electricity markets over the 2010–2017 time period. Large changes in revenue-optimized output profiles are observed for the California system, where solar capacity penetration has increased from ∼2% of peak load in 2010 to ∼28% of peak load in 2017, and the wholesale revenue benefits of temporal output shaping are increasing with time. On the California real-time market in 2017, compared to capacity-factor-optimized fixed-tilt arrays with must-run operation, curtailment increases revenues by 9%, curtailment in conjunction with fixed-tilt orientation optimization increases revenues by 20%, 1-axis tracking without curtailment increases revenues by 32%, and 1-axis tracking with curtailment increases revenues by 42% for the median node. Median optimal fixed-tilt azimuths for PV on the real-time market in California have increased from 192° in 2010 to 235° (i.e. 55° west of south) in 2017. Among the markets and years studied, the California market in 2017 demonstrates the largest potential benefit from temporal output shaping. These results highlight mechanisms for mitigating some of the decline in PV wholesale value at high solar penetrations, and illustrate the importance of adapting PV installation and dispatch strategies to changing power system conditions. [ABSTRACT FROM AUTHOR]