Solar+Storage for Low-and Moderate-Income Communities: A Guide for States and Municipalities

The Clean Energy States Alliance (CESA) has produced a new report for states and municipalities on solar+storage for low- and moderate-income (LMI) communities. The report explains how solar+storage can benefit LMI residents and describes a variety of policy tools for doing so, including grants, rebates, utility procurement standards, financing support, opening markets, and soft cost reduction

DETAILED RELIABILITY MODELS OF INTEGRATED SOLAR POWER TECHNOLOGIES IN ELECTRIC POWER SYSTEMS

The contribution of solar power in electric power system has been growing rapidly due to the significant negative impact of carbon emissions generated by conventional power sources. Large scale photovoltaic (PV) and concentrated solar power (CSP) have been installed around the world. However, these technologies involve major concerns regarding the reliability of system generation. The output power generation from solar technologies acts quite differently from that of conventional generation. The PV and CSP are composed of major components that have different failure characteristics. The interactions of the different component topologies in various commercially available PV system configurations will significantly influence the reliability of a PV system. Moreover, the output power of PV and CSP are highly variable and depend on the solar irradiation resulting in discontinuous and variable electricity generation. All these factors have a direct impact on the overall generation system adequacy. It is, therefore, vital to incorporate these factors in the reliability modeling of PV and CSP systems. An analytical probabilistic technique is employed in this thesis to develop detailed reliability models of PV and CSP systems. This thesis investigates the impact of PV/CSP system components on the reliability performance of PV/CSP systems. Different studies were conducted on test systems in this thesis considering system load variation, growth in solar capacity, geographical location, and seasonal effects. These analyses have been expanded to quantify the comparative reliability of a generation system with large scale PV and CSP. The power output of PV is also affected by dust accumulation on PV panel surfaces. The deposition of dust on PV panels will reduce the net solar irradiation absorbed by the solar panel, and lower the solar panel efficiency. This project is extended to incorporate the cumulative dust in the reliability model of the PV system. A regression model is adopted to develop a probabilistic model of PV power reduction caused by cumulative dust. This work also investigates the impact of a dust-removal strategy on the overall system adequacy. The concept and methodology discussed in this thesis can be used effectively by system planners and electric utilities to evaluate the reliability benefit of utilizing solar power in existing generation systems

Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System

Due to the inherent aleatory uncertainties in renewable generators, the reliability/adequacy assessments of distributed generation (DG) systems have been particularly focused on the probabilistic modeling of random behaviors, given sufficient informative data. However, another type of uncertainty (epistemic uncertainty) must be accounted for in the modeling, due to incomplete knowledge of the phenomena and imprecise evaluation of the related characteristic parameters. In circumstances of few informative data, this type of uncertainty calls for alternative methods of representation, propagation, analysis and interpretation. In this study, we make a first attempt to identify, model, and jointly propagate aleatory and epistemic uncertainties in the context of DG systems modeling for adequacy assessment. Probability and possibility distributions are used to model the aleatory and epistemic uncertainties, respectively. Evidence theory is used to incorporate the two uncertainties under a single framework. Based on the plausibility and belief functions of evidence theory, the hybrid propagation approach is introduced. A demonstration is given on a DG system adapted from the IEEE 34 nodes distribution test feeder. Compared to the pure probabilistic approach, it is shown that the hybrid propagation is capable of explicitly expressing the imprecision in the knowledge on the DG parameters into the final adequacy values assessed. It also effectively captures the growth of uncertainties with higher DG penetration levels

Large Scale Deployment of Renewables for Electricity Generation

Comparisons of resource assessments suggest resource constraints are not an obstacle to the large-scale deployment of renewable energy technologies. Economic analysis identifies barriers to the adoption of renewable energy sources resulting from market structure, competition in an uneven playing field and various non-market place barriers. However, even if these barriers are removed, the problem of ‘technology lock-out’ remains. The key policy response is strategic deployment coupled with increased R&D support to accelerate the pace of improvement through market experience. The paper suggests significant contributions from various technologies, but does not assess their optimal or maximal market share

Energy Academic Group Compilation of Abstracts 2012-2016

This report highlights the breadth of energy-related student research at NPS and reinforces the importance of energy as an integral aspect of today's Naval enterprise. The abstracts provided are from theses and a capstone project report completed by December 2012-March 2016 graduates.http://archive.org/details/energyacademicgr109454991

A Balanced Energy Plan for the Interior West

Describes a Balanced Energy Plan for the Interior West region of Arizona, New Mexico, Nevada, Utah, Colorado, Wyoming and Montana. Part of the Hewlett Foundation Energy Series

Optimal energy management of a campus microgrid considering financial and economic analysis with demand response strategies

An energy management system (EMS) was proposed for a campus microgrid (µG) with the incorporation of renewable energy resources to reduce the operational expenses and costs. Many uncertainties have created problems for microgrids that limit the generation of photovoltaics, causing an upsurge in the energy market prices, where regulating the voltage or frequency is a challenging task among several microgrid systems, and in the present era, it is an extremely important research area. This type of difficulty may be mitigated in the distribution system by utilizing the optimal demand response (DR) planning strategy and a distributed generator (DG). The goal of this article was to present a strategy proposal for the EMS structure for a campus microgrid to reduce the operational costs while increasing the self-consumption from green DGs. For this reason, a real-time-based institutional campus was investigated here, which aimed to get all of its power from the utility grid. In the proposed scenario, solar panels and wind turbines were considered as non-dispatchable DGs, whereas a diesel generator was considered as a dispatchable DG, with the inclusion of an energy storage system (ESS) to deal with solar radiation disruptions and high utility grid running expenses. The resulting linear mathematical problem was validated and plotted in MATLAB with mixed-integer linear programming (MILP). The simulation findings demonstrated that the proposed model of the EMS reduced the grid electricity costs by 38% for the campus microgrid. The environmental effects, economic effects, and the financial comparison of installed capacity of the PV system were also investigated here, and it was discovered that installing 1000 kW and 2000 kW rooftop solar reduced the GHG generation by up to 365.34 kg CO2/day and 700.68 kg CO2/day, respectively. The significant economic and environmental advantages based on the current scenario encourage campus owners to invest in DGs and to implement the installation of energy storage systems with advanced concepts

The Spatial Economics of Clean Energy in New Jersey

Clean energy policy is critically important in driving reductions of greenhouse gases and mitigating climate change. As clean energy technologies improve over time and interact with social systems and broader energy markets, there is a need for innovative environmental management that supports development of new clean energy policy. Understanding where these technologies may be deployed, quantifying the anticipated benefits, and mitigating risks are required for successful policy optimization. With these considerations in mind, this dissertation explores geothermal heat pumps (GHP), solar photovoltaics, and the Regional Greenhouse Gas Initiative (RGGI). We call upon spatial economics to investigate these topics by incorporating the biophysical environment, socioeconomic factors, and economic considerations in our methodology to approach this problem from a holistic environmental management perspective. Reducing energy end use is a climate mitigation strategy that can be applied across the building, industry, and transportation sectors. Increasing energy efficiency, particularly in the building sector, is a promising means to reduce energy end use. In the second chapter of this dissertation, we perform a place-based investigation of GHP systems in New Jersey. In doing so we provide new baseline information on which building sectors this technology is most used and identify areas of significant clustering. Both of which provide insights for new energy efficiency policy within the study area. In the third chapter, we conduct a life cycle assessment of geothermal heat pumps to assess the cradle-to-grave environmental and human health impacts throughout the lifetime of a system operating in New Jersey. The results of this section highlight lower environmental and human impacts associated with GHP systems operating within New Jersey compared to the rest of the United States. We also conclude that GHP systems are significantly less impactful throughout their lifetime and operation as compared to other heating and cooling configurations that are common in the state. A combination of renewable energy technologies such as wind and solar photovoltaics will be an integral part of the clean energy electric generation portfolio of the future. Understanding where these systems are best located and how the public values their benefits can support smart policy decisions. In the fourth chapter, we evaluate solar photovoltaic potential using hosting capacity interpolation, multi-market suitability models, and remote sensing. The findings show hosting capacity of potential solar siting locations varies within each electric distribution company (EDC) territory. The results of the suitability models highlight areas for targeted local investigations of project suitability and community solar off-taker potential. Our municipal remote sensing analysis yield valuable local scale information of roof geometry, flood hazards, and solar radiation potential which can be used to streamline system siting and design. In the fifth chapter, we conduct a consumer willingness to pay survey for potential community solar customers in New Jersey. Evaluating the responses of over six-hundred residents underscores the common barriers to traditional residential net metering, such as home ownership and financial requirement. It also illuminates consumers’ willingness to participate in community solar projects that improve environmental quality and are sited in commercial settings and landfills. Reducing the carbon dioxide emissions associated with the electric generation sector will be crucial in mitigating future climate change. Emission trading schemes (ETS) are a regulatory approach that forces emitters to internalize the negative externalities of carbon dioxide with the goal of driving emission efficiency improvements and creating funding mechanisms to support other climate mitigation and adaptation efforts. In the sixth chapter, we perform a qualitative policy analysis of the Regional Greenhouse Gas Initiative (RGGI) ETS in the context of generation shifting mitigation. We identify the best mitigation approaches as the program expands to be a combination of increased monitoring and modeling, promoting load reductions through efficiency, and expanding the RGGI program to states within distribution systems that have partial state participation. In New Jersey, successful climate mitigation and clean energy transitions are a function of policy, available technology, and energy markets. Historically, stringent air quality regulations and inexpensive natural gas have led to efficient fossil generation within the state. Additionally, early progressive solar policies have led to a robust solar industry and resulting overall in-state solar photovoltaic capacity ranking high in the nation. Although low-hanging fruit may be relatively sparse, current political environments in the state have been supportive of improved climate action and sparked increased potential for academic research to make tangible contributions to new clean energy policy. As the state continues to transition towards a clean energy future, government administrations, regulatory agencies, grid operators, research institutions, and stakeholders must work alongside each other to develop new policies that support increased climate mitigation. Currently in New Jersey, the potential of clean energy has not been adequately researched, particularly on local and regional scales. The goal of this research is to address this gap by contributing to the body of knowledge in our applied subject areas. The spatial economic approach can be used effectively in clean energy investigations because energy is inherently influenced by economics and geography. We anticipate the overall findings of this work to be applied within the study area to increase clean energy generation and access, promote the clean energy economy, and conserve valuable landscapes