Land Use Planning for Solar Energy: Resource Guide

This document was created to help New York State localities develop and adopt solar friendly policies and plans. It begins by presenting the local government’s role in land use planning and regulation and introduces common characteristics of “solar friendly” communities. The resource then describes how municipalities should begin a solar energy initiative through an official policy statement that provides support for solar energy and that authorizes a task force to shepherd the process, appropriate studies, training programs for staff and board members, inter-municipal partnerships, and outside funding sources. Next, the document explains how municipalities should engage the entire community in the solar energy initiative process to ensure support for the initiative and its implementation. Finally, the resource presents local planning best practices that communities can incorporate into their comprehensive plans, subarea plans, or other plans. Throughout, this document provides helpful resources and examples that communities can use to develop effective solar energy policies and plans

Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

Integrated Framework for Analyzing Clean Energy Technology Subsidies

Renewable energy technologies can significantly reduce fossil fuel consumption and greenhouse gas emissions associated with the energy sector. In US, both federal and state governments have implemented numerous policies and programs to support these technologies. But these policies require a substantial amount of public spending. In this study, an integrated model to identify optimal subsidy schedules for clean energy technologies that maximize social benefits less subsidy costs is developed. The national flexible optimal subsidy schedule for residential solar PV begins at $585/kW and declines to zero in 14 years. An alternative analytical model is also presented to analyze technological features affecting subsidy design. Three important factors determining the social benefits of subsidizing the use of clean energy technology are examined: the price sensitivity of adoption, induced cost reductions through learning, and environmental benefits. Results show that optimal subsidy schedules for utility wind are roughly constant over time. In contrast, optimal residential solar subsidies either decline over time or are not desirable (subsidy of zero). The results imply that the optimal subsidy for utility wind is justified mainly through the direct environmental benefits, unlike residential solar PV, in which indirect technological progress benefits primarily justify the subsidy. The effects of multiple adoption modeling and parameter choice alternatives on optimal subsidy design are also explored. The study considers three different model structures for rooftop solar adoption consisting of a combination of single and multiple explanatory variables. Results show that the scale of sensitivity of optimal subsidy designs to technology learning rate assumptions depends on the model choice. This dissertation shows that analytical inputs can be instrumental in informing policymakers deciding on subsidy schedules promoting renewable technologies. These tools can integrate environmental benefits and the complex interaction between the subsidy, diffusion patterns, and technology cost trajectories to ensure socially optimal policy designs

That's Not Fair: Tariff Structures for Electric Utilities with Rooftop Solar

(1) Problem definition: Utility regulators are grappling to devise compensation schemes for customers who sell rooftop solar generation back to the grid, balancing environmental interests and the financial interests of utilities, solar system installers, and retail customers. This is difficult: Regulatory changes made in Nevada in 2015 to protect Nevada's utility induced SolarCity, the market leader in solar systems, to suspend local operations. We show that the choice of tariff structure is crucial to achieving socially desirable objectives. (2) Academic/Practical Relevance: It is important for regulators to understand how tariff structure interacts with social objectives. This has implications for consumers, regulators and industry. (3) Methodology: We use a sequential game to analyze the regulator's social welfare maximization problem in a market with a regulated utility, an unregulated, price-setting, profit-maximizing solar system installer, and customers who endogenously determine whether to adopt solar or not, based on utility tariffs, solar prices and their heterogeneous usage profiles and generation potentials. (4) Results: We illustrate that the effectiveness of tariff structures is not governed simply by the number of free tariff parameters, but by the functions these parameters serve. In particular, an effective tariff must discriminate among customer usage tiers between customers with and without rooftop solar to achieve socially desirable outcomes. We present a tariff structure with these two characteristics and show how it can be implemented as a simple buy-all, sell-all tariff while retaining its favorable properties. We illustrate our findings numerically using data from Nevada and New Mexico, two states grappling with this issue. (5) Managerial Implications: Many utilities in the U.S. operate tariff structures that are missing at least one of the two identified features. Regulators must overhaul these tariff structures to adequately safeguard all stake-holders

Carbon Free Boston: Social equity report 2019

OVERVIEW: In January 2019, the Boston Green Ribbon Commission released its Carbon Free Boston: Summary Report, identifying potential options for the City of Boston to meet its goal of becoming carbon neutral by 2050. The report found that reaching carbon neutrality by 2050 requires three mutually-reinforcing strategies in key sectors: 1) deepen energy efficiency while reducing energy demand, 2) electrify activity to the fullest practical extent, and 3) use fuels and electricity that are 100 percent free of greenhouse gases (GHGs). The Summary Report detailed the ways in which these technical strategies will transform Boston’s physical infrastructure, including its buildings, energy supply, transportation, and waste management systems. The Summary Report also highlighted that it is how these strategies are designed and implemented that matter most in ensuring an effective and equitable transition to carbon neutrality. Equity concerns exist for every option the City has to reduce GHG emissions. The services provided by each sector are not experienced equally across Boston’s communities. Low-income families and families of color are more likely to live in residences that are in poor physical condition, leading to high utility bills, unsafe and unhealthy indoor environments, and high GHG emissions.1 Those same families face greater exposure to harmful outdoor air pollution compared to others. The access and reliability of public transportation is disproportionately worse in neighborhoods with large populations of people of color, and large swaths of vulnerable neighborhoods, from East Boston to Mattapan, do not have ready access to the city’s bike network. Income inequality is a growing national issue and is particularly acute in Boston, which consistently ranks among the highest US cities in regards to income disparities. With the release of Imagine Boston 2030, Mayor Walsh committed to make Boston more equitable, affordable, connected, and resilient. The Summary Report outlined the broad strokes of how action to reach carbon neutrality intersects with equity. A just transition to carbon neutrality improves environmental quality for all Bostonians, prioritizes socially vulnerable populations, seeks to redress current and past injustice, and creates economic and social opportunities for all. This Carbon Free Boston: Social Equity Report provides a deeper equity context for Carbon Free Boston as a whole, and for each strategy area, by demonstrating how inequitable and unjust the playing field is for socially vulnerable Bostonians and why equity must be integrated into policy design and implementation. This report summarizes the current landscape of climate action work for each strategy area and evaluates how it currently impacts inequity. Finally, this report provides guidance to the City and partners on how to do better; it lays out the attributes of an equitable approach to carbon neutrality, framed around three guiding principles: 1) plan carefully to avoid unintended consequences, 2) be intentional in design through a clear equity lens, and 3) practice inclusivity from start to finish

That’s Not Fair: Tariff Structures for Electric Utilities with Rooftop Solar

Problem definition: Utility regulators are grappling to devise compensation schemes for customers who sell rooftop solar generation back to the grid, balancing environmental interests and the financial interests of utilities, solar system installers, and retail customers. This is difficult: Regulatory changes made in Nevada in 2015 to protect Nevada’s utility induced SolarCity, the market leader in solar systems, to suspend local operations. We show that the choice of utility tariff structure is crucial to achieving socially desirable objectives. Academic/practical relevance: It is important for regulators to understand how tariff structure interacts with social objectives. This has implications for consumers, regulators, and industry. Methodology: We use a sequential game to analyze the regulator’s social welfare maximization problem in a market with a regulated utility; an unregulated, price-setting, profit-maximizing solar system installer; and customers who endogenously determine whether to adopt solar or not, based on utility tariffs, solar prices, and their heterogeneous usage profiles and generation potentials. Results: We illustrate that the effectiveness of tariff structures is not governed simply by the number of free tariff parameters, but by the functions these parameters serve. In particular, an effective tariff must discriminate among customer usage tiers and between customers with and without rooftop solar to achieve socially desirable outcomes. We present a tariff structure with these two characteristics and show how it can be implemented as a simple buy-all, sell-all tariff while retaining its favorable properties. We illustrate our findings numerically using data from Nevada and New Mexico, two states grappling with this issue. Managerial implications: Many utilities in the United States operate tariff structures that are missing at least one of the two identified features. Regulators must overhaul these tariff structures to adequately safeguard all stakeholders

Overcoming barriers to solar and wind energy adoption in two Asian giants: India and Indonesia

Solar and wind electricity generation technologies have become cost competitive and account for a growing share of global investment in new electricity generation capacity. Both India and Indonesia have ambitious targets for adoption of these technologies, and India has an impressive current rate of uptake. Substantial obstacles exist, however, including the entrenched positions of coal and other fossil fuels, regulatory barriers to market access, and weak abilities of electricity utilities to manage intermittent renewables. This paper reviews these obstacles and discusses strategies to overcome them. We focus on the use of reverse auction processes able to deliver low-price solar and wind contracts, as are being successfully employed in India, on tax and subsidy reform options, on regulatory and incentive-design strategies, on approaches to bolster grid management capacities, and on the importance of minimizing protectionist barriers. Our analysis covers both small-scale and large-scale systems.Australian National University 'Zero-Carbon Energy for the Asia-Pacific' Grand Challenge projec

Optimizing the Implementation of Green Technologies Under Climate Change Uncertainty

In this study, we aim to investigate the application of the green technologies (i.e., green roofs (GRs), Photovoltaic (PV) panels, and battery integrated PV systems) under climate change-related uncertainty through three separate, but inherently related studies, and utilize optimization methods to provide new solutions or improve the currently available methodsFirst, we develop a model to evaluate and optimize the joint placement of PV panels and GRs under climate change uncertainty. We consider the efficiency drop of PV panels due to heat, savings from GRs, and the interaction between them. We develop a two-stage stochastic programming model to optimally place PV panels and GRs under climate change uncertainty to maximize the overall profit. We calibrate the model and then conduct a case study on the City of Knoxville, TN.Second, we study the diffusion rate of the green technologies under different climate projections for the City of Knoxville through the integration of simulation and dynamic programming. We aim to investigate the diffusion rates for PV panels and/or GRs under climate change uncertainty in the City of Knoxville, TN. We further investigate the effect of different and evaluate their effects on the diffusion rate. We first present the agent based framework and the mathematical model behind it. Then, we study the effects of different policies on the results and rate of diffusion.Lastly, We aim to study a Lithium-ion battery load connected to a PV system to store the excess generated electricity throughout the day. The stored energy is then used when the PV system is not able to generate electricity due to a lack of direct solar radiation. This study is an attempt to minimize the cost of electricity bill for a medium sized household by maximizing the battery package utilization. We develop a Markov decision processes (MDP) model to capture the stochastic nature of the panels\u27 output due to weather. Due to the minute reduction in the Li-ion battery capacity per day, we have to deal with an excessively large state space. Hence, we utilize reinforcement learning methods (i.e., Q-Learning) to find the optimal policy

Opportunities and Obstacles in the Transition to a Distributed Network of Rooftop Solar: A Multi-Method Approach

This paper investigates the feasibility and viability of providing power to Ada County, Idaho, using a distributed network of rooftop solar photovoltaic panels. Using a multi-disciplinary and multi-method modeling approach, a detailed simulation is performed where existing structures are retro-fitted with grid-tied solar photovoltaic systems using currently available technology. Feasibility is determined using simulated supply and demand per building, while viability is determined through standard financial metrics used in the energy sector. A major critique of solar energy comes from the vast amounts of space required to efficiently capture solar power, along with the inefficiencies created by transmission loss and intermittency. Under a system where structures become both producers and consumers of energy, with PV panels deployed in unused rooftop space, this paper mitigates those critiques and analyzes the results. Four case scenarios are discussed based on the perspectives of differing energy stakeholders; consumers, private firms, public utilities, and national governments