A hybrid simulation model for urban weatherization programs

In the face of climate change, cities are becoming interested in developing policies and programs that will increase sustainability and resilience in their neighborhoods. In particular, government officials, planning agencies, and residents of the City of Des Moines, Iowa, would like to find ways to improve the energy efficiency of their urban built environment. Weatherization of residential buildings is one way of reducing energy consumption, particularly in winter months. While financial incentives might increase residents\u27 adoption of weatherization measures, research has shown that social interactions more strongly influence this decision. To enable stakeholders to explore different scenarios for encouraging weatherization, a hybrid simulation model that integrates an urban energy model with an agent-based model has been developed to connect the physical processes of built environment systems with the goals, constraints, and interactions that drive resident behavior. This paper describes an application of the model to a specific residential city block

An Agent Based Simulation of Smart Metering Technology Adoption

Based on the classic behavioural theory “the Theory of Planned Behaviour”, we develop an agent-based model to simulate the diffusion of smart metering technology in the electricity market. We simulate the emergent adoption of smart metering technology under different management strategies and economic regulations. Our research results show that in terms of boosting the take-off of smart meters in the electricity market, choosing the initial users on a random and geographically dispersed basis and encouraging meter competition between energy suppliers can be two very effective strategies. We also observe an “S-curve” diffusion of smart metering technology and a “lock-in” effect in the model. The research results provide us with insights as to effective policies and strategies for the roll-out of smart metering technology in the electricity market

Factor Price Risk and the Diffusion of Conservation Technology: Evidence from the Water Industry

The paper examines the influence of factor price risk on factor-use efficiency through the adoption of conservation technology. The effect of a mean-preserving increase in factor price risk on optimal input-use efficiency is shown to be conditional on the own-price elasticity of factor use evaluated at the initial equilibrium. The conceptual analysis indicates that that there may be a discrepancy between the aggregate and firm-level effects of price risk on efficiency. Theoretical results are tested and confirmed using a unique data set from the water industry.technology adoption; risk; conservation; water resources; ordered probit

Greening Demand: Energy Consumption and U.S. Climate Policy

The search for greener, less polluting energy supplies has dominated discussions of u.s. climate change strategy, but we often overlook cheaper and faster greenhouse gas emissions reductions achievable through energy efficiency and conservation. In this article, I outline a decade-long greening demand agenda to reduce the amount of energy consumed in the United States. The federal government should aim to reduce U.S. energy consumption by fifteen percent by 2016 and twenty percent by 2020 to achieve needed reductions in greenhouse gas emissions. While the United States has achieved notable efficiency gains since the 1970s, several market failures and other barriers continue to serve as obstacles to energy savings. These include principal-agent divergence, high implicit discount rates used in decision making on efficiency upgrades, and outmoded forms of utility regulation. I demonstrate how a greening demand agenda, centered on price signals, performance standards, informational tools, and changes in utility regulation can be used to overcome these barriers. Many of the challenges are technical and scientific, but law will play a central role in structuring incentives and shaping national markets for efficiency innovations. I conclude with some thoughts on the technical and political feasibility of greening demand

Energy Efficiency Economics and Policy

Energy efficiency and conservation are considered key means for reducing greenhouse gas emissions and achieving other energy policy goals, but associated market behavior and policy responses have engendered debates in the economic literature. We review economic concepts underlying consumer decisionmaking in energy efficiency and conservation and examine related empirical literature. In particular, we provide an economic perspective on the range of market barriers, market failures, and behavioral failures that have been cited in the energy efficiency context. We assess the extent to which these conditions provide a motivation for policy intervention in energy-using product markets, including an examination of the evidence on policy effectiveness and cost. While theory and empirical evidence suggest there is potential for welfare-enhancing energy efficiency policies, many open questions remain, particularly relating to the extent of some of the key market and behavioral failures.energy efficiency, appliance standards, energy policy, market failures, behavioral failures

Are Peer Effects Present in Residential Solar Installations? Evidence from Minnesota and Wisconsin

There are geographic differences in the rate of adoption of residential photovoltaic (PV) solar. Are adoption rates in small scale localities (counties and zip codes) influenced by previous, nearby adoptions? This paper adds to the literature on Peer Effects with an analysis of Minnesota and Wisconsin zip codes. I use residential adoption data from the OpenPV Project in an empirical analysis of social interactions. My findings indicate that there is a small but significant effect of nearby adoptions at the zip code level. These peer effects are shown to be nuanced by policy incentives such as the XCEL Solar Rewards Program. I additionally engage in a case study analysis of the relationship of some localities

Demand Response Strategy Based on Reinforcement Learning and Fuzzy Reasoning for Home Energy Management

As energy demand continues to increase, demand response (DR) programs in the electricity distribution grid are gaining momentum and their adoption is set to grow gradually over the years ahead. Demand response schemes seek to incentivise consumers to use green energy and reduce their electricity usage during peak periods which helps support grid balancing of supply-demand and generate revenue by selling surplus of energy back to the grid. This paper proposes an effective energy management system for residential demand response using Reinforcement Learning (RL) and Fuzzy Reasoning (FR). RL is considered as a model-free control strategy which learns from the interaction with its environment by performing actions and evaluating the results. The proposed algorithm considers human preference by directly integrating user feedback into its control logic using fuzzy reasoning as reward functions. Q-learning, a RL strategy based on a reward mechanism, is used to make optimal decisions to schedule the operation of smart home appliances by shifting controllable appliances from peak periods, when electricity prices are high, to off-peak hours, when electricity prices are lower without affecting the customer’s preferences. The proposed approach works with a single agent to control 14 household appliances and uses a reduced number of state-action pairs and fuzzy logic for rewards functions to evaluate an action taken for a certain state. The simulation results show that the proposed appliances scheduling approach can smooth the power consumption profile and minimise the electricity cost while considering user’s preferences, user’s feedbacks on each action taken and his/her preference settings. A user-interface is developed in MATLAB/Simulink for the Home Energy Management System (HEMS) to demonstrate the proposed DR scheme. The simulation tool includes features such as smart appliances, electricity pricing signals, smart meters, solar photovoltaic generation, battery energy storage, electric vehicle and grid supply.Peer reviewe

Is There an Energy Efficiency Gap?

Many analysts have argued that energy efficiency investments offer an enormous “win-win” opportunity to both reduce negative externalities and save money. This overview paper presents a simple model of investment in energy-using capital stock with two types of market failures: first, uninternalized externalities from energy consumption, and second, forces such as imperfect information that cause consumers and firms not to exploit privately-profitable energy efficiency investments. The model clarifies that only if the second type of market failure cannot be addressed directly through mechanisms such as information provision, energy efficiency subsidies and standards may be merited. We therefore review the empirical work on the magnitude of profitable unexploited energy efficiency investments, a literature which frequently does not meet modern standards for credibly estimating the net present value of energy cost savings and often leaves other benefits and costs unmeasured. These problems notwithstanding, recent empirical work in a variety of contexts implies that on average the magnitude of profitable unexploited investment opportunities is much smaller than engineering-accounting studies suggest. Finally, there is tremendous opportunity and need for policy-relevant research that utilizes randomized controlled trials and quasi-experimental techniques to estimate the returns to energy efficiency investments and the welfare effects of energy efficiency programs.