Efficient energy management for the internet of things in smart cities

The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities

China and East Asian Energy : Prospects and Issues

In October 2005, the Crawford School (then the Asia Pacific School of Economics and Government) within the Australian National University (ANU) initiated a major research project on China and East Asian Energy. The project is being undertaken under the schools East Asia Forum in conjunction with the China Economy and Business Program. The first conference in the series being organised under the auspices of the China and East Asian Energy Strategies Research Program was hosted in Beijing by the Energy Research Institute and the ANU on 1011 October 2005. It was the first of five annual conferences in the program. This book brings together the key papers presented at that conference.

Hydrogen and fuel cell technologies for heating: A review

The debate on low-carbon heat in Europe has become focused on a narrow range of technological options and has largely neglected hydrogen and fuel cell technologies, despite these receiving strong support towards commercialisation in Asia. This review examines the potential benefits of these technologies across different markets, particularly the current state of development and performance of fuel cell micro-CHP. Fuel cells offer some important benefits over other low-carbon heating technologies, and steady cost reductions through innovation are bringing fuel cells close to commercialisation in several countries. Moreover, fuel cells offer wider energy system benefits for high-latitude countries with peak electricity demands in winter. Hydrogen is a zero-carbon alternative to natural gas, which could be particularly valuable for those countries with extensive natural gas distribution networks, but many national energy system models examine neither hydrogen nor fuel cells for heating. There is a need to include hydrogen and fuel cell heating technologies in future scenario analyses, and for policymakers to take into account the full value of the potential contribution of hydrogen and fuel cells to low-carbon energy systems

In-State Gas Demand Study

Northern Economics, Inc.; Institute of Social and Economic Research, UAA; SAIC. In-State Gas Demand Study. Prepared for TransCanada Alaska Company, LLC. January 2010TransCanada Alaska Company, LLC

The Proposed U.S.-South Korea Free Trade Agreement (KORUS FTA): Provisions and Implications

[Excerpt] On June 30, 2007, U.S. and South Korean trade officials signed the proposed U.S.-South Korean Free Trade Agreement (KORUS FTA) for their respective countries. If approved, the KORUS FTA would be the second-largest FTA that South Korea has signed to date, after the agreement with the European Union (EU). It would be the second-largest (next to North American Free Trade Agreement, NAFTA) in which the United States participates. South Korea is the seventhlargest trading partner of the United States and the United States is South Korea’s third-largest trading partner. Various studies conclude that the agreement would increase bilateral trade and investment flows. The final text of the proposed KORUS FTA covers a wide range of trade and investment issues and, therefore, could have substantial economic implications for both the United States and South Korea. The agreement will not enter into force unless Congress approves implementation legislation. The negotiations were conducted under the trade promotion authority (TPA), also called fast-track trade authority, that Congress granted the President under the Bipartisan Trade Promotion Act of 2002 (P.L. 107-210). Under TPA the President has the discretion on when to submit the implementing legislation to Congress. President Bush did not submit the legislation because of differences with the Democratic leadership over treatment of autos and beef, among other issues. Early in his Administration, President Obama indicated the need to resolve those issues before he would submit the implementing legislation. On December 3, 2010, after a series of arduous negotiations and missed deadlines, President Obama and President Lee announced that their negotiators reached agreement on modifications in the KORUS FTA, and that they were prepared to move ahead to getting the agreement approved by the respective legislatures. The White House is expected to send implementing legislation to the 112th Congress and that it would like to see Congress approve the agreement by July 1 of this year. The modifications are in the form of changes in phase-out periods for tariffs on autos, a new safeguard provision on autos, and concessions by South Korea on allowing a larger number of U.S. cars into South Korea under U.S. safety standards than was the case under the original KORUS FTA provisions. The issue of full U.S. beef access was not resolved because of the political sensitivity of the issue in South Korea. In 2008, when President Lee reached a separate agreement with the United States to lift South Korea’s ban on U.S. beef imports, massive anti-South Korean government protests forced the two governments to renegotiate its terms. The U.S. beef sector has largely supported the KORUS FTA. A broad swath of the U.S. business community supports the KORUS FTA . With the modifications in the agreement reached in December, this group also includes the three Detroit-based auto manufacturers and the United Auto Workers (UAW) union. It still faces opposition from some labor unions and other groups, including Public Citizen. Many U.S. supporters view passage of the KORUS FTA as important to secure new opportunities in the South Korean market, while opponents claim that the KORUS FTA does not go far enough to break down South Korean trade barriers or that the agreement will encourage U.S. companies to move their production offshore at the expense of U.S. workers. Other observers have suggested the outcome of the KORUS FTA could have implications for the U.S.-South Korean alliance as a whole, as well as on U.S. Asia policy and U.S. trade policy, particularly in light of an FTA signed in by South Korea and the EU that is expected to go into effect on July 1, 2011

Insufficient Incentives for Investment in Electricity Generation

In theory, competitive electricity markets can provide incentives for efficient investment in generating capacity. We show that if consumers and investors are risk averse, investment is efficient only if investors in generating capacity can sign long-term contracts with consumers. Otherwise the uncovered price risk increases financing costs, reduces equilibrium investment levels, distorts technology choice towards less capital-intensive generation and reduces consumer utility. We observe insufficient levels of long-term contracts in existing markets, possibly because retail companies are not credible counter-parties if their final customer can switch easily. With consumer franchise, retailers can sign long-term contracts, but this solution comes at the expense of the idea of retail competition. Alternative capacity mechanisms to stimulate investment are discussed

인공신경망 발전량 예측 불확실성을 고려한 가상발전소 모델예측제어

학위논문(박사) -- 서울대학교대학원 : 공과대학 기계공학부, 2022.2. 차석원.This study presents statistical and control analyses for grid resources to enhance the stability and efficiency on their operations. More specifically, this study focuses on cost-optimal model predictive control for a virtual power plant with the uncertainty in neural network power forecasting. Chapter 2 analyzes the monitoring data of solar photovoltaic power plants (PVs) distributed throughout Korea. Errors within the raw data are categorized according to their causes and symptoms. The effect of typical errors on the statistical analysis is particularly evaluated for a day-ahead hourly PV power forecast study. Chapter 3 addresses a control strategy for an energy storage system (ESS). A virtual power plant or a microgrid with a commercial building load, PV generation, and ESS charge/discharge operation is targeted as a behind-the-meter consumer-generator. Economic dispatch scheduling problem for the ESS is formulated as a mixed-integer linear program. The main goal of the control problem is optimizing the economic benefit under the time-of-use tariff and future uncertainties. Peak control as a regulation ancillary market service can be also applied during the optimization. The resulting control schedule robustly guarantees the economic benefit even under the forecast uncertainties in load power consumption and PV power generation patterns. Chapter 4 presents a more specific case of day-ahead hourly ESS scheduling. An integration of a PV and ESS is considered as a control target. Power transactions between the grid and resources are normally settled according to the time-of-use tariff. Additional incentive is provided with respect to the imbalance between the forecasted-scheduled power and actual dispatch power. This incentive policy stands for the imbalance tariff of a regulation ancillary service market. Accurate forecasting and robust scheduling functions are required for the energy management system to maximize both revenues. The PV power forecast model, which is based on a recurrent neural network, uses a convolutional neural network discriminator to decrease the gap between its open-loop one-step-ahead training and closed-loop multi-step-ahead test dynamics. This generative adversarial network concept for the model training process ensures a stable day-ahead hourly forecast performance. The robust ESS scheduling model handles the remaining forecast error as a box uncertainty set to consider the cost-optimality and cost-robustness of the control schedule. The scheduling model is formulated as a concise mixed-integer linear program to enable fast online optimization with the consideration for both transaction and incentive revenues.본 논문에서는 전력망 내 에너지자원들의 운영에 있어 안정성과 효율을 향상시키기 위한 통계분석 및 제어분석 방법과 그 결과를 서술한다. 더욱 상세하게는 인공신경망 기반 발전량 예측 결과의 불확정성을 고려한 가상발전소 전력시장 비용 최적화 모델예측제어를 목표로 한다. 제2장에서는 대한민국 전역에 분포한 태양광발전소들의 모니터링 데이터에 대한 분석 결과를 서술한다. 원시 데이터 내에 존재하는 오류들이 목록화되며, 그 원인과 증상에 따라 분류된다. 일반적으로 발생 가능한 데이터 오류들이 통계분석 결과에 미치는 영향을 확인하기 위해, 인공신경망 기반 통계적 태양광발전소 발전량 예측 모델의 성능에 대한 오류 데이터의 영향이 평가된다. 제3장에서는 전력망 내 에너지저장장치에 대한 제어 방법론을 제시한다. 상업용 건물 부하, 태양광발전소 발전, 에너지저장장치 충방전 운전을 포함하는 가상발전소 또는 마이크로그리드가 계량기 후단에 위치한 전력 소비원이자 발전원으로 제시된다. 에너지저장장치를 위한 경제적 급전계획 문제는 혼합정수 선형계획법 형태로 수식화된다. 최적화 목표는 시간대별 요금제하에서 미래 부하와 발전량 예측 불확실성을 고려한 마이크로그리드 경제적 이득 최대화이며, 피크 제어에 대한 목표 역시 보조서비스 형태로 적용 가능하다. 최적화 문제 해결을 통해 도출된 충방전 제어 스케줄은 마이크로그리드 내 부하와 발전량 예측에 대한 불확실성에도 불구하고 경제적 이득을 강건하게 보장할 수 있다. 제4장에서는 특수 조건하에서의 에너지저장장치 하루 전 시간대별 운전 스케줄 도출 방법론을 제시한다. 태양광발전소와 에너지저장장치를 물리적 또는 가상으로 연결한 집합전력자원이 고려된다. 집합전력자원과 전력망 사이의 전력 거래는 일반적인 시간대별 요금제하에서 이루어진다. 전력망 보조서비스에 해당하는 불균형 요금제가 대한민국 전력시장에서의 분산자원 중개사업자 인센티브 제도 형태로 추가 고려된다. 해당 제도 하에서 집합전력자원은 전일 예측 또는 결정된 운전 스케줄과 실제 스케줄 사이의 오차율에 따라 추가적인 인센티브를 부여받을 수 있다. 집합자원을 위한 에너지관리시스템은 시간대별 요금제와 인센티브 각각에 따른 경제적 이득을 최대화하기 위하여 정확한 예측 기능과 강건한 스케줄 도출 기능을 제공한다. 제안되는 RNN 기반 태양광발전소 발전량 예측 모델은 개방회로 형태의 학습 과정과 폐회로 형태의 사용 방식 사이의 차이를 줄이기 위해 CNN 기반 식별기를 적용한다. 모델 학습 과정에 적용되는 이 GAN 개념은 하루 전 도출한 시간대별 운전 스케줄이 안정적이도록 지원한다. 제안되는 에너지저장장치를 위한 강건 스케줄 도출 모델은 남아있는 예측 오차를 박스 형태의 불확실성 집합으로 처리하여, 도출된 제어 스케줄의 경제적 최적성과 강건성을 보장한다. 스케줄 도출 모델은 간결한 혼합정수 선형계획법 형태로 수식화되어 전력 거래 수익과 인센티브 수익 양쪽 모두를 고려한 빠른 실시간 최적화가 가능하다.1 Introduction 1 2 Analysis of Data Errors in the Solar Photovoltaic Power Plant Monitoring System Database 8 2.1 Background 9 2.2 Solar Photovoltaic Power Plants in Korea 11 2.3 Solar Photovoltaic Power Plants for Analysis 14 2.4 Errors in Static Information Data 16 2.4.1 Errors: Missing or Redundant Static Information Data 19 2.4.2 Errors: Incorrect Specification Data 20 2.5 Errors in Monitoring Data 21 2.5.1 Errors: Invalid Peak Power Values 21 2.5.2 Errors: Invalid Units 23 2.5.3 Errors: Conflictions Between Static and Monitoring Data 23 2.5.4 Errors: Garbage or Corrupted Values 24 2.5.5 Errors: Terminations of Daily Monitoring 26 2.5.6 Errors: Long-term Disconnections 27 2.5.7 Errors: Fluctuating Data Transmission Periods 28 2.5.8 Errors: Disharmonious Data Collection Timings 30 2.6 Analyses with Error Data 33 2.6.1 Effect of Incorrect Location Information 38 2.6.2 Effect of Invalid Monitoring Data Values 40 2.6.3 Effect of Missing Monitoring Data 42 2.7 Conclusion 45 2.8 Acknowledgments 47 3 Robust Scheduling of a Microgrid Energy Storage System with Ancillary Service Considerations 48 3.1 Background 49 3.2 System Architecture 52 3.3 Robust MILP Optimization 55 3.3.1 ESS Constraints 55 3.3.2 Non-Robust Approach 56 3.3.3 Intuitive Approach 58 3.3.4 ESS Power Partitioning Approach 60 3.3.5 Combined Constraint Approach 63 3.4 ESS Efficiency Maps 65 3.5 External Working Conditions 68 3.5.1 Peak Control 69 3.5.2 Demand Response 71 3.6 Simulation Results 72 3.6.1 Computation Time 72 3.6.2 Cost Robustness 76 3.6.3 Precise ESS Control 77 3.6.4 External Working Condition 79 3.7 Conclusion 81 3.8 Acknowledgments 82 4 Robust PV-BESS Scheduling for a Grid with Incentive for Forecast Accuracy 83 4.1 Background 84 4.2 PV Power Forecast Model 88 4.2.1 Data Preprocessing 88 4.2.2 RNN-based Sequence Generator 90 4.2.3 CNN-based Sequence Discriminator 93 4.2.4 Training Objectives 94 4.2.5 Training and Validation 96 4.3 Robust BESS Scheduling 98 4.3.1 Power Transaction Revenue 98 4.3.2 Forecast Accuracy Incentive 102 4.4 Results 106 4.4.1 Benchmark Models for PV Power Forecasting 106 4.4.2 Stability of the PV Power Forecast Results 107 4.4.3 Accuracy of the PV Power Forecast Results 109 4.4.4 Incentive Analysis for the PV Power Forecast Results 110 4.4.5 Effect of Input Data Accuracy on Forecast Results 111 4.4.6 Robust BESS Scheduling for the Transaction Revenue 112 4.4.7 Computation Speed of the Scheduling Problems 116 4.4.8 Online Optimization for the Incentive Revenue 117 4.5 Conclusion 119 4.6 Appendix 120 4.6.1 A Toy Example for the Robust Optimization Result 120 4.7 Acknowledgments 121 5 Conclusion 122 Bibliography 125박

World Nuclear Industry Status Report 2013

Two years after the Fukushima disaster started unfolding on 11 March 2011, its impact on the global nuclear industry has become increasingly visible. Global electricity generation from nuclear plants dropped by a historic 7 percent in 2012, adding to the record drop of 4 percent in 2011. This World Nuclear Industry Status Report 2013 (WNISR) provides a global overview of the history, the current status and the trends of nuclear power programs worldwide