A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies

In a power system with high penetration of renewable power sources, gas-fired units can be considered as a back-up option to improve the balance between generation and consumption in short-term scheduling. Therefore, closer coordination between power and natural gas systems is anticipated. This article presents a novel hybrid information gap decision theory (IGDT)-stochastic cooptimization problem for integrating electricity and natural gas networks to minimize total operation cost with the penetration of wind energy. The proposed model considers not only the uncertainties regarding electrical load demand and wind power output, but also the uncertainties of gas load demands for the residential consumers. The uncertainties of electric load and wind power are handled through a scenario-based approach, and residential gas load uncertainty is handled via IGDT approach with no need for the probability density function. The introduced hybrid model enables the system operator to consider the advantages of both approaches simultaneously. The impact of gas load uncertainty associated with the residential consumers is more significant on the power dispatch of gas-fired plants and power system operation cost since residential gas load demands are prior than gas load demands of gas-fired units. The proposed framework is a bilevel problem that can be reduced to a one-level problem. Also, it can be solved by the implementation of a simple concept without the need for Karush–Kuhn–Tucker conditions. Moreover, emerging flexible energy sources such as the power to gas technology and demand response program are considered in the proposed model for increasing the wind power dispatch, decreasing the total operation cost of the integrated network as well as reducing the effect of system uncertainties on the total operating cost. Numerical results indicate the applicability and effectiveness of the proposed model under different working conditions

Economic efficiencies of the energy flows from the primary resource suppliers to the electric load centers

The economic efficiency of the electric energy system depends not only on the performance of the electric generation and transmission subsystems, but also on the ability to produce and transport the various forms of primary energy, particularly coal and natural gas. However, electric power systems have traditionally been developed and operated without a conscious awareness of the energy system-wide implications, namely the consideration of the integrated dynamics with the fuel markets and infrastructures. This has been partly due to the difficulty of formulating models capable of analyzing the large-scale, complex, time-dependent, and highly interconnected behavior of the integrated energy system. In this dissertation, a novel approach for studying the movements of coal, natural gas, and electricity in an integrated fashion is presented. Conceptually, the model developed is a simplified representation of the national infrastructures, structured as a generalized, multiperiod network composed of nodes and arcs. Under this formulation, fuel supply and electricity demand nodes are connected via a transportation network and the model is solved for the most efficient allocation of quantities and corresponding prices for the mutual benefits of all. The synergistic action of economic, physical, and environmental constraints produces the optimal pattern of energy flows. Key data elements are derived from various publicly available sources, including publications from the Energy Information Administration, survey forms administered by the Federal Energy Regulatory Commission, and databases maintained by the Environmental Protection Agency. The results of different test cases are analyzed to demonstrate that the decentralized level of decision-making combined with imperfect competition may be preventing the realization of potential cost savings. An overall optimization at the national level shows that there are opportunities to better utilize low cost generators, curtailing usage of higher cost units and increasing electric power trade, which would ultimately allow customers to benefit from lower electricity prices. In summary, the model developed is a simulation tool that helps build a better understanding of the complex dynamics and interdependencies of the coal, natural gas, and electricity networks. It enables public and private decision makers to carry out comprehensive analyses of a wide range of issues related to the energy sector, such as strategic planning, economic impact assessment, and the effects of different regulatory regimes

전력시장 시뮬레이션 기법을 활용한 재생에너지 확대가 전력시스템 유연성 및 경제성에 미치는 영향 분석

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2021. 2. 이종수.전 세계적으로 온실가스 감축 목표를 달성하기 위해서 재생에너지 비중을 확대하는 에너지 전환 정책이 시행되고 있다. 하지만, 출력 변동성과 불확실성 특성을 가지고 있는 재생에너지 확대는 전력시스템의 유연성에 문제를 일으킬 수 있으며, 낮은 운영 비용과 국가 정책상의 목적 등에 의해 전력 시장에서 우선 구매되면서 전통 발전원의 급전 우선순위 결정에도 많은 영향을 주게 된다. 이와 같은 맥락에서, 본 연구는 한국의 재생에너지 확대 정책에 의해 재생에너지 발전 비중이 20%를 초과 하는 2031년을 대상으로 전력 시스템의 유연성 평가 및 재생에너지 확대가 전력 시장에 미치는 경제적 영향 분석을 목적으로 한다. 이를 위해서 우선, 혼합정수계획법을 활용하여 하루 전 발전계획 수립 모형을 구축하고, 재생에너지 발전 비중이 6.2%로 상대적으로 낮은 2018년을 기준으로 2031년의 전력 시장 운영 실적과 비교하기 위해서, 구축한 발전계획 수립 모형을 기반으로 전력 시장 시뮬레이션을 수행하였다. 2031년 전력 시스템의 유연성 평가를 위해서 5가지 유연성 공급 용량 산정 시나리오를 설정하고 각 시나리오에 따른 유연성 공급량과 순수요 변동 폭인 유연성 요구량의 시간 단위 비교를 통해서 총 8,760시간에 대한 증∙감발 유연성 부족 횟수를 산출하였다. 유연성 공급 자원으로 운영 예비력만을 고려할 경우, 증발 유연성 측면에서 재생에너지 변동성을 약 94%까지 대응할 수 있지만, 운영 예비력 확보량보다 큰 변동 폭인 약 6% 변동성에 대해서는 속응성 자원의 역할이 필요한 것으로 분석되었다. 반면에, 감발 유연성 측면의 유연성 부족 횟수는 약 18회 수준으로 매우 낮은 발생확률을 보였다. 재생에너지 변동성 분포에 대한 분석 결과를 보면, 고정적으로 운영하던 전통적인 운영 예비력 기준과 다르게 재생에너지 변동성 대응을 위한 유연성 자원은 확보 기준을 탄력적으로 운영할 필요가 있는 것으로 나타난다. 또한, 유연성 측면에서 효율적 대응을 위한 물리적 특성인 높은 증•감발률과 짧은 기동 준비시간을 보유한 발전원들이 운영 예비력에 포함되게 하려면 현행 발전출력 상한제약 방법 개선 및 예비력 보조 서비스 시장의 분리 운영을 검토할 필요가 있겠다. 이때 고려할 수 있는 예비력 보조 서비스 시장 최소 규모는 약 1,620억 원으로 추정되었다. 재생에너지 확대로 인해 2031년의 계통한계가격이 평균적으로 13.7원/kWh 낮아질 것으로 분석되었으며, 더욱이 재생에너지 발전량 비중이 높아질수록 전통 발전원으로 충족시켜야 하는 순수요 크기가 감소하면서 계통한계가격 하락은 더욱 심화할 수도 있다. 이와 같은 시장 가격 하락은 판매사업자의 전력 도매 요금의 동반 하락을 유도할 것처럼 보이지만, 기후변화 대응을 위한 RPS 제도와 배출권거래제를 고려한 전력 구입비 변화에 대한 분석 결과를 보면, 전력량 정산금을 제외한 용량 정산금, 배출권거래비용 및 RPS 의무이행 비용이 상승할 것으로 예측되었다. RPS 의무이행비율, 배출권 유상할당비율 및 배출권 가격 시나리오에 따른 전력 시장 시뮬레이션 결과에 의하면, 평균 전력 구매 단가는 2018년 93.87원/kWh에서 2031년 106.03원/kWh까지 최대 약 13% 상승할 수 있으며, 이는 향후 전력 소매 요금의 인상 압력 요인으로 작용할 수 있다. 본 연구 결과를 종합해보면 다음과 같은 정책적 함의를 끌어낼 수 있다. 첫째, 2031년 전력 시스템의 유연성을 적정 수준으로 확보하기 위해서는 운영 예비력 확보 방법을 발전출력 상한 제약 방식 대신 유연성 요구사항을 충족하는 자원들을 대상으로 한 경쟁 입찰을 통해 확보하는 방안 등 새로운 운영예비력 확보 대안이 고려되어야 한다. 또한, 재생에너지 변동성 대응 목적으로 운영 예비력과 별도로 운영하는 속응성 자원을 차질없이 계획대로 보급하고, 각 유연성 공급 자원별 변동성 대응 메커니즘을 고려하여 재생에너지 발전량 예측시스템을 정교화하여 속응성 자원에 대한 탄력적인 유연성 공급량 확보 기준을 적용해 나가야 할 것이다. 둘째, 재생에너지 확대와 관련한 정책을 개정하거나 신설하고자 할 때는 직접적인 정책의 기대효과뿐만 아니라 판매사업자의 전력 구입비 증가로 인한 전기 요금 인상 압력과 같은 간접적인 파급효과까지 함께 고려해 주어야겠다. RPS 의무할당비율, 배출권거래제 유상할당비율, 배출권 거래 비용 등의 변화로 최대 13%까지 전력 도매가격이 상승할 수 있기 때문이다. 셋째, 재생에너지 발전량과 시장 가격이 점점 상반된 패턴으로 변화할 것으로 예측되기 때문에, 변동비 반영 시장의 정산 규칙이나 시장 가격 산정 방법에 대한 개선 검토 시 이런 패턴 변화를 반드시 고려해야 한다. 또한, 유연성 공급에 참여한 발전사업자들의 보상이 적정한 수준으로 설정되어야 에너지 시장 대비 보조 서비스 시장 참여가 활성화 될 것이다. 마지막으로, 미래 전력 시장에서는 수요 피크와 시장 가격 피크의 불일치가 점점 증대될 수 있으므로, 수요 관리, 경제성 DR, 전기 요금 산정 등 수요 패턴을 고려하는 다양한 정책들이 향후에는 순수요 패턴도 함께 고려하는 방향으로 재검토되어야 할 것이다.To achieve the reduction target of greenhouse gas emissions, energy transition policy is being implemented to expand the share of renewable energy worldwide. However, the expansion of renewable energy not only causes the flexibility problem of the power system due to volatility and uncertainty of renewable energy output, but also affects the merit order of traditional power generation sources due to low operating costs of renewables or national policy objectives. These effects give rise to a huge transformation in power systems with a high share of renewable energy. In this context, this study evaluates the flexibility of the power system and analyzes the economic impact on the power market in 2031, when the share of renewable energy exceeds 20% due to Koreas energy transition policy. First, a mixed-integer linear programming approach was used to formulate the power system day-ahead unit commitment and economic dispatch model, and a power market simulation was conducted to compare the performance of the electricity market in 2031 based on 2018 figures, when the share of renewable energy is relatively low at 6.2%. To assess the flexibility of the power system in 2031, the number of periods of flexibility deficit for 8,760 hours was calculated by comparing the supply of flexibility according to the scenario of available flexibility resources with the flexibility requirement, which is the fluctuation in net load over an hour. The results show that if only the operational reserve is considered as a flexibility supply resource, about 94% of the renewable energy volatility can be dealt with in terms of upward flexibility, but the role of the quick-start generation resources is found to be important for 6% of the ramping event greater than the reserve capacity. On the other hand, the number of times flexibility deficit occurs in terms of downward flexibility is expected to be about 18, showing a very low probability of occurrence. The analysis of the distribution of renewable energy volatility reveals that, unlike the standard for operational reserve, which was traditionally fixed, the resource for responding to flexibility problem in renewable energy needs to operate the flexible securing standard. In addition, it is necessary to review the improvement of the current upper limit method of power output level and the separate operation of the reserve auxiliary service market from the energy service market to ensure that power generation sources suitable for supplying flexibility with physical characteristics for response to flexibility are included in the operational reserve. At this time, the minimum market size of the reserve auxiliary service that could be considered was estimated to be about KRW 162 billion. The expansion of renewable energy will lower the system marginal price by 13.7 KRW/kWh on average in 2031. As the share of renewable energy generation increases, the capacity of net load to be met by traditional power generation decreases, and the drop in the system marginal price may be even worse. Such a decrease in electricity market prices seems to lead to the accompanied decline in the power vendors wholesale electricity price. However, when looking at the result of power purchase cost analysis considering the renewable portfolio standard (RPS) and the emissions trading scheme (ETS) to expand renewable energy, it was predicted that the capacity settlement amount, the emission trading cost, and the RPS obligation fulfillment cost, excluding the electricity settlement amount, would increase. According to the analysis of power market simulation by RPS obligatory rate, paid allocation ratio for emissions trading, and emissions price per unit scenarios, the average power purchase cost may increase up to about 13% from 93.87 KRW/kWh in 2018 to 106.03 KRW/kWh in 2031. This suggests that it could act as a pressure factor to raise electricity rates in the future. The results of this study have the following policy implications. First, to secure the flexibility of the power system to an appropriate level in 2031, it is necessary to consider the alternative method of securing the operating reserve via competitive bidding for flexibility resources that meet the power system requirement instead of the upper limit constraint on generation output. In addition, for the purpose of responding to variability of renewable energy, quick-start generators operated separately from the operational reserve should be implemented as planned. It is also necessary to refine the system for predicting the amount of renewable energy generation in consideration of the mechanism for responding to the variability of each flexibility resource to realize the flexible regulation of flexibility supply amount. Second, if policy makers consider revising or establishing a new policy related to the expansion of renewable energy, it is necessary to examine not only the expected direct effect of the policy but also the indirect ripple effect, such as the pressure to increase electricity rates due to the hike in power purchase costs of vendors. Third, since the amount of renewable energy generation and electricity market price are expected to change in an increasingly inconsistent pattern, it is also important to reconsider the design for the settlement rules of the cost-based pool market or method of deciding the market price. Finally, in the future power market, the pattern difference between the demand peak and the market price peak may increase. Therefore, various policies that consider demand patterns, such as demand management, economical demand response, and electricity fee system, should be reviewed in the direction of considering the net load pattern in the future.Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Research Objectives 6 1.3 Research Outline 9 Chapter 2. Literature Review 12 2.1 Power System Flexibility 12 2.1.1 Sources of Flexibility 15 2.1.2 Studies on Flexibility Evaluation 19 2.2 Generation Scheduling 23 2.2.1 Unit Commitment and Economic Dispatch Model 23 2.2.2 Optimization techniques for solving UC problem with High Renewable Energy Sources Penetration 25 2.3 Research of the Energy policy in Korea 28 2.4 Limitations of previous research and Research Motivation 33 Chapter 3. Methodology 36 3.1 Methodological Framework 36 3.2 Unit Commitment and Economic Dispatch Modeling 40 3.2.1 Generation scheduling using MILP 42 3.2.2 An empirical model for day-ahead unit commitment and economic dispatch 49 3.2.3 Model Input data 58 3.2.4 Evaluation of the power system flexibility 68 3.2.5 Economic impact analysis 72 3.3 Model validation 79 3.3.1 Overview of model validation 79 3.3.2 Model validation result 82 Chapter 4. Empirical Studies 87 4.1 The study on evaluating the power system flexibility 87 4.1.1 Overview of flexibility evaluation and premises of analysis 87 4.1.2 Net load variability and calculation of flexibility requirement 91 4.1.3 Unit commitment and economic dispatch simulation and calculation of flexibility supply amount 96 4.1.4 Empirical results of evaluating the power system flexibility 103 4.2 Composition of flexibility resources and ability to respond to volatility 111 4.2.1 Incentive effect for participation in operational reserve service 112 4.2.2 Composition of operational reserve resources for flexibility supply 117 4.2.3 Volatility response mechanism of operational reserves and quick–start generators 123 4.2.4 Improvement of reserve system and separation of the auxiliary service market 128 4.3 Analysis of the economic impact 132 4.3.1 Premises for economic impact analysis 132 4.3.2 Forecasting SMP and electricity settlement amount 134 4.3.3 Analysis of the impact of policies related to the expansion of renewable energy 138 4.3.4 Empirical results and discussion 143 Chapter 5. Summary and Conclusion 146 5.1 Concluding Remarks and Contribution 146 5.2 Limitations and Future Studies 148 Bibliography 151 Appendix 1: The results of power generation scheduling of pumped-storage power plants 164 Appendix 2: Power market operation performance trend (2001-2019) 166 Abstract (Korean) 168Docto

Stochastic optimization model for coordinated operation of natural gas and electricity networks

Renewable energy sources will anticipate significantly in the future energy system paradigm due to their low cost of operation and low pollution. Considering the renewable generation (e.g., wind) intermittency, flexible gas-fired power plants will continue to play their essential role as the main linkage of natural gas and electricity networks, and hence coordinated operation of these networks is beneficial. Furthermore, uncertainty is always found in gas demand prediction, electricity demand prediction, and output power of wind generation. Therefore, in this paper, a two-stage stochastic model for operation of natural gas and electricity networks is implemented. In order to model uncertainty in these networks, Monte Carlo simulation is applied to generate scenarios representing the uncertain parameters. Afterwards, a scenario reduction algorithm based on distances between the scenarios is applied. Stochastic and deterministic models for natural gas and electricity networks are optimized and compared considering integrated and iterative operation strategies. Furthermore, the value of flexibility options (i.e., electricity storage systems) in dealing with uncertainty is quantified. A case study is presented based on a high pressure 15-node gas system and the IEEE 24-bus reliability test system to validate the applicability of the proposed approach. The results demonstrate that applying the stochastic model of gas and electricity networks as well as considering integrated operation strategy in the presence of flexibility provides different benefits (e.g., 14% cost savings) and enhances the system reliability in the case of contingency

Flexible operation of coal fired power plant integrated with post combustion CO2 capture using model predictive control

The growing demand for CO2 capture from coal-fired power plant (CFPP) has increased the need to improve the dynamic operability of the integrated power generation-CO2 capture plant. Nevertheless, high-level operation of the entire system is difficult to achieve due to the strong interactions between the CFPP and post combustion CO2 capture (PCC) unit. In addition, the control tasks of power generation and CO2 removal are in conflict, since the operation of both processes requires consuming large amount of steam. For these reasons, this paper develops a model for the integrated CFPP-PCC process and analyzes the dynamic relationships for the key variables within the integrated system. Based on the investigation, a centralized model predictive controller is developed to unify the power generation and PCC processes together, involving the key variables of the two systems and the interactions between them. Three operating modes are then studied for the predictive control system with different focuses on the overall system operation; power generation demand tracking and satisfying the CO2 capture requirement. The predictive controller can achieve a flexible operation of the integrated CFPP- PCC system and fully exert its functions in power generation and CO2 reduction

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

Reinforced coordinated control of coal-fired power plant retrofitted with solvent based CO2 capture using model predictive controls

Solvent-based post-combustion CO2 capture (PCC) provides a promising technology for the CO2 removal of coal-fired power plant (CFPP). However, there are strong interactions between the CFPP and the PCC system, which makes it challenging to attain a good control for the integrated plant. The PCC system requires extraction of large amounts of steam from the intermediate/low pressure steam turbine to provide heat for solvent regeneration, which will reduce power generation. Wide-range load variation of power plant will cause strong fluctuation of the flue gas flow and brings in a significant impact on the PCC system. To overcome these issues, this paper presents a reinforced coordinated control scheme for the integrated CFPP-PCC system based on the investigation of the overall plant dynamic behavior. Two model predictive controllers are developed for the CFPP and PCC plants respectively, in which the steam flow rate to re-boiler and the flue-gas flow rate are considered as feed-forward signals to link the two systems together. Three operating modes are considered for designing the coordinated control system, which are: (1) normal operating mode; (2) rapid power load change mode; and (3) strict carbon capture mode. The proposed coordinated controller can enhance the overall performance of the CFPP-PCC plant and achieve a flexible trade-off between power generation and CO2 reduction. Simulation results on a small-scale subcritical CFPP-PCC plant developed on gCCS demonstrates the effectiveness of the proposed controller

Flexibility provision by combined heat and power plants – An evaluation of benefits from a plant and system perspective

Variable renewable electricity generation is likely to constitute a large share of future electricity systems. In such electricity systems, the cost and resource efficiency can be improved by employing strategies to manage variations. This work investigates combined heat and power (CHP) plant flexibility as a variation management strategy in an energy system context, considering the operation and cost-competitiveness of CHP plants. An energy system optimization model with detailed representation of CHP plant flexibility is applied, covering the electricity and district heating sectors in one Swedish electricity price area. The results show that investments in CHP plants are dimensioned based on the demand for district heating rather than electricity. In the system studied, this implies that CHP plant capacity is small relative to electricity system variations, and variation management using CHP plants has a weak impact on the total system cost of supplying electricity and district heating. However, flexibility measures increase CHP plant competitiveness in scenarios with low system flexibility (assuming low availability of hydropower or no thermal energy storage) although investments in CHP capacity are sensitive to fuel cost. It is found that while district heating is the dominant CHP product (constituting 50%–90% of the annual CHP energy output), the dispatchable electricity supply has a high value and comprises around 60% of the annual CHP plant revenue. In all scenarios, operational flexibility of the boiler is more valuable than a flexible steam cycle power-to-heat ratio