Unlocking the Potential of Flexible Energy Resources to Help Balance the Power Grid

Flexible energy resources can help balance the power grid by providing different types of ancillary services. However, the balancing potential of most types of resources is restricted by physical constraints such as the size of their energy buffer, limits on power-ramp rates, or control delays. Using the example of Secondary Frequency Regulation, this paper shows how the flexibility of various resources can be exploited more efficiently by considering multiple resources with complementary physical properties and controlling them in a coordinated way. To this end, optimal adjustable control policies are computed based on robust optimization. Our problem formulation takes into account power ramp-rate constraints explicitly, and accurately models the different timescales and lead times of the energy and reserve markets. Simulations demonstrate that aggregations of select resources can offer significantly more regulation capacity than the resources could provide individually.Comment: arXiv admin note: text overlap with arXiv:1804.0389

Hybrid storage system coupled with PV power plant for primary frequency control

Transitioning from fossil fuel classical generators to intermittent, non-synchronous sources like solar and wind presents a series of technical challenges to be overcome on large scale. A specific issue is related with the concept of inertia of the electrical system: the less the number of generators with rotating masses connected to the grid, the less the value of total inertia of the system. Solar driven generating units such as PV present no mechanical inertia, therefore their increase in the electricity generation mix decreases the total inertia of the system, which lower the overall reliability of the system. Logically, it is of fundamental importance to ensure that PV power plants are more and more capable to provide ancillary services to improve the stability of the grid, especially in terms of frequency. The need for faster frequency regulation and voltage control in the electrical system can be ensured effectively by energy storage systems. In the purpose of this study it is addressed the possibility of large battery systems to overcome the variability of the solar resource, and the forecasting error, resulting in higher profit for a PV plant operator. The methodology consists in the formulation and the resolution of a Non-Linear Programming (NLP) problem, implemented in GAMS, applied to a 9.4 MW PV power plant. The output of the simulation determines the parameters that characterize the optimal Hybrid Storage System, in order to increase the profit during one typical day of solar radiation (01 April), while participating actively in the PFC. The result of the investigation determines that the most profitable hybrid storage system to be coupled with the PVPP is formed by a 883 kWh Lithium Ion Battery and a 32 kWh High Speed Flywheel. The analysis is finally complemented with a realistic simulation in Simulink environment in which is developed and implemented a prototype of EM

Electricity market design

Published: 02 November 2017 Electricity markets are designed to provide reliable electricity at least cost to consumers. This paper describes how the best designs satisfy the twin goals of short-run efficiency-making the best use of existing resources-and long-run efficiency-promoting efficient investment in new resources. The core elements are a day-ahead market for optimal scheduling of resources and a real-time market for security-constrained economic dispatch. Resources directly offer to produce per their underlying economics and then the system operator centrally optimizes all resources to maximize social welfare. Locational marginal prices, reflecting the marginal value of energy at each time and location, are used in settlement. This spot market provides the basis for forward contracting, which enables participants to manage risk and improves bidding incentives in the spot market. There are important differences in electricity markets around the world, reflecting different economic and political settings. Electricity markets are undergoing a transformation as the resource mix transitions from fossil fuels to renewables. The main renewables, wind and solar, are intermittent, have zero marginal cost, and lack inertia. These challenges can be met with battery storage and improved demand response. However, good governance is needed to assure the market rules adapt to meet new challenges

A Review of the Monitoring of Market Power The Possible Roles of TSOs in Monitoring for Market Power Issues in Congested Transmission Systems

The paper surveys the literature and publicly available information on market power monitoring in electricity wholesale markets. After briefly reviewing definitions, strategies and methods of mitigating market power we examine the various methods of detecting market power that have been employed by academics and market monitors/regulators. These techniques include structural and behavioural indices and analysis as well as various simulation approaches. The applications of these tools range from spot market mitigation and congestion management through to long-term market design assessment and merger decisions. Various market-power monitoring units already track market behaviour and produce indices. Our survey shows that these units collect a large amount of data from various market participants and we identify the crucial role of the transmission system operators with their access to dispatch and system information. Easily accessible and comprehensive data supports effective market power monitoring and facilitates market design evaluation. The discretion required for effective market monitoring is facilitated by institutional independence.Electricity, liberalisation, market power, regulation

Multi-Interval Rolling-Window Joint Dispatch and Pricing of Energy and Reserve under Uncertainty

In this paper, the intra-day multi-interval rolling-window joint dispatch and pricing of energy and reserve is studied under increasing volatile and uncertain renewable generations. A look-ahead energy-reserve co-optimization model is proposed for the rolling-window dispatch, where possible contingencies and load/renewable forecast errors over the look-ahead window are modeled as several scenario trajectories, while generation, especially its ramp, is jointly scheduled with reserve to minimize the expected system cost considering these scenarios. Based on the proposed model, marginal prices of energy and reserve are derived, which incorporate shadow prices of generators' individual ramping capability limits to eliminate their possible ramping-induced opportunity costs or arbitrages. We prove that under mild conditions, the proposed market design provides dispatch-following incentives to generators without the need for out-of-the-market uplifts, and truthful-bidding incentives of price-taking generators can be guaranteed as well. Some discussions are also made on how to fit the proposed framework into current market practice. These findings are validated in numerical simulations

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

Improving data center efficiency through smart grid integration and intelligent analytics

The ever-increasing growth of the demand in IT computing, storage and large-scale cloud services leads to the proliferation of data centers that consist of (tens of) thousands of servers. As a result, data centers are now among the largest electricity consumers worldwide. Data center energy and resource efficiency has started to receive significant attention due to its economical, environmental, and performance impacts. In tandem, facing increasing challenges in stabilizing the power grids due to growing needs of intermittent renewable energy integration, power market operators have started to offer a number of demand response (DR) opportunities for energy consumers (such as data centers) to receive credits by modulating their power consumption dynamically following specific requirements. This dissertation claims that data centers have strong capabilities to emerge as major enablers of substantial electricity integration from renewables. The participation of data centers into emerging DR, such as regulation service reserves (RSRs), enables the growth of the data center in a sustainable, environmentally neutral, or even beneficial way, while also significantly reducing data center electricity costs. In this dissertation, we first model data center participation in DR, and then propose runtime policies to dynamically modulate data center power in response to independent system operator (ISO) requests, leveraging advanced server power and workload management techniques. We also propose energy and reserve bidding strategies to minimize the data center energy cost. Our results demonstrate that a typical data center can achieve up to 44% monetary savings in its electricity cost with RSR provision, dramatically surpassing savings achieved by traditional energy management strategies. In addition, we investigate the capabilities and benefits of various types of energy storage devices (ESDs) in DR. Finally, we demonstrate RSR provision in practice on a real server. In addition to its contributions on improving data center energy efficiency, this dissertation also proposes a novel method to address data center management efficiency. We propose an intelligent system analytics approach, "discovery by example", which leverages fingerprinting and machine learning methods to automatically discover software and system changes. Our approach eases runtime data center introspection and reduces the cost of system management.2018-11-04T00:00:00