Intermittent Resources Research Articles

Meteorological phenomena associated with wind-power ramps downwind of mountainous terrain

Wind-power ramps are a significant source of uncertainty in wind-energy forecasting and are a challenge to electric-grid stability. In the Canadian province of Alberta, strong westerly winds buffet the Rocky Mountains creating an abundant yet intermittent wind energy resource in the plains of Alberta. In the current study, wind-power ramp events have been detected and correlated to several environmental factors including time-of-day, atmospheric stability, season and a Föhn wind event known locally as a Chinook wind at a field wind measurement station downstream of the Rocky Mountains. Large wind-power ramps (a 50% change in power in less than 4 h) were found to occur on days when a Föhn wind was present over 50% of the time. The result highlights the importance of this meteorological phenomenon to wind energy production locally and also in regions where Föhn winds occur. The detected wind-power ramps were found to vary significantly with season, with the strongest wind-power ramps emanating from the Rocky Mountains in the winter months under stable atmospheric conditions.

Hybrid Solar and Coal-fired Steam Power Plant with Air Preheating Using a Centrifugal Solid Particle Receiver

Coal power stations have been hybridised with concentrated solar thermal (CST) fields which producefeedwater or with turbine bleed steam (TBS) heating from directlinear Fresnel to steam technology. This paper assesses solar hybridisation of boiler based steam power plants, whichpreheat boiler combustion air with a novel high temperature CST system based on a solid particle receiver (SPR). This new method of preheating has the potential to increase the solar share of the overall system, improve fuel saving and therefore produce a higher solar to electric conversion efficiency. These benefits result from theSPR solar systems higher operating temperature and integrated thermal storage. The integrated thermal storage also allows a buffered response time for handling transients in the intermittent solar resource. Analysis indicates that air-solarisation of coal plants can result in significantly higher solar to electric conversion efficiency than existing solar hybridisation options. Solarisation by TBS decreases power cycle efficiency due to bleed steam reduction, while solarisation by air-preheating increases the power system efficiency, primarily due to enhanced boiler efficiency brought about by reduced stack losses. The air solarisation option proposed in this paper has beencompared to current TBS with Fresnel based technology. The comparison was conducted by modelling both systems and analysing the thermodynamic heat and mass balance of the steam cycle and boiler using EBSILON®Professional software. Annual simulation tools, which calculate the performance of the solar field, receiver, storage (when applicable) and other system components, were used to model the output of the solar technologies. These tools, coupled with available economic data and cost models for the newly developed solar components, were used to calculate the levelized cost of energy of the compared hybridisation options. It was calculated that the levelized cost of the solar electricity produced by the SPR system was approximately 59%theelectricity produced by the Fresnel hybridisation.

열에너지 저장 암반공동의 형상 및 레이아웃 설계 가이드라인

열에너지 저장은 고온 또는 저온의 잉여 열에너지를 저장하여 수요 발생 시 사용하기 위한 기술로서 에너지의 수요와 공급 사이의 불균형을 해소하고, 이를 통해 에너지 시스템의 효율을 향상시킬 수 있다. 특히 간헐적인 신재생에너지 자원을 열에너지 형태로 변환하거나 저장함으로써 에너지 믹스에서 신재생에너지의 비중을 제고할 수 있으며, 이를 위해서는 열에너지 저장 장치와의 조합이 반드시 필요하다. 지하 암반공동을 이용한 열에너지 저장은 높은 건설비용이 수반되어 그 활용이 제한적이지만, 대규모의 열에너지를 장기간 저장할 수 있는 가장 현실적인 방법이다. 또한 기후조건에 따라 외부로의 열손실이 영향을 받는 지상의 열저장소와는 달리, 열저장 지하 암반공동은 장기 운영 시 주변 암반의 히팅에 따른 열손실의 감소를 기대할 수 있다. 본고에서는 열저장 암반공동의 형상 및 다중배치 설계 시 고려해야 할 주요 인자들을 소개하고, 저장공간의 설계에 대한 가이드라인을 제안하였다. Thermal energy storage (TES) is a technology that stores surplus thermal energy at high or low temperatures for later use when the customer needs it, not just when it is available. TES systems can help balance energy demand and supply and thus improve the overall efficiency of energy systems. Furthermore, the conversion and storage of intermittent renewable resources in the form of thermal energy can help increase the share of renewable resources in the energy mix which refers to the distribution of energy consumption from different sources, and to achieve this, it is essential to combine renewable resources with TES systems. Underground TES using rock caverns, known as cavern thermal energy storage (CTES), is a viable option for large-scale, long-term TES utilization although its applications are limited because of the high construction costs. Furthermore, the heat loss in CTES can significantly be reduced due to the heating of the surrounding rock occurred during long-term TES, which is a distinctive advantage over aboveground TES, in which the heat loss to the surroundings is significantly influenced by climate conditions. In this paper, we introduced important factors that should be considered in the shape and multiple layout design of TES caverns, and proposed guidelines for storage space design.

Ionic Liquid Electrolytes for Redox Flow Batteries

The development of efficient devices that store energy generated from intermittent resources (such as solar energy or wind energy) will play a crucial role for sustainable energy supply. Redox flow batteries (RFBs) are considered to be one of the most promising energy storage devices owing to their capacity for storing very large amounts of energy, low cost and high flexibility of design.1 RFBs store electrical energy by chemical changes to species dissolved in aqueous acidic media in two reaction compartments, which are separated by an ion-conducting membrane.1 However, the use of aqueous systems significantly limits the energy and power density of the RFBs due to the narrow potential window of water. A number of non-aqueous electrolytes based on ruthenium, vanadium, manganese and chromium have been reported in order to increase the cell voltage.2 Notably, a cell potential of 2.2 V was reported in a system that employed vanadium and acetonitrile electrolytes.3 The main problem of non-aqueous RFBs is the possibility that the organic solvents in the liquid electrolytes can evaporate during operation and result in poor long-term stability. Moreover, organic solvents are highly flammable, which may pose a serious hazard. In an effort to combat this problem, we propose room temperature ionic liquids (RTILs) as electrolytes in RFBs. RTILs are thermally stable, non-flammable, conductive and, crucially exhibit very wide electrochemical windows of up to 6.0 V.4 In this poster, the electrochemical behavior of several RFB redox mediators are examined at glassy carbon (GC) electrodes using a RTIL as the electrolyte. The RTIL was 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([C2C1Im][Tf2N], see inset of Figure 1C), and this RTIL was chosen because it has a low viscosity and a large electrochemical window. Figure 1A shows the CVs recorded at GC in 10 mM V(acac)3 in ([C2C1Im][Tf2N], and this response is similar to the electrochemical behavior of V(acac)3 in acetonitrile.3 Three oxidation and reduction processes were observed which were attributed to the redox process of V3+/V2+ (A1/C1), V3+/V4+ (A2/C2) and V4+/V5+(A3/C3). Each process displayed an electrochemically quasi-reversible response. The potential difference between A1/C1 and A2/C2 is 2.0 V and can reach upto 2.3 V for (A1/C1)/A3/C3). Two redox processes were observed when Mn(acac)3 in ([C2C1Im][Tf2N] was studied (Figure 1B). The oxidation/reduction of Mn3+ to Mn2+ (A1/C1) is electrochemically irreversible and its peak-to-peak separation is about 0.55 V at 50 mV s-1, while the Mn3+/Mn4+(A2/C2) is quasi-reversible process with peak-to-peak separation of 0.1 V at 50 mV s-1. In the case of Cr electrochemistry in [C2C1Im][Tf2N], electrochemical analysis indicated that the electro generated Cr4+ (A3/C3) is unstable in this RTIL, suggesting the presence of an additional chemical step during electron transfer (see Figure 1C, A2/A2 was assigned to the redox process of Cr3+/Cr2+ and A1/C1 was to Cr2+/Cr1+). Notably, a similar electrochemical response was also observed when acetonitrile was used as the electrolyte.5 The diffusion coefficients of V, Cr and Mn in [C2C1Im][Tf2N] are 1.8 x 10-7 cm2 s-1, 1.6 x 10-7 cm2 s-1 and 1.5 x 10-7 cm2 s-1 respectively. Finally, the effect of ionic liquid composition (changing the anions) on the electrochemistry of each redox mediator will be presented.

Operation cost minimization of photovoltaic–diesel–battery hybrid systems

In this paper, two control strategies involving “continuous” and “ON/OFF” operation of the diesel generator in the solar photovoltaic–diesel–battery hybrid systems are modeled. The main purpose of these developed models is to minimize the hybrid system's operation cost while finding the optimal power flow considering the intermittent solar resource, the battery state of charge and the fluctuating load demand. The non-linearity of the load demand, the non-linearity of the diesel generator fuel consumption curve as well as the battery operation limits have been considered in the development of the models. The simulations have been performed using “fmincon” for the continuous operation and “intlinprog” for the ON/OFF operation strategy implemented in Matlab. These models have been applied to two test examples; the simulation results are analyzed and compared to the case where the diesel generator is used alone to supply the given load demand. The results show that using the developed photovoltaic–diesel–battery optimal operation control models, significant fuel saving can be achieved compared to the case where the diesel is used alone to supply the same load requirements.

Optimal Strategies Modeling in Electricity Market for Electric Vehicles Integration in Presence of Intermittent Resources

Electric vehicles (EVs) as an alternative to the current fossil fuel vehicles represent the most promising green approach to electrification of an important portion of the global transportation sector. This uncertain load brings new challenges to market-oriented demand response programs (DRPs) specifically in the presence of renewable energy resources (RER). Being a special type of load, EVs are highly capable of providing a significant amount of flexible load demand through participating in various types of DRPs, while using their battery storage potentials allows a higher penetration level of intermittent RER in the grid. Therefore, there is a strong need to increase EV owner’s participation in the market by providing attractive financial benefit-based decision-making tools and simplifying the market process to enhance system reliability and reduce price volatility. In this paper, a novel optimal decision-making methodology is proposed which, unlike previous works, utilizes a grid characteristic’s model within a game-theoretical approach, conflicting and capturing economic interests of both players together and evaluates the optimum strategies for a successful market operation in simplest way. This approach can facilitate both EV owners and utilities to derive their robust bidding strategies, in which they can create a simple business case analysis to weigh their benefits of participation in the market. To evaluate the performance, a simulation framework with uncertain load demands and generation has been developed and compared. The results show that the proposed strategy is appropriate for use in real-time automated DRPs.

Application of a modified flux-coupling type superconducting fault current limiter to transient performance enhancement of micro-grid

Concerning the application and development of a micro-grid system which is designed to accommodate high penetration of intermittent renewable resources, one of the main issues is related to an increase in the fault-current level. It is crucial to ensure the micro-grid’s operational stability and service reliability when a fault occurs in the main network. In this paper, our research group suggests a modified flux-coupling type superconducting fault current limiter (SFCL) to enhance the transient performance of a typical micro-grid system. The SFCL is installed at the point of common coupling (PCC) between the main network and the micro-grid, and it is expected to actively improve the micro-grid’s fault ride-through capability. And for some specific faults, the micro-grid should disconnect from the main network, and the SFCL’s contribution is to make the micro-grid carry out a smooth transition between its grid-connected and islanded modes. Related theory derivation, technical discussion and simulation analysis are performed. From the demonstrated results, applying the SFCL can effectively limit the fault current, maintain the power balance, and enhance the voltage and frequency stability of the micro-grid.

Uncertainty-averse TRANSCO planning for accommodating renewable energy in CO2 reduction environment

The concern of the environment and energy sustainability requests a crucial target of CO2 abatement and results in a relatively high penetration of renewable energy generation in the transmission system. For maintaining system reliability and security, the transmission company (TRANSCO) has to make strategic planning to handle the uncertainty challenges from the intermittent renewable energy resources. In this paper, a stochastic multi-period multi-objective transmission planning (MPMOTP) model is proposed to reduce correlated uncertainties from renewable energy generation, conventional generation, demand-side variations, market price volatility, and transmission configuration. Three objectives, i.e. social CO2 reduction benefit, energy purchase and network expansion cost and power delivery profit, are optimized simultaneously by a developed two-phase multi-objective particle swarm optimization (MOPSO) method. The feasibility and effectiveness of the proposed uncertainty-averse MPMOTP model have been verified by the IEEE 24-bus test system.

Resource and revenue potential of California residential load participation in ancillary services

Increasing penetrations of intermittent renewable energy resources will require additional power system services. California recently adopted an energy storage mandate to support its renewable portfolio standard, which requires 33% of delivered energy from renewables by 2020. The objective of this paper is to estimate the amount of energy storage that could be provided by residential thermostatically controlled loads, such as refrigerators and air conditioners, and the amount of revenue that could be earned by loads participating in ancillary services markets. We model load aggregations as virtual energy storage, and use simple dynamical system models and publicly available data to generate our resource and revenue estimates. We find that the resource potential is large: 10–40GW/8–12GWh, which is significantly more than that required by the mandate. We also find that regulation and spinning/non-spinning reserve revenues vary significantly depending upon type of load and, for heat pumps and air conditioners, climate zone. For example, mean regulation revenues for refrigerators are $11/year, for electric water heaters are $24/year, for air conditioners are $0-32/year, and for heat pumps are $22–56/year. Both consumer choices, such as appliance settings, and policy, such as the design of ancillary service compensation and appliance standards, could increase revenue potentials.

Two-phase Short-term Scheduling Approach with Intermittent Renewable Energy Resources and Demand Response

Neglecting input power from renewable energy sources in the unit commitment can lead to excessive commitment of fossil generation, inefficient use of committed power and potential reliability problems. In this paper, a two-phase short-term scheduling with intermittent renewable resources and storage methodology is presented. The first-phase is the day-ahead model which determines the unit commitment operational decisions and feeds them into the second-phase which is a real-time economic dispatch. Perfect forecasting for renewable energy sources is considering besides customer based line is used for demand forecasting. A case study is presented to illustrate the application of the proponed methodology

Interval Power Flow Analysis Using Linear Relaxation and Optimality-Based Bounds Tightening (OBBT) Methods

With increasingly large scale of intermittent and non-dispatchable resources being integrated into power systems, the power flow problem presents greater uncertainty. In order to obtain the upper and lower bounds of power flow solutions including voltage magnitudes, voltage angles and line flows, Cartesian coordinates-based power flow is utilized in this paper. A quadratically constrained quadratic programming (QCQP) model is then established to formulate the interval power flow problem. This non-convex QCQP model is relaxed to linear programming problem by introducing convex and concave enclosures of the original feasible region. To improve the solutions bounds while still encompassing the true interval solution, optimality-based bounds tightening (OBBT) method is employed to find a better outer hull of the feasible region. Numerical results on IEEE 9-bus, 30-bus, 57-bus, and 118-bus test systems validate the effectiveness of the proposed method.

Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty

The integration of intermittent and stochastic renewable energy resources requires increased flexibility in the operation of the electric grid. Storage, broadly speaking, provides the flexibility of shifting energy over time; network, on the other hand, provides the flexibility of shifting energy over geographical locations. The optimal control of storage networks in stochastic environments is an important open problem. The key challenge is that, even in small networks, the corresponding constrained stochastic control problems on continuous spaces suffer from curses of dimensionality and are intractable in general settings. For large networks, no efficient algorithm is known to give optimal or provably near-optimal performance for this problem. This paper provides an efficient algorithm to solve this problem with performance guarantees. We study the operation of storage networks, i.e., a storage system interconnected via a power network. An online algorithm, termed online modified greedy algorithm, is developed for the corresponding constrained stochastic control problem. A sub-optimality bound for the algorithm is derived and a semidefinite program is constructed to minimize the bound. In many cases, the bound approaches zero so that the algorithm is near-optimal. A task-based distributed implementation of the online algorithm relying only on local information and neighborhood communication is then developed based on the alternating direction method of multipliers. Numerical examples verify the established theoretical performance bounds and demonstrate the scalability of the algorithm.

A Decision Framework for Optimal Pairing of Wind and Demand Response Resources

Day-ahead electricity markets do not readily accommodate power from intermittent resources such as wind because of the scheduling difficulties presented by the uncertainty and variability in these resources. Numerous entities have developed methods to improve wind forecasting and thereby reduce the uncertainty in a day-ahead schedule for wind power generation. This paper introduces a decision framework for addressing the inevitable remaining variability resulting from imperfect forecasts. The framework uses a paired resource, such as demand response, gas turbine, or storage, to mitigate the generation scheduling errors due to wind forecast error. The methodology determines the cost-effective percentage, or adjustment factor, of the forecast error to mitigate at each successive market stage, e.g., 1 h and 10 min ahead of dispatch. This framework is applicable to any wind farm in a region with available pairing resources, although the magnitude of adjustment factors will be specific to each region as the factors are related to the statistics of the wind resource and the forecast accuracy at each time period. Historical wind data from New England are used to illustrate and analyze this approach. Results indicate that such resource pairing via the proposed decision framework will significantly reduce the need for an independent system operator to procure additional balancing resources when wind power participates in the markets.

Optimal Planning of a Smart Microgrid Including Demand Response and Intermittent Renewable Energy Resources

Heating/cooling systems have played an important role in building energy and comfort management. There have been intensive discussions about the integration of heating/cooling systems into the smart grid infrastructure over the past decade, yet controlling the operation of heating/cooling systems in a smart grid with high penetration of renewable resources has not been addressed clearly. This study has investigated the suitability of a novel active controller applied to heating/cooling systems in the context of smart grid with high penetration of renewable energies. The proposed controller operates by responding to a combination of internal set points and external signals (e.g. the availability of renewable energy resources and welfare of customers) from a single local controller. The heating/cooling systems management minimizes the overall cost of the simulated smart microgrid, the size of smart microgrid units, and the imported energy from the distribution grid through an optimization process. It also at the same time maximizes the reliability of the smart microgrid. Demonstrated results confirm the capability of the proposed heating/cooling system controller on the planning of a smart microgrid.

Linking Hawaii’s Islands with wind energy

This study assesses the economic and greenhouse gas (GHG) emissions impacts of a proposed 400-MW wind farm (Big Wind) in Hawaii. Due to its island setting, this project is a hybrid between onshore and offshore wind development. An undersea cable would carry the power from Maui County, which has high-quality wind areas, to the population center of Oahu, which has fewer sites for wind power. The project is additionally motivated by Hawaii’s high electricity rates, which are nearly three times the national average, and a renewable portfolio standard (RPS) mandating that 40 % of the State’s electricity sales be met through renewable sources by the year 2030. Using an economy-wide computable general equilibrium model coupled with a fully dynamic optimization model for the electric sector, we find that the 400- MW wind project increases gross state product by $2.2 billion (in net present value) and average annual per capita income by $60 per year. Although there are potentially near-term welfare losses if there are capital cost overruns, fuel costs are a dominant factor in determining the cost-effectiveness of the project. However, without upgrades to Hawaii’s grid and/or its operations, there is a trade-off between investment in wind energy projects and solar PV. If higher levels of intermittent resources cannot be integrated into the system, higher-cost biofuels serve a more prominent role in meeting the RPS. Without upgrades, wind and solar PV generation are restricted, and hence, reduction in GHG emissions in excess of those present without the Big Wind project is negligible. With upgrades, the project is estimated to reduce GHG emissions by an additional $$\hbox {12 MMTCO}_{2}$$ from 2020 to 2040.

Security-based multi-objective congestion management for emission reduction in power system

Power system operation in the era of post-restructuring faces several challenges: transmission congestion frequently occurs, security is deterred more than in the past, emission reduction is becoming a matter of importance and intermittent renewable power generation resources (RPGR) have been widely promoted. This paper intends to solve these challenges in a multi-objective optimisation framework. The proposed procedure comprises two stages: in the a priori stage, transmission congestion management cost (TCMC) and emission are traded-off via a proposed stochastic augmented ε-constraint technique which yields a set of non-dominated solutions. In the a posteriori stage, a solution is selected by considering power system security. For this purpose, two strategies are proposed: in the first strategy, based on a proposed managerial vision, a combination of data envelopment analysis introduced by Charnes, Cooper, and Rhodes (CCR-DEA), cross-efficiency technique and robustness analysis is deployed to select the most robust super-efficient solution. The advantage of the proposed a posteriori approach is that selecting the final solution is not subjected to assigning weights to the objective functions and/or providing higher-level information. In the second strategy, first the effective scenarios due to outage of transmission components are identified using CCR-DEA and next, each scenarios’ degree of severity (DOS) is obtained using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The sums of the DOS of non-dominated solutions’ effective scenarios are evaluated for final decision making. The proposed approach is applied to IEEE 24 bus test system and the results are analysed.

Time Series Analysis of Rural Distribution Grids in the Presence of HTS Cables and Intermittent Renewable Resources

Time Series Analysis of Rural Distribution Grids in the Presence of HTS Cables and Intermittent Renewable Resources

Review of energy storage technologies for sustainable power networks

A significant percentage of the global energy demand is expected to be met through widespread supply of renewable electricity in the near future. However, renewable energy outputs are variable due to a stochastic characteristic of their sources. Electrical power system operators around the world are faced with difficulties of integrating these variable power sources into the existing power grids. Energy storage systems are one of the possible solutions for mitigating the effects of intermittent renewable resources on networks, allowing increased renewable energy utilization, and providing flexibility and ancillary services for managing future electricity supply/demand challenges. This paper presents a comprehensive review of energy storage technologies that are currently engaged for power applications, including pumped hydro, compressed-air, battery, flywheel, capacitor, supercapacitor, superconducting magnetic and thermal systems. The study compares the characteristics of these systems, and presents their technological development status and capital costs. Some directions for future work are also highlighted. Furthermore, particular attention is paid to some new storage technologies such as: adiabatic, underwater, isothermal and small-scale compressed-air; sub-surface, seawater and variable-speed pumped hydro, and pumped heat systems, which hold opportunity for future smart electrical grid applications, but there is need for more research to actualize their promising potentials.

Stochastic simulation of power systems with integrated intermittent renewable resources

Abstract We report on the development of a comprehensive, stochastic simulation methodology that provides the capability to quantify the impacts of integrated renewable resources on the power system economics, emissions and reliability variable effects over longer periods with the various sources of uncertainty explicitly represented. We model the uncertainty in the demands, the available capacity of conventional generation resources and the time-varying, intermittent renewable resources, with their temporal and spatial correlations, as discrete-time random processes. We deploy Monte Carlo simulation techniques to systematically sample these random processes and emulate the side-by-side power system and transmission-constrained day-ahead market operations. We construct the market outcome sample paths for use in the approximation of the expected values of the various metrics of interest. Our efforts to address the implementational aspects of the methodology so as to ensure computational tractability for large-scale systems over longer periods include the use of representative simulation periods, parallelization and variance reduction techniques. Applications of the approach include planning and investment studies and the formulation and analysis of policy. We illustrate the capabilities and effectiveness of the simulation approach on representative study cases on a modified WECC 240-bus system. The results provide valuable insights into the impacts of deepening penetration of wind resources.

Optimal hybrid renewable energy design in autonomous system using Iterative-Pareto-Fuzzy technique

The intermittent resources which cause fluctuations in the power generated by photovoltaic (PV) and wind turbine (WT) system made the optimal design for these resources essential, especially for an autonomous system. Therefore, this paper aims to obtain the best combination size between the hybrid PV–WT-battery system that yields minimum cost and maximum reliability. In addition to that, the minimization of unutilized surplus power is also being considered as one of the design objectives. An Iterative-Pareto-Fuzzy (IPF) technique is used to obtain the best compromised solution between all the design objectives. Results show that the inclusion of unutilized surplus power criteria gave different set of Pareto points to the system and provided a different result for the best compromised solution. The total cost of the hybrid system is lower when the minimization of unutilized surplus power criteria is taken into account in the analysis.