Bilevel approach to wind-CSP day-ahead scheduling with spinning reserve under controllable degree of trust

This paper proposes a day-ahead schedule harmonization between wind power plants and concentrating solar thermal power plants having thermal energy storage. The negative correlation between wind power and solar power is computed and an artificial neural network method estimates the power. The schedule is carried out by a bilevel mathematical programming approach. The upper-level determines energy and spinning reserve schedule by the maximization of profit subject to all lower-level problems. Lower-level problems minimize the post-contingency power output. A controllable degree of trust on the schedule is introduced based on n – K security criterion for worst-case contingency. The approach uses duality theory and problem approximations for a conversion into an equivalent mixed-integer linear programming problem. A case study is presented to illustrate the effectiveness of the approach for power producers not only with transmission constraints, but also valuing safekeeping on the day-ahead schedule to ensure a degree trust on the satisfaction of compromises within electricity markets.     

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

The North Atlantic Oscillation (NAO) is a large-scale atmospheric circulation pattern driving climate variability in north-western Europe. As the deployment of wind-powered generation expands on electricity networks across Europe, the impacts of the NAO on the electricity system will be amplified. This study assesses the impact of the NAO, via wind-power generation, on the electricity market considering thermal generation costs, wholesale electricity prices and wind generation subsidies. A Monte Carlo approach is used to model NAO phases and generate hourly wind speed time-series data, electricity demand and fuel input data. A least-cost unit commitment and economic dispatch model is used to simulate an island electricity system, modelled on the all-island Irish electricity system. The impact of the NAO obviously depends on the level of wind capacity within an electricity system. Our results indicate that on average a switch from negative to positive NAO phase can reduce thermal generation costs by up to 8%, reduce wholesale electricity prices by as much as €1.5/MWh, and increase wind power generators' revenue by 12%.     

Risk‐based optimal energy management of virtual power plant with uncertainties considering responsive loads

This paper proposes a stochastic scheduling model to determine optimal operation of generation and storage units of a virtual power plant (VPP) for participating in a joint energy and regulation service (RS) market under uncertainty. Beside electricity, the VPP provides required RSs according to the probability of delivery request in the electricity market. A new model for providing RS is introduced in which the dispatchable generation units are financially compensated with their readiness declarations and will be charged/paid for their real‐time down/up regulations. Besides, the VPP sets up incentive price‐quantity curves to benefit from the potential of demand side management in both energy and RS market. Within the model presented here, the VPP consists of two types of generation units: wind turbine and standby diesel generator; the latter is modeled by considering CO₂‐emission penalty costs. The given uncertainties are divided into two parts. Firstly, the uncertainties from the energy market price are simulated using information gap decision theory to evaluate the risk‐based resource scheduling for both risk‐taker and risk‐averse VPP. Other uncertainties affecting decision making such as wind turbine generation, load, regulation up/down calling probabilities, and regulation market prices are modeled via scenario trees. Three typical case studies are implemented to validate the performance and effectiveness of the proposed scheduling approach.     

Potential role of power authorities in offshore wind power development in the US

This article examines how power authorities could facilitate and manage offshore wind power development in US coastal waters. The power authority structure is an American 20th century institution for managing energy resources—a form of a public authority or public corporation dedicated to creating, operating and maintaining electric generation and transmission infrastructure. Offshore wind power is characterized by high capital costs but no fuel costs and thus low operating costs. Therefore a power authority, by virtue of its access to low-cost capital and managerial flexibility, could facilitate offshore wind power development by reducing financial risk of developing and lowering debt payments, thus improving the risk profile and lowering the cost of electricity production. Additionally, power authorities can be made up of multiple states, thus opening the possibility for joint action by neighboring coastal states. Using primary and secondary data, we undertake an in-depth analysis of the potential benefits and shortcomings of a power authority approach.     

The optimization of hybrid energy conversion systems using the dynamic programming model—Rapsody

The paper describes a stochastic, dynamic programming model, RAPSODY, which is designed to analyse and determine optimal operating strategies for a hybrid electricity generating system comprising up to three diesel sets with optional battery storage and augmented by variable wind or photo-voltaic power. The model takes capital, operating and maintenance, and fuel costs into account to assess the optimal operating strategy for the auxiliary and to calculate the average daily cost of satisfying an electrical load profile which may also contain a stochastic element. In doing so, the decreased fuel efficiency and lifetime of the diesel set as it is operated below full capacity is explicitly taken into consideration as is a further important cost component attributable to switching on. The model is provided with an efficient optimizing routine which allows the user to obtain optimal component sizes for a particular load profile and wind or solar resource. An example is given in which a hybrid wind power system incorporating battery storage and an auxiliary diesel generator is optimized. For the case studied, the auxiliary switching cost and the shape of its operating cost function were important in defining the optimal operating strategy which was a significant factor in minimizing generating costs.     

Optimization of hybrid solar energy sources/wind turbine systems integrated to utility grids as microgrid (MG) under pool/bilateral/hybrid electricity market using PSO

This study presents an optimized design of microgrid (MG) in distribution systems with multiple distributed generation (DG) units under different market policies such as pool/hybrid electricity market.Proposed microgrid includes various energy sources such as photovoltaic array and wind turbine with energy storage devices such as battery bank.In this study, microgrid is considered as independent power producer company (IPP) in power system. Price of selling/buying power in on-peak or off-peak for MG, DG and upstream power system (DISCO) under pool/bilateral/hybrid electricity market are different. In this study, particle swarm optimization (PSO) algorithm has been implemented for the optimization of the microgrid cost. The costs include capital cost, replacement cost, operation and maintenance costs and production cost for microgrid and DGs. Then, an objective function to maximize total net present worth (NPW) is presented. PSO approach is employed to obtain the minimum cost of microgrid, during interconnected operation by optimizing the production of local DGs and power exchanges with the main distribution grid. The optimization algorithm is applied to a typical LV network operating under different market policies.     

A novel optimization model for combined wind power accommodation and electric boiler with thermal storage

As the installed capacity of wind power continues to increase, the problem of curtailed wind power is becoming serious in China, especially in the northern region during the winter heating season. To solve the problem of wind‐heat conflict during the heating period in the Three North area, an electric boiler with thermal storage (EBTS) is installed at the end of the grid where wind power is difficult to accommodate and using curtailed wind power to supply heat promotes local accommodation. In this paper, a multi‐objective optimization model of wind power accommodation based on the wind power–EBTS system for heating is established. The goals of maximizing wind power accommodation, minimizing the number of times EBTS must be adjusted, and minimizing operating costs are presented, and a bi‐level optimization scheme is designed. An improved multi‐objective particle swarm optimization algorithm is used to solve these functions, and an optimal compromise solution from the generated Pareto solution set is filtered using the fuzzy membership method. Based on actual data from a demonstration project in China's Jilin Province, the simulation results verify that this method can effectively reduce operating costs and improve wind power accommodation.     

Geographic aggregation and wind power output variance in Denmark

At modest penetration, wind power merely substitutes electricity generated typically at thermal power plants. In this case, wind power only provides economic benefits in terms of saved marginal fuel and operation and maintenance costs. At higher penetrations, it becomes increasingly important for the energy system to be able to operate without costly reserve capacity awaiting fluctuations in demand or wind power generation. Existing transmission interconnections have mainly been established in order to assist in reducing the reserve capacity of thermal power systems. While indeed relevant in thermal systems, this is typically even more important in renewable energy-based systems, in which fluctuations to a large extent are uncontrollable. This makes interconnected systems an interesting option for integrating electricity produced from such energy sources. Using a Danish example, this article demonstrates how different demand and wind production variations in different geographical areas assist in evening out fluctuations and reducing imbalances in systems with high penetrations of wind power. By exploiting these variations, the needs for reserve capacity and condensing mode power generation are reduced. However, the article also demonstrates that there are limits to what can be gained on this account.     

Simulation of energy use in buildings with multiple micro generators

This paper focuses on the detailed modelling of micro combined heat and power (mCHP) modules and their interaction with other renewable micro generators in domestic applications based on an integrated modular modelling approach. The simulation model has been developed using Matlab/Simulink and incorporates a Stirling engine mCHP module embedded in a lumped-parameter domestic energy model, together with contributions from micro wind and photovoltaic modules. The Stirling cycle component model is based on experimental identification of a domestic-scale system which includes start up and shut down characteristics. The integrated model is used to explore the interactions between the various energy supply technologies and results are presented showing the most favourable operating conditions that can be used to inform the design of advanced energy control strategies in building. The integrated model offers an improvement on previous models of this kind in that a fully-dynamic approach is adopted for the equipment and plant enabling fast changing load events such as switching on/off domestic loads and hot water, to be accurately captured at a minimum interval of 1 min. The model is applied to two typical 3- and 4-bedroom UK house types equipped with a mCHP module and two other renewable energy technologies for a whole year. Results of the two cases show that the electrical contribution of a Stirling engine type mCHP heavily depends on the thermal demand of the building and that up to 19% of the locally-generated electricity is exported whilst meeting a similar percentage of the overall annual electricity demand. Results also show that the increased number of switching of mCHP module has an impact on seasonal module efficiency and overall fuel utilisation. The results demonstrate the need for the analysis of equipment design and optimal sizing of thermal and electrical energy storage.     

Dispatch modeling of a regional power generation system – Integrating wind power

A modeling tool has been developed which can be used to analyze interaction between intermittent wind power generation and thermal power plant generation in a regional electricity grid system. The model uses a mixed integer programming (MIP) approach to determine the power plant dispatch strategy which yields the lowest systems costs. In the model, each large thermal plant is described separately, including properties such as start-up time, start-up cost and minimum load level. The model is evaluated using western Denmark as a case study.For western Denmark, it is found that the inclusion of start-up performance (i.e. start-up time and related costs) and minimum load level of the power generating units have a significant impact on the results. It is shown that the inclusion of these aspects influences the analysis of the effect of wind power variations on the production patterns of thermal units in the system. The model demonstrates how the introduction of wind power production and associated variations change the dispatch order of the large thermal power plants in the western Denmark system so that the unit with the lowest running costs no longer has the highest capacity factor. It is shown that this effect only is detected if start-up performance and minimum load level limitations are included in the optimization. It can also be concluded that start-up performance and minimum load level must be taken into account if the total system costs and emissions are not to be underestimated. The simulations show that if these aspects are disregarded, both total costs and total emissions of the power system are underestimated, with 5% in the case of western Denmark. Models such as the one developed in this work can be efficient tools to understand the effects of large-scale wind power integration in a power generation system with base load plants.     

The economics of wind power with energy storage

We develop a nonlinear mathematical optimization program for investigating the economic and environmental implications of wind penetration in electrical grids and evaluating how hydropower storage could be used to offset wind power intermittence. When wind power is added to an electrical grid consisting of thermal and hydropower plants, it increases system variability and results in a need for additional peak-load, gas-fired generators. Our empirical application using load data for Alberta's electrical grid shows that costs of wind-generated electricity vary from $37 per MWh to $68/MWh, and depend primarily on the wind profiles of installed turbines. Costs of reducing CO₂ emissions are estimated to be $41–$56 per t CO₂. When pumped hydro storage is introduced in the system or the capacity of the water reservoirs is enhanced, the hydropower facility could provide most of the peak load requirements obviating the need to build large peak-load gas generators.     

Network constrained wind integration on Vancouver Island

The aim of this study is to determine the costs and carbon emissions associated with operating a hydro-dominated electricity generation system (Vancouver Island, Canada) with varying degrees of wind penetration. The focus is to match the wind resource, system demand and abilities of extant generating facilities on a temporal basis, resulting in an operating schedule that minimizes system cost over a given period. This is performed by taking the perspective of a social planner who desires to find the lowest-cost mix of new and existing generation facilities. Unlike other studies, this analysis considers variable efficiency for thermal and hydro-generators, resulting in a fuel cost that varies with respect to generator part load. Since this study and others have shown that wind power may induce a large variance on existing dispatchable generators, forcing more frequent operation at reduced part load, inclusion of increased fuel cost at part load is important when investigating wind integration as it can significantly reduce the economic benefits of utilizing low-cost wind. Results indicate that the introduction of wind power may reduce system operating costs, but this depends heavily on whether the capital cost of the wind farm is considered. For the Vancouver Island mix with its large hydro-component, operating cost was reduced by a maximum of 15% at a wind penetration of 50%, with a negligible reduction in operating cost when the wind farm capital cost was included.     

Compressed Air Energy Storage in an Electricity System With Significant Wind Power Generation

In this paper, a stochastic electricity market model is applied to estimate the effects of significant wind power generation on system operation and on economic value of investments in compressed air energy storage (CAES). The model's principle is cost minimization by determining the system costs mainly as a function of available generation and transmission capacities, primary energy prices, plant characteristics, and electricity demand. To obtain appropriate estimates, notably reduced efficiencies at part load, start-up costs, and reserve power requirements are taken into account. The latter are endogenously modeled by applying a probabilistic method. The intermittency of wind is covered by a stochastic recombining tree and the system is considered to adapt on increasing wind integration over time by endogenous modeling of investments in selected thermal power plants and CAES. Results for a German case study indicate that CAES can be economic in the case of large-scale wind power deployment     

Effect of the generation mix on wind power introduction

The specific needs and ensuing costs for wind power integration into electricity generation systems depend to a large extent on the operation, composition and behaviour of the electricity generation system. The differences in the considered systems greatly influence the outcomes regarding wind power integration. The generation mix is studied here. Analyses are performed using a mixed integer linear programming model so as to get more insight in the consequences of the design and operation of electricity generation systems including wind power by looking at three distinct case systems. The model takes into account a multitude of technical specificities of the operation of an electricity generation system. The results show several aspects that are strongly related to the composition of electricity generation systems that influence the integration of wind power in the systems. These aspects range from the composition of the system to more specific technical parameters of the power plants and their operation, such as the marginal power plant and the greenhouse gas emission levels. The results shed some light on the reasons for the divergence in wind power integration studies. Moreover, it can help in gaining insights in the future development of electricity generation systems where wind power is being introduced.     

Optimizing biogas plants with excess power unit and storage capacity in electricity and control reserve markets

Increasing shares of intermittent power sources such as solar and wind will require biomass fueled generation more variable to respond to the increasing volatility of supply and demand. Furthermore, renewable energy sources will need to provide ancillary services. Biogas plants with excess generator capacity and gas storages can adapt the unit commitment to the demand and the market prices, respectively. This work presents a method of day-ahead unit commitment of biogas plants with excess generator capacity and gas storage participating in short-term electricity and control reserve markets. A biogas plant with 0.6 MW annual average electric output is examined in a case study under German market conditions. For this biogas plant different sizes of the power units and the gas storage are compared in consideration of costs and benefits of installing excess capacity. For optimal decisions depending on prices, a mixed-integer linear programming (MILP) approach is presented.The results show that earnings of biogas plants in electricity markets are increased by additional supplying control reserve. Furthermore, increasing the installed capacity from 0.6 MW to 1 MW (factor 1.7) leads to the best cost–benefit-ratio in consideration of additional costs of excess capacity and additional market revenues. However, the result of the cost–benefit-analysis of installing excess capacity is still negative. Considering the EEG flexibility premium, introduced in 2012 in the German renewable energy sources act, the result of the cost–benefit-analysis is positive. The highest profit is achieved with an increase of the installed capacity from 0.6 MW to 2 MW (factor 3.3).     

Current facts about offshore wind farms

This paper reviews offshore wind projects with a wide perspective. The current situation of the offshore wind market is presented, pointing out the countries leading the process in terms of installed capacity and in terms of technological leadership. Feasibility studies of alternative offshore wind farms (OWFs) are interesting not only in relation to the business but in relation to the techno-economical analyses that engineering researchers need to do. Details about the average energy yield assessment, the costs and the price for the purchased energy are commented on, as key elements of those feasibility studies. The higher cost of renewable energy sources of electricity (RESE) when compared with conventional sources, demands appropriate policy support. The European regulatory framework and the support schemes established by European Member States are presented, as well as the role that different transmission system operators (TSOs) are playing at the moment. Finally, most of the OWFs currently operating are presented, analysing the technical characteristics of their electric subsystems: the wind energy conversion systems (WECSs) transforming the kinetic energy of the wind into electricity, the collector system (CS) gathering the power output of all the turbines to a central collection point (CCP) and the transmission system (TS) taking that power to the onshore main grid.     

A linear diversity constraint - Application to scheduling in microgrids

Microgrids usually operate in disparate locations and may not be connected to the national grid. The potential sources of electricity in microgrids are wind farms, solar energy, biomass, tidal energy, among others. However, microgrids that are connected to the national grid are gaining importance, because they can supply electricity to the national grid when they have an excess and buy from it when they are in shortage. Such a symbiotic relationship with the national grid helps reduce investment in storage capacity and minimizes other operational costs. In this work, we develop a mathematical model MILP - (mixed integer linear programming) for scheduling operations in microgrids connected to the national grid. We allow several realistic features such as time constraints for the purchase/sale of power from/to the national grid; round trip efficiency of batteries; hydrogen generation, and limits on storage and retrieval rates from batteries/hydrogen tanks/natural gas tanks. Furthermore, to maintain diversity in the generation of electricity from multiple resources, we develop and impose a novel linear diversity constraint on the production schedule without sacrificing the ease of schedule implementation.     

Representation of variable renewable energy sources in TIMER,an aggregated energy system simulation model

The power system is expected to play an important role in climate change mitigation. Variable renewable energy (VRE) sources, such as wind and solar power, are currently showing rapid growth rates in power systems worldwide, and could also be important in future mitigation strategies. It is therefore important that the electricity sector and the integration of VRE are correctly represented in energy models. This paper presents an improved methodology for representing the electricity sector in the long-term energy simulation model TIMER using a heuristic approach to find cost optimal paths given system requirements and scenario assumptions. Regional residual load duration curves have been included to simulate curtailments, storage use, backup requirements and system load factor decline as the VRE share increases. The results show that for the USA and Western Europe at lower VRE penetration levels, backup costs form the major VRE cost markup. When solar power supplies more than 30% of the electricity demand, the costs of storage and energy curtailments become increasingly important. Storage and curtailments have less influence on wind power cost markups in these regions, as wind power supply is better correlated with electricity demand. Mitigation scenarios show an increasing VRE share in the electricity mix implying also increasing contribution of VRE for peak and mid load capacity. In the current scenarios, this can be achieved by at the same time installing less capital intensive gas fired power plants. Sensitivity analysis showed that greenhouse gas emissions from the electricity sector in the updated model are particularly sensitive to the availability of carbon capture and storage (CCS) and nuclear power and the costs of VRE.     

The impact of Production Tax Credits on the profitable production of electricity from wind in the U.S.

A spatial financial model using wind data derived from assimilated meteorological condition was developed to investigate the profitability and competitiveness of onshore wind power in the contiguous U.S. It considers not only the resulting estimated capacity factors for hypothetical wind farms but also the geographically differentiated costs of local grid connection. The levelized cost of wind-generated electricity for the contiguous U.S. is evaluated assuming subsidy levels from the Production Tax Credit (PTC) varying from 0 to 4 ¢/kWh under three cost scenarios: a reference case, a high cost case, and a low cost case. The analysis indicates that in the reference scenario, current PTC subsidies of 2.1 ¢/kWh are at a critical level in determining the competitiveness of wind-generated electricity compared to conventional power generation in local power market. Results from this study suggest that the potential for profitable wind power with the current PTC subsidy amounts to more than seven times existing demand for electricity in the entire U.S. Understanding the challenges involved in scaling up wind energy requires further study of the external costs associated with improvement of the backbone transmission network and integration into the power grid of the variable electricity generated from wind.