energia 2

Please download to get full document.

View again

of 9
All materials on our website are shared by users. If you have any questions about copyright issues, please report us to resolve them. We are always happy to assist you.
Information Report
Category:

Documents

Published:

Views: 5 | Pages: 9

Extension: PDF | Download: 0

Share
Related documents
Description
energia 2
Transcript
  An energy management approach for renewable energy integrationwith power generation and water desalination Malak Al-Nory  a ,  b ,  * , Mohamed El-Beltagy  a ,  c a College of Engineering, Effat University, Jeddah, Saudi Arabia b Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, MA, USA c Engineering Math.  &  Physics Dept., Faculty of Engineering, Cairo University, Giza, Egypt  a r t i c l e i n f o  Article history: Received 21 April 2014Accepted 17 July 2014Available online Keywords: Renewable energyStorageEnergy managementOptimizationRandom variationsDesalination a b s t r a c t The share of the renewable energy sources (RES) in the global electricity market is substantiallyincreasing as a result of the commitment of many countries to increase the contribution of the RES totheir energy mix. However, the integration of RES in the electricity grid increases the complexity of thegrid management due to the variability and the intermittent nature of these energy sources. Energystorage solutions such as batteries offer either short-term storage that is not suf  󿬁 cient or longer periodstorage that is signi 󿬁 cantlyexpensive. This paper introduces an energy management approach which canbe applied in the case of power and desalinated water generation. The approach is based on mathe-matical optimization model which accounts for random variations in demands and energy supply. Theapproach allows using desalination plants as a deferrable load to mitigate for the variability of therenewable energy supply and water and/or electricity demands. A mathematical linear programmingmodel is developed to show the applicability of this idea and its effectiveness in reducing the impact of the uncertainty in the environment. The model is solved for the real world case of Saudi Arabia. Theoptimal solution accounts for random variations in the renewable energy supply and water and/orelectricity demands while minimizing the total costs for generating water and power. ©  2014 Elsevier Ltd. All rights reserved. 1. Introduction The development and use of renewable energy has experiencedrapid growth over the past few years. In the next few decades allsustainable energy systems will have to be based on the rationaluse of traditional resources and greater use of renewable energy[1]. As a result, the share of the renewable energy sources (RES) inthe global electricity market will substantially increase. The inte-gration of the RES in the electricity grid will increase thecomplexity of the grid management due to the variability and theintermittent nature of these energy sources. The success in inte-grating the RES into the grid depends on many technological de-velopments of the electricity grid in network communications,decentralized generation, and demand response. In addition, thegrid will be characterized by the level of adoption and integrationof the renewable energy sources such as wind and solar. However,the dominant types of renewable energy sources are non-dispatchable, i.e., cannot be turned on and off at will or its outputadjustedasinregularfossilfuelpowerplants.Thegridmustbeableto manage this type of variations to supply power to its clientsef  󿬁 ciently.Distribution Management Systems operated by distributionutilities and Energy Management Systems operated by end con-sumers are typically used to manage the supply. Demand SideManagement including demand response, intelligent energy sys-tems, and smart loads improves the stability by focusing on theconsumption side [2]. With a large portfolio of 40% or morerenewable energy sources integrated into the grid, a critical situa-tion is created because of the sudden interruption or variation of alarge portion of the supply. Other types of storage technologies arebeing developed and implemented to meet the variable supplyanddemand. This has led to the emergence of storage as a crucialelement in the management of energy from renewable sources,allowing energy to be released into the grid during peak hourswhen it is more valuable [1]. Several studies have also examinedtheoperationalchallengesinthedevelopmentofrenewablepower,such as the mismatch between capacity and generation, the *  Corresponding author. College of Engineering, Effat University, P.O. Box 34689, Jeddah 21478, Saudi Arabia. Tel.:  þ 1 966 50 5527266. E-mail addresses:  malnory@effatuniversity.edu.sa (M. Al-Nory), melbeltagy@effatuniversity.edu.sa (M. El-Beltagy). Contents lists available at ScienceDirect Renewable Energy journal homepage: www.elsevier.com/locate/renene http://dx.doi.org/10.1016/j.renene.2014.07.0320960-1481/ ©  2014 Elsevier Ltd. All rights reserved. Renewable Energy 72 (2014) 377 e 385  contradictions of high generation cost and the  󿬁 xed feed-in tariff,the lag in grid construction, and regulatory uncertainty and policyinconsistency. Despite the promising recent growth rates in thecapacity of RES, it is established that the two most pressing issuesfor successful integration into the grid are the capability of theelectricitygridinfrastructureandtheavailabilityofbackupsystems[3].In addition, increased environmental concerns have led to theformation of energy and climate policies which suggest a signi 󿬁 -cant reduction of CO 2  emissions. As a result, the integration of RESin the energy mix is expected to rise rapidly as shown in Fig.1 [4]. Yet, electricity generated from renewable sources can rarely pro-videimmediateresponsetodemandasthesesourcesdonotdelivera regular and easily adjustable supply to consumption needs. Theconstantmismatchbetweensupplyanddemandcanhave aseriousimpact on grid reliability and security of supply. This constitutes achallenge, which requires the introduction of advanced energystorage solutions. But it is widely known that electricity is dif  󿬁 cultto store as this requires bulky and costly equipment [1].This study proposes an energy management approach tomanage renewable energy connected to the grid based on mathe-maticalmodelwhichconsiderstherandomvariationsof thesupplyand the demand (of both water and electricity) through anexpansion method discussed in Section 5. The approach can beimplemented in the case of powerand water generation. Thewaterstorage capacitycan be used allowing for the release of power backto the gird to absorb variability of supply from renewable energy.The case of Saudi Arabiais solved using the proposed approach andmodel to provide the decision makers with a strategy to comple-ment their announced ambitious plan of integrating renewableenergy to the national energy mix to produce 52 GW by 2032 [5].The remaining sections of this paper is organized as follows.Section 2 reviews the energy storage techniques. Section 3 dis- cusses the random variations of the renewable sources and thevarious demands. Section 4 describes the modes of integration of desalination capacity with the electricity grid. Section 5 describesthe proposed mathematical model and the expansion method.Section 6 uses a case study to illustrate the mathematical modeland discusses the analysis results. Finally, Section 7 concludes thepaper and provides interesting directions for future work. 2. Storage techniques There is a plethora of work on the integration of power storageinto the grid to compensate for sudden supply reduction. Yet, theoptimal active integration of storage devices and energy storagesystems into the grid is still not fully developed and faces manyoperational, technical and market challenges [6,7]. The integrationof energy storage techniques into the grid could obviously providean important and even crucial approach to deal with the inter-mittency of renewable energy and the associated unpredictabilityof its output, allowing the surplus to be stored during the periodswhen generation exceeds the demand and later the stored energycan be used to cover periods when the load is greater than thegeneration [8]. There are various types of storage techniques pro-posed, some of which are well developed, while others are still inthe development phase. These storage techniques differ in porta-bility (permanent or portable), durability (long or short term),maximum power requirement, and other factors which determinetheir characteristics and their proposed  󿬁 eld of application [1].Electrical energy storage refers to a process of converting elec-tricity from a power network into a form that can be stored forconverting back to electricity when desired. This technique whichcan provide many bene 󿬁 ts by reducing on-peak energy and loadleveling has numerous applications in commercial buildings,portable devices, transport vehicles and stationary energy re-sources [9]. It is expected that electricity storage will have a dualpurpose in the next few years [4]. On one hand, it will enablerenewable energy to be captured and stored for later use, withoutwasting additional resources for electricity generation; therefore,increasing its ef  󿬁 ciency. On the other hand, it can also serve as avaluable tool that will provide the needed  󿬂 exibility in energysupply, by smoothing out the mismatch between supply and de-mand. Given the current attempts being made toward the reduc-tion of CO 2  emissions, electrical energy storage technologies alongwith renewable energy technologies are expected tobe a necessaryelement of the built environment in the future [4].The Pumped HydroStorage (PHS) technology has the advantagethat it is readily available. It uses the power of water as a highlyconcentratedrenewableenergysource.Thistechnologyiscurrentlythe most used for high-power applications (a few tens of GWh or Fig. 1.  Expected scenario for a worldwide energy mix until 2050 [4]. M. Al-Nory, M. El-Beltagy / Renewable Energy 72 (2014) 377  e  385 378  100 of MW). Pumped storage subtransmission stations will beessential for the storage of electrical energy. The principle isgenerally well known: during periods when demand is low, thesestations use electricity to pump the water from the lower reservoirto the upper reservoir as shown in Fig. 2. When demand is veryhigh, the water  󿬂 ows out of the upper reservoir and activates theturbines to generate high-value electricity during the peak hours[1].It is becoming increasingly important for any market with asigni 󿬁 cant fraction of energy portfolio from renewable sources tocreate mechanisms through which it can respond to the unpre-dictable and the correlated changes in electricity supply. Theelectrical energy from RES can be stored in storage batteries andcan be used when needed. However, this solution (i.e., the batte-ries) has proven to be veryexpensive and dif  󿬁 cult to implement ona large scale [2]. Desalination facilities connected to the electricitygrid represent an opportunity to overcome such a challenge. Thework in Ref. [10] proposed an alternative approach to energystorage based on integration with large desalination plants. Theidea is to use desalination plants as a storage for excess renewableenergy supply and to work as deferrable load to mitigate for therenewable energy supply interruption. In essence, we are replacingpower storage with water storage. The implementation of this idearequires solving a decision optimization question (described inSection 5) which accounts for the random variations of the de-mands and the renewable energy supply which is exactly thecontribution of the present work. The optimal solutionprovided bythis work involves determining how to optimally scheduledesalinationproductionsoastointegrateitwiththeelectricitygridto provide the required buffer given the random variations in de-mands and energy supply. 3. Random behavior of renewable energy and demands The behavior of the renewable energy sources is a stochasticphenomenon. In particular, the wind speed is highly dependent ontheweatherconditions,thegeographicalregion,andtheseasons of the year. The analytical method proposed in Ref. [11] estimates themean and the variance of power output variation due to the sto-chastic wind speed. The proposed analytical method was validatedby comparing the data from simulations. The energy productionfrom wind farms can be treated as a random variable due to thestochastic nature of the wind behavior.Many probabilistic models have been proposed to evaluate andpredict the reliability performance of wind power generation withthe presence of stochastic wind speeds, uncertain power demands,and challenging maintenance activities (e.g. off-shore farms). Themain objective of these studies is to quantify (and hence mitigate)the uncertainties in the wind energy production by considering allpossible risk scenarios that could occur during the energy pro-duction process. Fig. 3 (left-side) shows the probabilistic behaviorof the renewable power generated as a function of the wind speed.The renewable power generated can be approximated as a randomvariable with Weibull or normal (Gaussian) distribution. Fig. 3(right-side) shows a typical simulation of the Probability Distribu-tion Function (PDF) of generated renewable energy after assuming Fig. 2.  Pumped Hydro Storage with the pumping energy supplied by wind turbines [1]. Fig. 3.  Probabilistic renewable power generated from the wind [11]. M. Al-Nory, M. El-Beltagy / Renewable Energy 72 (2014) 377  e  385  379  Gaussiandistributionofthewindspeed.Asshowninthe 󿬁 gure,thedeviation in the generated power is around 30% of the mean value.Renewable resources  󿬂 uctuate independently from demand asshown in Fig. 4 [1]. Power consumption (electricity demands) by users during the day is characterized by disparity and  󿬂 uctuation,meaning that minimum consumption is nearly half of themaximumpeak. Fig.5showsatypicaldailyconsumptionpatterninSaudi Arabia during a holiday in January 2012 and a work day inAugust 2012. The ratio between peak and average power levels of end-user demand often reaches a value of 10. 4. Integration of desalination with the electricity grid Desalination has been realized as a viable solution to waterscarcity issues around the world. Thermal desalination in whichfossil fuel (i.e., oil, gas, or coal) is the main drive to operate theprocess such as in Multi-Stage Flash (MSF), Multi-Effect Distillation(MED) and Vapor Compression (VC) is an energy intensive processespecially in areas with higher water salinity levels such as in theMiddle East and the Gulf countries (35,000 e 45,000 ppm salinitylevels). Therefore, these technologies are typically feasible only inthe case of power and water cogeneration. The power plant istypically connected to the grid to export produced electricity.Membrane-based desalination such as Reverse Osmosis (RO) andElectrodialysis (ED) can be built as stand-alone plants and areconnected to the grid to import electricity required for the opera-tion (i.e., pumping and mechanical processes). For detaileddescriptionofcommerciallyavailabledesalinationtechnologies thereader is referred to Ref. [12].Desalination can also be powered by renewable energy sourcessuch as Photovoltaic (PV)-RO, Wind-RO and Wind-Mechanical VC.In this case, the plant can be designed to be coupled tothe grid andtherenewableenergysourcesareusedasafuelsubstituteincaseof gridsupply interruption[13].The electricityconsumptionlevelsfornormaldesalination operation fordifferenttechnologies are shownin Table 1 [14,15]. Desalination plants have storage tanks with capacities from afew hours to a few days for large-scale plants to cover shortagesduring shutdowns for maintenance or emergency conditions.Aquifer storage and recovery (ASR) can store billions of cubic me-ters of desalinated water and are used for strategic long-termstorage. ASR systems need to be in strategic locations such asnearplantsandclosetomajorpipelinestodeliverwatertodemandconcentrations, or near pumping stations associated with munic-ipal high water use centers. In addition to strategic storage, distri-bution systems need to provide certain storage capacity to meetshorter demand  󿬂 uctuations and system emergencies of a shortduration. The normal operating storage is the storage required tocompensatefortheimpactofthevariationonwaterdemandonthewater production facilities. Two hours of an average day  󿬂 ow maybe used as normal operating storage (i.e., operatingstorage  ¼  average day demand/24 h)    2 h [16].Typically, the connectivity of the conventional stand-alonedesalination plants, such as the dominant technology in the mar-ket today i.e., Reverse Osmosis (RO), to the grid is a one-waylink inwhich the desalination plant imports the electricity required fromthe grid. However, desalination plants with appropriate technolo-gies can implement a two-way link in which the plant wouldimport the electricity needed for the operation (pumping andmechanical processes) but also would act as a storage device andexport electricity to the grid during interruption of the powersupply, which is the focus of this paper.Desalination units (of appropriate technologies) can use smartcontrols to be able to dynamicallyadapt the power consumption toconsume electricity when there is enough power in the grid andnot toconsumewhenthe poweris scarce. Based on the desalinatedwater demand, the capacity of the plant, and the typical energyconsumption, each desalination plant realizes speci 󿬁 c electricityneedsforeachtime period. The desalinationplanttypically realizesminimum energy consumption and the energy consumptionrequiredforoperatingoptimally. The difference between these twolevels of consumption is the range of the amountof energy that theplantiswillingtodelivertothegridshouldtheneedarise.Fromthegrid point of view the desalination plant acts like a virtual batterywhich is capable of delivering this amount of power for each timeperiod.Fig.6showsaschematicrepresentationoftheintegrationof desalination plants into the grid.In this case of integration, between power generation anddesalinationplants there will be a market interface. In the case of acentralized authority tocontrol desalination and power productionmodeling this interface is straightforward. The model can expressthe overall costs or bene 󿬁 ts of generation of power and productionof desalinated water. However, the incentive of desalination plantsto collaborate with the grid and act as storage devices must be Fig. 4.  Fluctuation of instantaneous power on March 2004 at the Cap-Chat (Canada)wind farm [1]. Fig. 5.  Typical average daily power consumption in Saudi Arabia [5].  Table 1 Electricity consumption of desalination technologies [14,15].Technology Electricity (kWh/m 3 ) Feed watersalinity (ppm)RO without energy recovery 5.9 25,000RO with energy recovery 3 e 4 25,000ED 1.22 ( þ 50% after 3 years) 3000VC 8.5 e 16 45,000MSF 4 e 5 AnyMED 1 e 1.5 Any M. Al-Nory, M. El-Beltagy / Renewable Energy 72 (2014) 377  e  385 380
We Need Your Support
Thank you for visiting our website and your interest in our free products and services. We are nonprofit website to share and download documents. To the running of this website, we need your help to support us.

Thanks to everyone for your continued support.

No, Thanks