Datos Digestion Anaerobia y su Importancia

Andres Ortiz
30 Oct 2017

Base de datos inicial

X1	Summary data per period	X__1	X__2	X__3	X__4	X__5	X__6	X__7	X__8	X__9	X__10	X__11	X__12	X__13	X__14	X__15	X__16	X__17	X__18	X__19	X__20	X__21	X__22	X__23	X__24	X__25
1	Period	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24
2	Month	June	July	July	August	September	October	November	December	January	February	March	April	May	June	July	August	September	October	November	December	January	February	March	April	May
3	Date	41067	41102	41121	41137	41169	41197	41229	41256	41291	41320	41347	41379	41409	41446	41472	41502	41533	41564	41593	41627	41653	41690	41712	41744	41774
4	Biomass	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
5	Influent_biomass_gal	NA	2439588.7759543112	1462095.711046445	1071907.9828260974	1903617.2125744785	1367202.5354003906	2133814.4467773438	1866644.8390696908	1789314.8309316002	1515053.4396840904	1796384.14181722	2160602.2013089466	2346075.4632812501	3118507.1	2668167.5	3152645	3517967	3237216	3135991	3334404	2444506	3237703	1613576	2895836	2847064
6	Food_waste_tank_RT1_gal	NA	394805.63106770138	185416.30735841929	144838.64707528247	330932.87658541702	285808.57885742188	594263.27294921875	620144.50523481611	374006.6364301893	454542.36499538756	394183.21118028427	661510.13911692111	613636.73984375014	870612.2	607983.5	816993	858435	995524	894159	918288	591950	1015859	489276	898696	818932
7	Manure_tank_RT2_gal	NA	2044783.1448866099	1276679.4036880257	927069.33575081488	1572684.3359890613	1081393.9565429688	1539551.173828125	1246500.3338348747	1415308.1945014107	1060511.0746887028	1402200.9306369359	1499092.0621920258	1732438.7234375004	2247894.9	2060184	2335652	2659532	2241692	2241832	2416116	1852556	2221844	1124300	1997140	2028132
8	Co-digestionratio%	NA	0.16183286091454593	0.12681543756510572	0.13512227672137841	0.17384423422913831	0.20904626158678216	0.27849810176640355	0.33222415547667189	0.20902226369825824	0.30001738096457237	0.21943146902951893	0.30616933497344484	0.2615588242781885	0.2791759557000848	0.22786556691062312	0.25914525739498107	0.24401451179047445	0.30752473730514118	0.28512805043126715	0.27539794218097147	0.24215526572649035	0.31375916815100086	0.30322463893860591	0.31034077896676471	0.28764088197525589
9	Average_influent_biomass_per_day_gal/d	NA	69702.536455837471	76952.405844549736	66994.248926631088	59488.037892952452	48828.661978585376	66681.701461791992	69134.994039618177	51123.280883760002	52243.222058072082	66532.745993230375	67518.818790904581	78202.515442708333	84283.975675675683	102621.82692307692	105088.16666666667	113482.80645161291	104426.32258064517	108137.62068965517	98070.705882352937	94019.461538461532	87505.486486486479	73344.363636363632	90494.875	94902.133333333331
10	HRT_d	NA	31.562696450707911	28.589099663033057	32.838639663075192	36.982224963594469	45.055504510134782	32.992559454419137	31.82180067505724	43.033231865579651	42.110725819218089	33.066424166888396	32.583508411381757	28.13208740851481	26.102233341075284	21.43793446251032	20.93480236436389	19.386196630042292	21.067485147731876	20.344446141586502	22.432794586378858	23.399410760292675	25.141280716606808	29.995488281927845	24.3107689800113	23.181776033134486
11	Influent_biomass_lb	NA	20492545.718016215	12281603.972790139	9004027.0557392184	15990384.585625621	11484501.297363281	17924041.352929689	15679816.648185404	15030244.579825442	12726448.89334636	15089626.791264649	18149058.490995154	19707033.891562503	26195459.640000001	22412607	26482218	29550922.800000001	27192614.400000002	26342324.400000002	28008993.600000001	20533850.400000002	27196705.200000003	13554038.4	24325022.400000002	23915337.600000001
12	Food_waste_tank_RT1_lb	NA	3316367.3009686917	1557496.981810722	1216644.6354323728	2779836.1633175029	2400792.0624023438	4991811.4927734379	5209213.8439724557	3141655.7460135901	3818155.8659612555	3311138.9739143881	5556685.1685821377	5154548.6146875015	7313142.4799999995	5107061.4000000004	6862741.2000000002	7210854	8362401.6000000006	7510935.6000000006	7713619.2000000002	4972380	8533215.5999999996	4109918.4000000004	7549046.4000000004	6879028.8000000007
13	Manure_tank_RT2_lb	NA	17176178.417047523	10724106.990979416	7787382.4203068456	13210548.422308115	9083709.2349609379	12932229.860156251	10470602.804212948	11888588.833811851	8908293.0273851044	11778487.817350261	12592373.322413018	14552485.276875004	18882317.16	17305545.600000001	19619476.800000001	22340068.800000001	18830212.800000001	18831388.800000001	20295374.400000002	15561470.4	18663489.600000001	9444120	16775976	17036308.800000001
14	Effluent_digester_gal	NA	2180828.36328125	1335574.65625	932362.6796875	1702547.4931640625	1232853.9912109375	1844738.978515625	1615089.802734375	1569158.39453125	1300327.0999999999	1607578.3999999997	1813074.6000000006	1993242.7	2332325.7999999998	1836774	2217268	2408716	2166136	2109616	2600420	1967380	2309644	1189520	2176148	2027852
15	Average_effluent_biomass_per_day_gal/d	NA	62309.381808035716	70293.40296052632	58272.66748046875	53204.609161376953	44030.499686104908	57648.093078613281	59818.140842013891	44833.096986607146	44838.865517241371	59539.940740740727	56658.581250000017	66441.423333333325	63035.832432432428	70645.153846153844	73908.933333333334	77700.516129032258	69875.354838709682	72745.379310344826	76482.941176470587	75668.461538461532	62422.810810810814	54069.090909090912	68004.625	67595.066666666666
16	Influent-effluent_difference_gal/d	NA	7393.1546478017553	6659.0028840234154	8721.5814461623377	6283.4287315754991	4798.1622924804688	9033.6083831787109	9316.8531976042868	6290.1838971528559	7404.3565408307113	6992.8052524896484	10860.237540904564	11761.092109375008	21248.143243243256	31976.673076923078	31179.233333333337	35782.290322580651	34550.967741935485	35392.241379310348	21587.76470588235	18351	25082.675675675666	19275.272727272721	22490.25	27307.066666666666
17	Influent-effluentdifference%	NA	0.10606722543713955	8.6534044139895488E-2	0.13018403200122144	0.10562507949719917	9.8265283095096537E-2	0.13547357348634673	0.13476320244224244	0.12303951914696115	0.14172855825393457	0.10510321117966712	0.16084756421075808	0.15039275965478702	0.25210181499987616	0.31159719170554323	0.29669594895714552	0.3153102345758218	0.3308645453377223	0.32728888571427661	0.22012449601188097	0.1951829940282413	0.28664117740262157	0.26280509873721475	0.24852512366031779	0.28773922890388132
18	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19	Temperature	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20	Digester_temperature_F	NA	113	113.9	112.8	112.5	103.2	108.5	105	102.6	99.7	103.8	108	110	110.79805165823052	106.07931464727517	105.39634416620298	104.00688513654485	105.92159623138367	107.48065370655118	103.57721378385126	101.03532067336053	104.90026553864236	103.55107455131765	99.022802622129674	102.50227036106072
21	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
22	Biogas	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
23	Biogas_from_digester_Nm3	NA	301011.57282709487	161262.91230689513	119886.63789480277	258775.1550280368	190038.06547020806	270998.71940524451	226757.48566845278	251126.59853481717	225868.36114656416	243887.68336859808	305163.51466435043	307094.10214843752	405799.3	289559.5	336196	330965.5	368500	337398.5	325435.5	200852	363019.5	163886	234565.5	355959.5
24	Biogas_from_digester_Nm3/h	NA	358.34711050844629	353.64673751512095	312.20478618438221	336.94681644275624	282.7947402830477	352.86291589224544	349.93439146366171	298.96023635097282	324.52350739448872	376.36988174166368	397.34832638587295	426.51958631727433	456.98119369369368	464.03766025641022	466.93888888888887	444.84610215053766	495.2956989247312	484.76795977011494	398.81801470588238	321.87820512820514	408.80574324324328	310.3901515151515	305.423828125	494.38819444444448
25	Biogas_from_digester_Nm3/d	NA	8600.3306522027106	8487.5217003629023	7492.9148684251732	8086.7235946261499	6787.0737667931453	8468.709981413891	8398.4253951278806	7175.0456724233472	7788.5641774677297	9032.8771617999282	9536.3598332609508	10236.470071614584	10967.548648648648	11136.903846153846	11206.533333333333	10676.306451612903	11887.096774193549	11634.431034482759	9571.6323529411766	7725.0769230769229	9811.3378378378384	7449.363636363636	7330.171875	11865.316666666668
26	Biogas_from_digester_ft3	NA	10630133.390917009	5694951.369244311	4233760.6512635918	9138566.9672686122	6711137.2706607552	9570238.4761803877	8007872.5791357085	8868460.48927751	7976473.4133825675	8612820.3718570322	10776757.971317139	10844936.089141425	14330680.539709998	10225706.87465	11872660.881200003	11687947.342850003	13013466.949999999	11915126.807950003	11492657.051850006	7093028.124400001	12819924.736650003	5787584.9242000012	8283610.2628500015	12570602.954650002
27	Average_biogas_production_per_day_ft3/d	NA	303718.09688334313	299734.28259180585	264610.04070397449	285580.21772714413	239683.47395216982	299069.95238063711	296587.87330132251	253384.58540792885	275050.80735801958	318993.34710581601	336773.68660366058	361497.86963804747	387315.69026243238	393296.41825576924	395755.36270666675	377030.55944677431	419789.25645161286	410866.44165344839	338019.32505441195	272808.77401538467	346484.452341892	263072.04200909095	258862.82071406255	419020.0984883334
28	Specific_biogas_production_rate_ft3/lb_added	NA	0.51873171528764372	0.46369768817342266	0.47020745551458204	0.57150388837324317	0.58436471004636137	0.53393307277859692	0.51071213132217619	0.59004099648393782	0.62676348133160897	0.57077756070434915	0.593791571979568	0.55030788239445039	0.54706734436632309	0.45624798911835646	0.44832577396651602	0.39551886152435156	0.47856622973332047	0.45231873342012302	0.41032024270411505	0.34543098280291357	0.47137786148632449	0.42700077669840458	0.34053864891199448	0.52562933314602256
29	Biogas_to_CHP-boilerNm3	NA	298065.95762782416	187938.42552018401	147482.04235101541	244157.83677217137	64138.036759999995	316163.25755652279	289235.00705919293	137815	171899.77371406509	253886.13611111112	302362.70846127201	319087	414382	330647	350435	318180	432635	320544	374203	276274	456112	88119	154732	190894
30	Biogas_to_CHP-boiler_ft3	NA	10526109.873839326	6636989.1157176383	5208284.0810134038	8622360.7582582012	2265015.5267683719	11165210.59163134	10214247.503793284	4866895.3805000009	6070588.9387800954	8965912.7309230566	10677848.340497285	11268461.6789	14633776.015400004	11676699.610900002	12375506.894500002	11236431.246000001	15278375.2345	11319915.196799999	13214866.684099998	9756533.4278000016	16107458.446400002	3111896.0492999996	5464314.1604000004	6741364.3417999996
31	Biogastotal_energy_MMBTU-_wet_biogas	NA	5810.005706139601	3163.6593846425994	2162.2662398133416	4667.2489215234255	3487.6438168169807	5230.7095415411532	4089.780683616189	4688.2229530516624	4145.2137034666521	4553.0813613785012	5890.1448368030951	5927.4082688811368	7575.7709605122936	5497.3400158118402	6648.6900934720006	6492.8885079000338	6996.0398323199988	6832.61031675085	6229.9395346668507	3813.2119196774402	7006.8580640634254	3059.5488943290889	4490.3794512857285	6589.0072447093435
32	Biogastotal_energy_MMBTU-_dry_biogas	NA	5189.4514803862185	2815.2524388468751	1932.8849455334043	4177.1562874216916	3220.7679718712452	4751.3315513140742	3757.0540256060804	4336.731905624697	3863.6550935542245	4197.4883715687938	5359.4382390329692	5355.7358615831845	6825.0120610938966	5033.3654335294632	6100.435272943474	5982.2138781727972	6408.7362772290608	6227.7711075446796	5747.0609900402142	3542.155000138348	6438.7426372017462	2822.6161825561499	4192.3294632700508	6096.6492487693959
33	Biogasto_CHP-boiler_energy_MMBTU-_wet_biogas	NA	5281.5808902976205	3330.175658702482	2426.6437190257652	4017.3303244876615	1095.9051124716091	5702.2963533579568	4850.5418546013552	2398.4060435104007	2937.193752139362	4579.0709499370232	5692.5745072859127	5855.9941652907519	7473.7620865850895	6068.1472537925119	6431.3034229337609	5839.3485899212801	7939.8660418649588	6085.58640979968	6630.6915074140161	4982.8567522460162	8298.5625915852797	1672.9553161036797	2790.7345279994879	3322.14434763904
34	Biogasto_CHP-boiler_energy_MMBTU-_dry_biogas	NA	4717.4665837197344	2963.430636831908	2169.2162724063974	3595.4835291077657	1012.0460321776424	5179.6989229629717	4455.9229970951264	2218.5898827111587	2737.6884312908346	4221.4481884702918	5179.669148755821	5291.2093335844584	6733.1122665356015	5555.9966356374971	5900.9744326613709	5380.0757754600363	7273.3301636970464	5546.8755656241838	6116.7509391064787	4628.6572400713503	7625.7158768449544	1543.4009754444764	2605.4988699334372	3073.8999198399724
35	Water_vapor_density_g/L	NA	7.3645124195327524E-2	7.5815134654580577E-2	7.3171397861537535E-2	7.2466515863195802E-2	5.3680220751334787E-2	6.3691934547034548E-2	5.6890285944059489E-2	5.2650967001535029E-2	4.7947721007413804E-2	5.472959499163655E-2	6.2672615949001836E-2	6.6850443537688084E-2	6.859422895580769E-2	5.8906444030548455E-2	5.762251116035929E-2	5.5096164214366347E-2	5.8607427834868719E-2	6.1631125762519751E-2	5.4337578252732589E-2	5.0058765171976494E-2	5.670750166005379E-2	5.4291767853277807E-2	4.6911383737775113E-2	5.2485198437831157E-2
36	Water_vapor_density_L/L	NA	0.10680785134128618	0.11012783091852484	0.10608374216661622	0.10500674858836626	7.6520384237316191E-2	9.1646838047489271E-2	8.1355623626231083E-2	7.4973193669932575E-2	6.7923786336265252E-2	7.8099414788855792E-2	9.0100772132824108E-2	9.6445593312549288E-2	9.9099999634575692E-2	8.4399833546380684E-2	8.2460576868642055E-2	7.865137821262265E-2	8.3948000464168129E-2	8.8522421324591691E-2	7.7509346910934113E-2	7.1083623267919741E-2	8.1079910805588212E-2	7.7440407052195431E-2	6.637523426452005E-2	7.4724154588733688E-2
37	Watervapor_density%	NA	0.10680785134128618	0.11012783091852484	0.10608374216661622	0.10500674858836626	7.6520384237316191E-2	9.1646838047489271E-2	8.1355623626231083E-2	7.4973193669932575E-2	6.7923786336265252E-2	7.8099414788855792E-2	9.0100772132824108E-2	9.6445593312549288E-2	9.9099999634575692E-2	8.4399833546380684E-2	8.2460576868642055E-2	7.865137821262265E-2	8.3948000464168129E-2	8.8522421324591691E-2	7.7509346910934113E-2	7.1083623267919741E-2	8.1079910805588212E-2	7.7440407052195431E-2	6.637523426452005E-2	7.4724154588733688E-2
38	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
39	Biomass_loss	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
40	Masswater_loss_in_biomass_kg/d	NA	633.37241900235074	643.48260059668814	548.2670549801685	586.01668365125568	364.33161805704935	539.38852183403174	477.78882220867592	377.77309293326834	373.44390222956008	494.36570867451354	597.66861738145076	684.3125645477046	752.31054308936461	656.03540308706135	645.74859206893836	588.22353346096338	696.67216635964917	717.04308226156968	520.09932198432818	386.7078116277624	556.37645672653775	404.4391212001039	343.86850569197151	622.75349977770531
41	Volume_water_loss_in_biomass_L/d	NA	629.2538750920836	639.29831459600507	544.70191404137393	582.20607338254763	361.9625288421604	535.88111411431021	474.68197040227619	375.31659968429835	371.01555981487684	491.15106462336684	593.7822396822902	679.86277914360301	747.4185965616789	651.76949170026671	641.54957131647461	584.39857301284758	692.14201186897424	712.38046461159502	516.71734349737949	384.19321980966441	552.75858389387406	401.80923042854778	341.63247914967104	618.70400605622785
42	Volume_water_loss_in_biomass_gal/d	NA	166.231805117579	168.88527357637372	143.89547050281976	153.80305209028046	95.620681788492732	141.56525442867601	125.39810070330115	99.148465072198007	98.012247005567929	129.7487886678731	156.86116122002699	179.60130478776429	197.4477192797799	172.17982028326378	169.47999453597365	154.38225102045953	182.84514499629478	188.19159523738443	136.50270605415002	101.49342732859523	146.02382413849898	106.14709949504616	90.250034117839874	163.44481588636017
43	%_biomass_volume_due_to_water_loss	NA	2.3848745478997182E-3	2.1946717808607056E-3	2.1478779568139829E-3	2.5854450329500867E-3	1.9582900270834532E-3	2.1230000333718481E-3	1.8138151661869111E-3	1.9393994938946466E-3	1.8760758457167955E-3	1.9501493096508429E-3	2.3232213481962994E-3	2.2966180022603155E-3	2.3426483824108835E-3	1.6778089559088244E-3	1.6127409956018547E-3	1.3604021247596255E-3	1.7509488075201462E-3	1.7402971698210067E-3	1.3918805297261823E-3	1.0794938161507791E-3	1.6687390699901944E-3	1.4472427632110391E-3	9.9729442267133773E-4	1.7222459616611377E-3
44	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
45	COD_basis	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
46	kg_TS_destroyed_per_day_COD_based	NA	10821.067624553103	10854.197374795662	8809.4902950181659	9507.6367843915395	8119.6197346781619	10655.460482573037	9874.1075150321522	8731.7603768176286	9317.7386268567116	10992.67133493053	11998.793862810244	12879.68327744296	13347.09367623375	13782.907702185092	14446.958726188122	13653.306766173682	14711.338083630299	15358.551241255975	11944.459743459953	9560.4688424979304	12344.775395744569	9065.5950083363023	9147.336592663416	14317.273684380865
47	Volume_biomass_destroyed_L/d	NA	10750.702953104525	10783.617275066634	8752.2060314181599	9445.8127794229222	8066.8213976987627	10586.172681960061	9809.9005111348015	8674.9815568896956	9257.1494465770465	10921.190799583952	11920.770952573535	12795.932328495679	13260.30336182978	13693.283479722071	14353.016470260174	13564.525281931907	14615.676684335944	15258.681297779694	11866.79014424478	9498.3012937552976	12264.502718873286	9006.6454077626895	9087.8554623069376	14224.174713577378
48	Volume_of_biomass_destroyed_gal/d	NA	2840.044104481567	2848.7391755340609	2312.0954275421777	2495.3275160941835	2131.0353985572892	2796.5796697733558	2591.5096188341527	2291.6948161065397	2445.4877811002921	2885.0823689924318	3149.1443315299666	3380.3382280593014	3503.01245887615	3617.3940613203549	3791.6776219845124	3583.3796380651729	3861.0653258139018	4030.9297030114899	3134.8840662135522	2509.1935578156331	3239.948940369125	2379.3114090354229	2400.7649026012937	3757.6411247364554
49	%_biomass_destroyed_based_on_CH4-COD	NA	4.0745204534715584E-2	3.7019494637877223E-2	3.4511849368955155E-2	4.1946710708201135E-2	4.3643125004979459E-2	4.1939236829098767E-2	3.7484773880924534E-2	4.4826833812118022E-2	4.6809666110982917E-2	4.3363344258870444E-2	4.6640986734119018E-2	4.322544113732197E-2	4.1562022090126889E-2	3.5249753096209001E-2	3.6080918929830466E-2	3.1576410119827834E-2	3.6974062002730415E-2	3.7275923747017513E-2	3.1965550140673052E-2	2.668802306200372E-2	3.7025666280587698E-2	3.2440276131263296E-2	2.6529291328390627E-2	3.9594906802970946E-2
50	Total_volume_of_biomass_reduced_gal/d	NA	3006.275909599146	3017.6244491104344	2455.9908980449973	2649.1305681844638	2226.6560803457819	2938.1449242020317	2716.9077195374539	2390.8432811787379	2543.5000281058601	3014.8311576603051	3306.0054927499937	3559.9395328470655	3700.46017815593	3789.5738816036187	3961.157616520486	3737.7618890856324	4043.9104708101968	4219.1212982488742	3271.3867722677023	2610.6869851442284	3385.9727645076241	2485.4585085304689	2491.0149367191334	3921.0859406228155
51	Totalvolume_of_biomass_reduced%	NA	4.3130079082615298E-2	3.9214166418737928E-2	3.6659727325769137E-2	4.4532155741151221E-2	4.5601415032062914E-2	4.4062236862470613E-2	3.9298589047111442E-2	4.6766233306012671E-2	4.8685741956699717E-2	4.5313493568521289E-2	4.8964208082315323E-2	4.552205913958228E-2	4.3904670472537773E-2	3.6927562052117828E-2	3.7693659925432318E-2	3.2936812244587457E-2	3.8725010810250565E-2	3.9016220916838519E-2	3.335743067039923E-2	2.77675168781545E-2	3.8694405350577894E-2	3.3887518894474333E-2	2.7526585751061962E-2	4.1317152764632083E-2
52	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
53	Molar_basis	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
54	Mass_of_biomass_destroyed_kg/d	NA	9823.2483244719315	9588.3661024043504	8932.7928115076356	9164.448280172408	7873.2841626119571	9839.1651236343951	9847.4376203078882	8374.5680984515566	9035.0541477785646	10542.991413585245	10892.375484383187	11692.037381579144	12801.100818660982	12641.004499449151	12590.037448504587	12061.03954646137	13259.154033589377	13309.544091560163	10898.498980371161	8920.0459897930123	11013.842859055012	8694.7464742458706	8490.2182606076822	14039.539463704101
55	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
56	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
57	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
58	CHP_	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
59	Working_hours_h	1689	2264	2700	3011	3555	3709	4449	5047	5262	5609	6114	6803	7507	8324	8935	9629	10299	11033	11692	12402	12980	13850	14116	14595	15269
60	CHP_runtime_h	NA	575	436	311	544	154	740	598	215	347	505	689	704	817	611	694	670	734	659	710	578	870	266	479	674
61	Electrical_energy_generated_MWh	NA	673.43107241047755	457.57916574017668	346.79763152453017	580.40475264971781	203.24712083333347	871.13401249999993	681.16182499999979	251.31660772269495	365.19711309535757	653.8615795857072	813.17669500987881	840.99199108608934	1024.8999999999999	731.5	893	764.09999999999991	1000.4000000000001	850.80000000000007	873.4	569.60000000000014	996.5	194.89999999999998	535.20000000000005	923.70000000000016
62	Electrical_energy_generated_MMBTU	NA	2297.7468190645495	1561.2601135054829	1183.273518761697	1980.3410160408373	693.4791762833338	2972.3092506499997	2324.1241468999997	857.49226554983522	1246.0525498813602	2230.9757095464329	2774.558883373707	2869.4646735857368	3496.9587999999994	2495.8780000000002	3046.9160000000002	2607.1091999999994	3413.3648000000003	2902.9296000000004	2980.0408000000002	1943.4752000000005	3400.058	664.99879999999985	1826.1024	3151.6644000000006
63	Average_energy_generated_per_day_MWh/d	NA	18.706418678068822	24.083113986325088	21.674851970283136	18.137648520303681	7.2588257440476243	27.222937890624998	24.327208035714278	7.1804745063627129	12.593003899839916	24.217095540211378	27.105889833662626	28.999723830554807	27.699999999999996	28.134615384615383	29.766666666666666	24.64838709677419	32.270967741935486	29.337931034482761	25.688235294117646	21.907692307692312	28.471428571428572	12.181249999999999	19.822222222222223	30.790000000000006
64	Daily_average_instant_Power_MW	NA	0.77943411158620091	1.0034630827635453	0.90311883209513077	0.75573535501265332	0.30245107266865096	1.1342890787760416	1.0136336681547615	0.29918643776511306	0.52470849582666312	1.0090456475088079	1.1294120764026097	1.2083218262731168	1.1541666666666666	1.1722756410256407	1.2402777777777776	1.0270161290322577	1.3446236559139784	1.2224137931034482	1.0703431372549017	0.91282051282051269	1.1221846846846848	0.36912878787878789	0.69687499999999991	1.2829166666666671
65	Capacity_factor	NA	0.56220452849335267	0.70369080137696027	0.63332316416208323	0.52996869215473597	0.21209752641560381	0.79543413658908957	0.73714982879677227	0.20980816112560524	0.36795827196820702	0.70760564341431098	0.74251319889722756	0.81910549233100483	0.80937353903693299	0.82207267954112273	0.86976001246688484	0.72020766411799297	0.94293384005187841	0.85723267398558789	0.75059126034705603	0.64012658683065438	0.78694578168631468	0.25885609248161839	0.48869214586255266	0.89966105656849005
66	Onlineefficiency%	NA	0.68452380952380953	0.95614035087719296	0.80989583333333337	0.70833333333333337	0.22916666666666666	0.96354166666666663	0.9228395061728395	0.25595238095238093	0.49856321839080459	0.77932098765432101	0.89713541666666663	0.97777777777777775	0.92004504504504503	0.97916666666666663	0.96388888888888891	0.90053763440860213	0.98655913978494625	0.94683908045977017	0.87009803921568629	0.92628205128205132	0.97972972972972971	0.50378787878787878	0.62369791666666663	0.93611111111111112
67	Thermalconversion_efficiency%	NA	0.39938930401266104	0.4303941052805178	0.41567378516240033	0.4202192546546587	NA	0.48706758714524906	0.41630833020806945	0.32235941287436576	0.37554993170140427	0.4552631403155083	0.47541442314404508	0.46590610972632984	0.43721622234867819	0.39107981437928507	0.45046353462352973	0.42451493973705645	0.40875933962705502	0.46919727991471	0.41259273751414444	0.36445643404460981	0.38620817395145823	0.39098305497558894	0.403336592639716	0.45871824297301061
68	ft3/kWh	NA	15.630567559293327	14.504570165430705	15.018222754629754	14.855772146755513	11.144145695553188	12.81686908262159	14.995331694921815	19.365593959752065	16.622773623062535	13.71224890840649	13.131030938322164	13.399011879230237	14.278247648941365	15.962678893916612	13.858350385778278	14.705445944248138	15.272266327968811	13.305024913963326	15.130371747309363	17.128745484199438	16.164032560361267	15.966629293483837	10.209854559790733	7.2982184061924853

Tipo base datos Inicial

Classes 'tbl_df', 'tbl' and 'data.frame':   68 obs. of  27 variables:
 $ X1                     : int  1 2 3 4 5 6 7 8 9 10 ...
 $ Summary data per period: chr  "Period" "Month" "Date" "Biomass" ...
 $ X__1                   : chr  "0" "June" "41067" NA ...
 $ X__2                   : chr  "1" "July" "41102" NA ...
 $ X__3                   : chr  "2" "July" "41121" NA ...
 $ X__4                   : chr  "3" "August" "41137" NA ...
 $ X__5                   : chr  "4" "September" "41169" NA ...
 $ X__6                   : chr  "5" "October" "41197" NA ...
 $ X__7                   : chr  "6" "November" "41229" NA ...
 $ X__8                   : chr  "7" "December" "41256" NA ...
 $ X__9                   : chr  "8" "January" "41291" NA ...
 $ X__10                  : chr  "9" "February" "41320" NA ...
 $ X__11                  : chr  "10" "March" "41347" NA ...
 $ X__12                  : chr  "11" "April" "41379" NA ...
 $ X__13                  : chr  "12" "May" "41409" NA ...
 $ X__14                  : chr  "13" "June" "41446" NA ...
 $ X__15                  : chr  "14" "July" "41472" NA ...
 $ X__16                  : chr  "15" "August" "41502" NA ...
 $ X__17                  : chr  "16" "September" "41533" NA ...
 $ X__18                  : chr  "17" "October" "41564" NA ...
 $ X__19                  : chr  "18" "November" "41593" NA ...
 $ X__20                  : chr  "19" "December" "41627" NA ...
 $ X__21                  : chr  "20" "January" "41653" NA ...
 $ X__22                  : chr  "21" "February" "41690" NA ...
 $ X__23                  : chr  "22" "March" "41712" NA ...
 $ X__24                  : chr  "23" "April" "41744" NA ...
 $ X__25                  : chr  "24" "May" "41774" NA ...
 - attr(*, "spec")=List of 2
  ..$ cols   :List of 27
  .. ..$ X1                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Summary data per period: list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__1                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__2                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__3                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__4                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__5                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__6                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__7                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__8                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__9                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__10                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__11                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__12                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__13                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__14                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__15                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__16                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__17                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__18                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__19                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__20                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__21                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__22                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__23                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__24                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ X__25                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  ..$ default: list()
  .. ..- attr(*, "class")= chr  "collector_guess" "collector"
  ..- attr(*, "class")= chr "col_spec"

Base de datos Final

X1	Month	Food_waste_tank_RT1_gal	Manure_tank_RT2_gal	Digester_temperature_F	Biogas_from_digester_ft3	Electrical_energy_generated_MWh
0	6	NA	NA	NA	NA	NA
1	7	394805.6	2044783.1	113.0000	10630133	673.4311
2	7	185416.3	1276679.4	113.9000	5694951	457.5792
3	8	144838.6	927069.3	112.8000	4233761	346.7976
4	9	330932.9	1572684.3	112.5000	9138567	580.4048
5	10	285808.6	1081394.0	103.2000	6711137	203.2471
6	11	594263.3	1539551.2	108.5000	9570238	871.1340
7	12	620144.5	1246500.3	105.0000	8007873	681.1618
8	1	374006.6	1415308.2	102.6000	8868460	251.3166
9	2	454542.4	1060511.1	99.7000	7976473	365.1971
10	3	394183.2	1402200.9	103.8000	8612820	653.8616
11	4	661510.1	1499092.1	108.0000	10776758	813.1767
12	5	613636.7	1732438.7	110.0000	10844936	840.9920
13	6	870612.2	2247894.9	110.7981	14330681	1024.9000
14	7	607983.5	2060184.0	106.0793	10225707	731.5000
15	8	816993.0	2335652.0	105.3963	11872661	893.0000
16	9	858435.0	2659532.0	104.0069	11687947	764.1000
17	10	995524.0	2241692.0	105.9216	13013467	1000.4000
18	11	894159.0	2241832.0	107.4807	11915127	850.8000
19	12	918288.0	2416116.0	103.5772	11492657	873.4000
20	1	591950.0	1852556.0	101.0353	7093028	569.6000
21	2	1015859.0	2221844.0	104.9003	12819925	996.5000
22	3	489276.0	1124300.0	103.5511	5787585	194.9000
23	4	898696.0	1997140.0	99.0228	8283610	535.2000
24	5	818932.0	2028132.0	102.5023	12570603	923.7000

Tipo de base datos Final

Classes 'tbl_df', 'tbl' and 'data.frame':   25 obs. of  7 variables:
 $ X1                             : int  0 1 2 3 4 5 6 7 8 9 ...
 $ Month                          : int  6 7 7 8 9 10 11 12 1 2 ...
 $ Food_waste_tank_RT1_gal        : num  NA 394806 185416 144839 330933 ...
 $ Manure_tank_RT2_gal            : num  NA 2044783 1276679 927069 1572684 ...
 $ Digester_temperature_F         : num  NA 113 114 113 112 ...
 $ Biogas_from_digester_ft3       : num  NA 10630133 5694951 4233761 9138567 ...
 $ Electrical_energy_generated_MWh: num  NA 673 458 347 580 ...
 - attr(*, "spec")=List of 2
  ..$ cols   :List of 7
  .. ..$ X1                             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Month                          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Food_waste_tank_RT1_gal        : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Manure_tank_RT2_gal            : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Digester_temperature_F         : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Biogas_from_digester_ft3       : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Electrical_energy_generated_MWh: list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  ..$ default: list()
  .. ..- attr(*, "class")= chr  "collector_guess" "collector"
  ..- attr(*, "class")= chr "col_spec"

Graficas obtenidas

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Por que es importante?

La digestion anaerobia puede producir energia al rededor de: 671 (MWh), lo que demuestra la utilidad y productividad de 365 dias de uso de desechos como fuente de produccion sustentable de energia, evidenciando que a partir de 1.759379 × 10⁶(gal/Y) de estiercol se puede dar energia a una granja por este tiempo.

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Impacto

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