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In a wastewater treatment plant reliable fault detection is an integral component of process supervision and ensuring safe operation of the process. Detecting and isolating process faults requires that sensors in the process can be used to uniquely identify such faults. However, sensors in the wastewater treatment process operate in hostile environments and often require expensive equipment and maintenance. This work addresses this problem by identifying a minimal set of sensors which can detect and isolate these faults in the Benchmark Simulation Model No. 1.Residual-based fault signatures are used to determine this sensor set using a graph-based approach; these fault signatures can be used in future work developing fault detection methods. It is recommended that further work investigate what sizes of faults are critical to detect based on their potential effects on the process, as well as ways to select an optimal sensor set from multiple valid configurations.

This study aims to develop a gridded optimization model for studying photovoltaic applications in Nordic countries. The model uses the spatial and temporal data generated by the mesoscale models STRÅNG and MESAN developed by the Swedish Meteorological and Hydrological Institute. The model is developed based on the comparison between five irradiance databases, three decomposition models, two transposition models, and two photovoltaic models. Several techno-economic and environmental aspects of photovoltaic systems and photovoltaic systems integrated with batteries are investigated from a spatial perspective. CM SAF SARAH-2, Engerer2, and Perez1990 have shown the best performances among the irradiance databases, and decomposition and transposition models, respectively. STRÅNG resulted in the second-best irradiance database to be used in Sweden for photovoltaic applications when comparing hourly global horizontal irradiance with weather station data. The developed model can be employed for carrying out further detailed gridded techno-economic assessments of photovoltaic applications and energy systems in general in Nordic countries. The model structure is generic and can be applied to every gridded climatological database worldwide.

Nordligt läge med lägre solstrålning än exempelvis södra Europa och förhållande­vis lågt elpris gör att noggranna förutsägelser av energiutbyte från solcellsanlägg­ningar är av stor vikt när man gör investeringskalkyler i Sverige. Noggrannare beräkningar av förväntad solelproduktion ger mindre ekonomisk osäkerhet, vilket resulterar i en mer resurseffektiv utveckling. Val av meteorologiska data och be­räkningsmetod för kalkyler av solelproduktion är därför av stor vikt.

En fråga är därför vilket simuleringsprogram för solelproduktion som är bäst att använda i Sverige. OptiCE, Polysun, PVsyst och PV*SOL med programmens meteo­rologiska databaser visade sig här vara relativt likvärdiga för Stockholm, Norrköping och Visby. Överensstämmelsen är relativt god med de uppmätta vär­dena för solelproduktion under 2019, med skillnader på mindre än ±5%. Men de ger alla 13%-15% för höga värden för Kiruna. PVGIS med databas ERA5 ger lite större avvikelser för Stockholm, Norrköping och Visby än ovan nämnda program men ger ett värde nära det uppmätta under 2019 i Kiruna. SAM och PVGIS med databaserna SARAH eller COSMO ger större avvikelser än ovan nämnda pro­gram. Då SARAH i en jämförande studie hade bäst nog­grannhet är det tänkbart att beräkningarna i PVGIS skulle kunna förbättras genom att välja SARAH i kombi­nation med ett lägre värde än grundinställningen 14% för system­förluster.

Den största osäkerheten vid uppskattning av solcellssystems elproduktion kommer från solstrålningsdata. Genom att förbättra solstrålningsdata och göra dem allmänt tillgängliga hjälps investerare att fatta beslut med minskad osäkerhet. Det finns behov av en branschstandard för solstrålningsdata i Sverige. En vidareutveckling av STRÅNG-modellen för solstrålningsdata är önskvärd. Ett standardförfarande hur man beräknar inverkan av skuggning skulle vara värdefullt, då skuggning vid sidan om val av solstrålningsdatabaser kan ha en stor inverkan på utbytet av solel.

Solstrålningsklimatet kan förändras över tid, vilket man kan se i upp­mätt solstrål­ning för Sverige. I framtiden kan även pågående klimatföränd­ring ha betydelse för solinstrålning och därmed solenergiproduktion. Data för solstrålning, vind, tempe­ratur och albedo­ från klimatscenarion för två tids­perioder (2030-2065 och 2066-2095) användes för att uppskatta hur solel­produktionen kan komma att påverkas. Resultatet pekar på att solelproduktionen minskar något men att förändringen endast är statistiskt signifikant i det scenario som representerar fortsatt höga kol­dioxidutsläpp och då endast för norra Sverige under den senare tidsperioden. Sett över hela landet beräknas förändringen för denna period hamna mellan -9% (10:e percentilen) och -2% (90:e percentilen) med medelvärde på ca -6%.

De kartor för Sverige för optimerade lutningar, solstrålning och solelproduktion som tagits fram med den utvecklade modellen OptiCE är ett verktyg för att bättre förstå, utforma och förbättra installationer av solcellssystem i Sverige.

Bland de undersökta modellerna för uppdelning av global horisontell solstrålning i diffus och direkt strålning för att ta fram egna solstrålningsdata för användning i simuleringsprogram är slutsatsen att för timvärden är Engerer2 eller Paulescu och Blaga lämpliga val. För 1-minutvärden visar Yang2 bäst pre­standa.

Northern location with lower solar radiation than southern Europe and relatively low electricity prices means that accurate predictions of energy yield from photovoltaic (PV) systems are of great importance when making investment calculations in Sweden. More accurate calculations of expected PV yield result in less economic uncertainty, which results in a more resource-efficient development. The choice of meteorological data and calculation method for PV yield is therefore of great importance

One question is which simulation program for PV yield is best to use in Sweden. OptiCE, Polysun, PVsyst and PV*SOL using the programs meteorological databases are relatively equivalent in this work for Stockholm, Norrköping and Visby. The agreement is relatively good with the measured values ​​for PV yield in 2019, with differences of less than ±5%. But they all give 13%-15% too high values ​​for Kiruna. PVGIS with database ERA5 gives slightly larger deviations for Stockholm, Norrköping and Visby than the above-mentioned programs but gives a value close to the measured in 2019 in Kiruna. SAM and PVGIS with the databases SARAH or COSMO give larger deviations than the above-mentioned programs. As SARAH in a comparative study had best accuracy, it is conceivable that PVGIS calculations could be improved by choosing SARAH in combination with a lower value than the default setting of 14% for system losses.

The greatest uncertainty in estimating solar cell systems electricity production comes from solar radiation data. By improving solar radiation data and making it publicly available, investors are helped to make decisions with reduced uncertainty. There is a need for an industry standard for solar radiation data in Sweden. A further development of the STRÅNG model for solar radiation data is desirable. A standard procedure for calculating the effect of shading would also be valuable, as shading can have a major impact on PV yield.

Data for solar radiation, wind, temperature and albedo from the climate scenario for two periods (2030-2065 and 2066-2095) were used to estimate how solar production may be affected in a future climate. The results indicate that PV yield is declining somewhat, but that the change is only statistically significant in the scenario that represents continued high carbon dioxide emissions and then only for northern Sweden during the recent period. Across the country, the change for this period is estimated to be between -9% (10th percentile) and -2% (90th percentile) with an average value of about -6%.

The maps for Sweden for optimized slopes, solar radiation and solar production produced with the developed model OptiCE are a tool for better understanding, designing and improving installations of PV systems in Sweden.

Among the models examined for the decomposition of global horizontal solar radiation into diffuse and direct radiation to produce own solar radiation data for use in simulation programs, the conclusion is that for hourly values ​​Engerer2 or Paulescu and Blaga are suitable choices. Of the models studied for 1-minute values, Yang2 shows the best performance.

Process control is an important part of any industrial system. In a wastewater reuse system this remains true. Process monitoring and fault detection (FD) are important to ensure that the control system has access to reliable data which can be used in making decisions about the operation of the process. The reuse scenario being considered in this work is that of utilizing the nutrients from the wastewater as fertilizer to agricultural soil along with using the water for irrigation purposes. This paper identifies variables that are important to the control of the process and should be a focus of monitoring and FD. In wastewater treatment these variables include temperatures, pressures, liquid levels, flow rates, pH, conductivity, biomass content, suspended solids concentration, dissolved oxygen content, total organic carbon, and the concentrations of nitrate and ammonium. The variables of interest in the reuse of nutrients and water for agriculture include soil moisture, ambient conditions, plant height, biomass content, photosynthetic activity of the crop, leaf area and leaf water content, as well as the concentrations of several ions both in the soil and in the plant. Challenges associated with process monitoring and FD specific to the two processes are also discussed, examples of these are the high dimensionality of the problem, the harsh conditions that sensors must operate in and the non-linear relationships between variables. This information will be used in future work when comparing specific FD methods to ensure that methods chosen are capable of overcoming the commonly encountered problems.

This study investigated the possibility of using a model based on the anaerobic digestion model no. 1 (ADM1) on a full-scale 4000 m³ digester in order to understand how such theoretical models can be applied to a real industrial process. The industrial scale digester co-digests the organic fraction of municipal solid waste, grease trap sludge, and ley crop silage with varying feed rates and amounts of volatile solids. A year of process data was collected. Biogas flow, methane content/flow, and ammonia nitrogen were the variables that the model was best at predicting (index of agreement at 0.78, 0.61/0.77, and 0.68, respectively). The model was also used to investigate the effect of increasing the volatile solids (VS) concentration entering the digester. According to simulation results, increasing the influent VS concentration will increase biogas and methane outflow (from 1.5 million Nm³ methane to more than 2 million Nm³ methane), but decrease the amounts of biogas/methane per unit of volatile solids (from about 264 Nm³methane per tonne VS to below 215 Nm³ methane per tonne VS).

Microalgae are considered as potential sources for biodiesel production due to the higher growth rate than terrestrial plants. However, the large-scale application of algal biodiesel would be limited by the downstream cost of lipid extraction and the availability of water, CO2 and nutrients. A possible solution is to integrate algae cultivation with existing biogas plant, where algae can be cultivated using the discharges of CO2 and digestate as nutrient input, and then the attained biomass can be converted directly to biomethane by existing infrastructures. This integrated system is investigated and evaluated in this study. Algae are cultivated in a photobioreactor in a greenhouse, and two cultivation options (greenhouse with and without heating) are included. Life cycle assessment of the system was conducted, showing that algal biomethane production without greenhouse heating would have a net energy ratio of 1.54, which is slightly lower than that (1.78) of biomethane from ley crop. However, land requirement of the latter is approximately 68 times that of the former, because the area productivity of algae could reach at about 400 t/ha (dry basis) in half a year, while the annual productivity of ley crop is only about 5.8 t/ha. For the case of Växtkraft biogas plant in Västerås, Sweden, the integrated system has the potential to increase the annual biomethane output by 9.4%. This new process is very simple, which might have potential for scale-up and commercial application of algal bioenergy. © 2013 Elsevier Ltd. All rights reserved.