This thesis investigates the potential of a large pumping station in IJmuiden, the Nether-lands, for participating in Demand Response. Due to climate change, renewable energy is onthe rise. The intermittency of energy, together with its unpredictable supply, are a big hurdlefor the energy transition. Two methods are promising solutions to this problem; large scaleenergy storage and demand response. Since large scale energy storage is not yet economi-cally feasible, demand response has an important role to play in the early days of the energytransition.Using energy when it is generated requires a data-stream from the generation facilities onproduction, which is not (yet) widely available. The market price, however, is an indicationof the scarcity of energy, since it is based on the ratio between supply and demand. Besidesthat, there is a correlation between a low energy price and sustainable energy productionsince marginal costs of sustainable energy production are lower than fossil energy produc-tion. This makes using sustainable energy cheaper that fossil energy, and gives DemandResponse a business case.In this thesis, a Model Predictive Control is created that uses energy market data to minimizeenergy costs. Multiple energy markets are analyzed with respect for their suitability for thepumping station in IJmuiden to act on them. The day ahead market is called the APX inthe Netherlands, and this is where energy is bought and sold the day before consumption.The intraday market, also called the flexibility market, is where energy can be bought andsold up to 5 minutes before consumption. A strategy combining these two markets will beevaluated. This is done by using a predicted day ahead price, generated by a SARIMA model,to create a plan. This plan will then be followed, but deviations from the plan are allowedagainst intraday market price.Due to imperfections of the market (mismatch between supply and demand), imbalances areoccurring. These imbalances result in frequency deviations of the grid, and voltage devia-tions. Tenner, the Dutch TSO (Transmission system operator), is responsible for minimizingthese imbalances. In order to minimize the imbalance, TenneT gives a real-time indication ofthe imbalance on the grid, and positive contributions are rewarded while negative contribu-tions are punished. This is done through the use of the imbalance price; a price per volumeof imbalance caused or solved. The imbalance price is based on the aFRR market, wherebids can be done on possible activation. Since the imbalance market is a fast-acting market,it is not suitable for a large pumping station like IJmuiden. However, the aFRR market willbe analyzed in this thesis.The effects of expected future development, like sea level rise and energy market changes,will be analyzed and simulated as well. A higher sea level would result in more pumping, andless discharging under gravity. Which causes the the pump schedule to become less flexible.The results show that it is possible to apply demand response to a pumping station, and theintraday market makes it possible for the MPC to adjust its energy use during the day.The aFRR market analysis shows a lot of potential for the pumping station, possibly makingup for all energy costs made through the spot markets.The conclusion of this thesis is that Rijkswaterstaat can possibly save energy costs on pump-ing, based on the fixed energy price, provided by Rijkswaterstaat, they pay now. Based ona reference scenario where the MPC only minimizes energy use, and a fixed ENDEX energyprice, the proposed MPC makes about 10% less costs in the German market scenario. TheDutch market scenario does not show cost savings. In the Netherlands there is not muchcorrelation between low energy prices and renewable energy yet, since renewable energy isnot a big part of the energy mix in the Netherlands. This correlation is expected to becomemore present when the Dutch energy mix becomes more sustainable. This is expected toresult in lower CO2emission through the energy use of the pumping station. However, moreresearch is needed to confirm this.

The Phetchaburi River in Phetchaburi province, Thailand, has a watershed with many different water resource projects. The surrounding farms rely on the Phetchaburi River for irrigation water and the drinking water companies rely on it as a source of water. However, the Phetchaburi basin has problems with yearly floods, salt intrusion and pollution. Water monitoring stations in the region are scarce. A new telemetering system has been put in place, but due to the cost of these stations they are few in number. This project presents a showcase for a cheap and robust water monitoring system in terms of both quantity through water level data and quality through various water quality parameters using apps on an android or iPhone device to gather and analyse the data. The app from Mobile Water Management (MWM) is used to measure the water level through reading a photo of a staff gauge. The Akvo app uses various methods like electronic devices and reading strips via a photo to measure several water quality parameters. It was proven that construction of the staff gauges needed for the MWM app is cheap and does not require highly skilled workers. The resulting data is reliable, if the app is handled by someone trained in handling the app, and/or the data that is created is checked by a trained person. The fact that the pictures taken by the app are uploaded to the database makes for easy verification of the data. This makes verification of telemetric data possible, which as it turns out is not always reliable when compared to the MWM data. The Akvo app has a similar advantage in the sense that verification of the data at a later moment is not only possible, but also easy. This eliminates several human errors in the data collection process and effectively increases the data quality. Right now, several RID officers are needed to collect this data. Using the Akvo app, the required manpower can be lowered. Data analysis shows that the Phetchaburi River has significant levels fecal contamination (E. coli) and issues with low oxygen concentrations at certain moments. For this reason, it is not recommended to use as recreational, fishing or irrigation water. The boundary between salt and freshwater is constantly changing depending on weather conditions and can cause serious problems for local farmers. When constructing the staff gauge there are multiple possible human errors that need to be avoided in order for the MWM app to work correctly. This mainly has to do with the placement of the staff gauge sticker, keeping it straight and unobstructed and also directed towards the user. It turned out that several of the Akvo strips are not working correctly. Other than that, taking data from many parameters can also be time consuming. We recommend that the RID looks into this method of data collection further, both as a cheap and easy way to expand their water monitoring network, and in the case of the MWM app to verify the effectiveness of the telemetering systems.

The Netherlands is a low-lying country situated in the Rhine-Meuse delta. A significant portion of the Netherlands is located below sea level, making the proper management of local and national waterways essential. Polders are used to manage groundwater levels, drain excess rainwater, and store water during times of drought. These polders often have pumping stations that pump water into drainage canals, like the Noordzeekanaal-Amsterdam-Rijnkanaal (NZK-ARK), which receives water from the Rhine river and four local water authorities and connects to the North Sea at IJmuiden through a pumping station and a series of undershot gates. The operators of the NZK-ARK utilize Model Predictive Control (MPC) to schedule the discharge of water through the gates and pumps. The combination of the pump and gate discharge allows the NZK-ARK to discharge excess water to the North Sea when the sea water level is both higher and lower than the water level in the canal. However, traditional MPC can lead to suboptimal schedules when uncertainty is introduced, resulting from, for example, incoming discharge, fluctuating electricity prices, and the availability of renewable energy. Stochastic MPC allows for the consideration of uncertainty in decision-making, optimizing control actions based on a range of potential scenarios. In the future, the objectives for the control system of the gates and pumps may become more complex and may need to take into account factors like renewable energy availability and electricity prices. Ensuring the effective and efficient management of water in the Netherlands is critical, and the use of polders for water storage and control of groundwater tables, and techniques like MPC and stochastic MPC play important roles in achieving this goal. In this study, we present a framework that combines probabilistic forecasting, scenario generation and reduction, and stochastic MPC to minimize energy costs associated with pumping at the NZK-ARK. This framework is based on probabilistic forecasts of electricity prices and incoming discharge and is specifically designed for use at the NZK-ARK. By considering the uncertainty present in electricity prices and incoming discharge, our framework allows for the optimization of control actions through the use of stochastic MPC. The ultimate goal of this approach is to reduce energy costs at the NZK-ARK by effectively managing the discharge of water through the pumps and gates while complying with local constraints.@en