Demand-side resources are taking an increasingly prominent role in providing essential grid services once provided by thermal power plants. This thesis considers the economic feasibility and environmental effects of integrating demand-side resources into the electric grid with consideration given to the diversity of market and environmental conditions that can affect their behavior. Chapter 2 explores the private economics and system-level carbon dioxide reduction when using demand response for spinning reserve. Steady end uses like lighting are more than twice as profitable as seasonal end uses because spinning reserve is needed year-round. Avoided carbon emission damages from using demand response instead of fossil fuel generation for spinning reserve are sufficient to justify incentives for demand response resources. Chapter 3 quantifies the system-level net emissions rate and private economics of behind-the-meter energy storage. Net emission rates are lower than marginal emission rates for power plants and in-line with estimates of net emission rates from grid-level storage. The economics are favorable for many buildings in regions with high demand charges like California and New York, even without subsidies. Future penetration into regions with average charges like Pennsylvania will depend greatly on installation cost reductions and wholesale prices for ancillary services. Chapter 4 outlines a novel econometric model to quantify potential revenues from energy storage that reduces demand charges. The model is based on a novel predictive metric that is derived from the building’s load profile. Normalized revenue estimates are independent of the power capacity of the battery holding other performance characteristics equal, which can be used to calculate the profit-maximizing storage size. Chapter 5 analyzes the economic feasibility of flow batteries in the commercial and industrial market. Flow batteries at a 4-hour duration must be less expensive on a dollar per installed kWh basis, often by 20-30%, to break even with shorter duration li-ion or lead-acid despite allowing for deeper depth of discharge and superior cycle life. These results are robust to assumptions of tariff rates, battery round-trip efficiencies, amount of solar generation and whether the battery can participate in the wholesale energy and ancillary services markets.

Demand Response (DR) was proposed more than a decade ago to incentivise customers to shift their electricity usage from peak demand periods to off-peak demand periods and to curtail their electricity usage during peak demand periods. However, the lack of two-way communication infrastructure weakens the influence of DR and limits its applications. With the development of smart grid facilities (e.g. smart meters and the two-way communication infrastructure) that enable the interactions between the energy retailer and its customers, demand response shows great potential to reduce customers' bills, increase the retailer's profit and further stabilize the power systems. Given such a context, in this thesis we propose smart pricing based demand response programs to study the interactions between the energy retailer and its customers based on game-theory and machine learning techniques. We conduct the research in two different application scenarios: 1) For customers with home energy management system (HEMS) installed in their smart meters, the retailer will know the customers' energy consumption patterns by interacting with the HEMS. As a result, the smart pricing based demand response problem can be modelled as a Stackelberg game or bilevel optimization problem. Further, efficient solutions are proposed for the demand response problems and the existence of optimal solution to the Stackelberg game and the bilevel model is proved; 2) For customers without HEMS installed in their smart meters, the retailer will not know the energy consumption patterns of these customers and must learn customers' behaviour patterns via historical energy usage data. To realize this, two appliance-level machine learning algorithms are proposed to learn customers' consumption patterns. Further, distributed pricing algorithms are proposed for the retailer to solve the demand response problem effectively. Simulation results indicate the effectiveness of the proposed demand response models in both application scenarios.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第22070号 / 工博第4651号 / 新制||工||1725(附属図書館) / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 引原 隆士, 教授 土居 伸二, 特定教授 中村 武恒 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

<p>As the number of water stressed regions around the world continues to growth due to a steadily increasing demand and climate change; the use of unconventional water sources, such as, brackish or seawater, through the implementation of desalination technologies has increased significantly. Reverse osmosis has established itself as the most widespread and energy efficient desalination technology, thanks to the development of high permeability membranes, high efficient pumps, and the integration of energy recovery devices; but, it still faces important challenges, such as, high specific energy consumption compared with traditional water treatment technologies, and poses environmental threats due to its significant CO₂emissions and the need of disposal of high salinity brine.</p> <p> </p> <p>The aim of this research is to address and provide solutions for two of the major challenge areas in reverse osmosis: reduction of the energy consumption and strategies to facilitate its integration with renewable energy sources to decrease its environmental impact. </p> <p> </p> <p>In chapter 2, the modeling and design of a double-acting batch reverse osmosis system is presented. A reduced specific energy consumption compared with previously proposed configurations was found. Moreover, the new design presents solutions to practical concerns that have limited the implementation of Batch reverse osmosis processes such as high start time and downtime, and permeate contamination. On the other hand, a novel hydraulic modeling is introduced to calculate the evolution of the pressure and other important parameters during the cycle.</p> <p> </p> <p>Chapter 3 presents a novel method which allows reverse osmosis plants to vary their power usage according to the energy availability, therefore, providing demand response capabilities. The effects on the energy consumption and performance of the reverse osmosis desalination facility due to the implementation of this technique are also studied. The split-salinity demand response reverse osmosis process proposed here poses as the first approach to grant demand response capabilities to reverse osmosis plants that provides energy gains and can be applied to existing plants. </p>

The Swedish electrical power system faces many challenges. Stricter environmental and economic demands require a more efficient use of both the transmission and distribution grids as well as the production capabilities. Since the Swedish national demand of electricity is fluctuating, the system has always been dimensioned to meet the periods of high demand, resulting in a low utilization of the system. To meet these challenges, the concept of a “Smart Grid” has been phrased. One of the most important goals of a Smart Grid is to enable end-consumers to participate more actively in the energy market. One way to do this is through “load-shifting” where consumption (or loads) are moved from hours of high demand (peak hours) to hours of low demand (off-peak hours). Load-shifting is a part of a set of intentional consumption modifications denoted “Demand Response” (DR) and is deemed to be one of the most important tools of the Smart Grid. In Sweden, a Smart Grid project called the Stockholm Royal Seaport (SRS) project is currently taking place. The project have phrased a hypotheses regarding load-shifting called the “Active customer” scenario, in which a customer load-shifts 5-15 % of his electricity consumption. To facilitate this scenario, the SRS project uses an end-consumer price model for electricity, called the SRS price model, as well as technological and market solutions not yet available on a national scale.   This study investigates what impact the results from the SRS pilot project might have if implemented for private apartment end-consumers on a Swedish national scale. The study is divided into three parts. The first part investigates the challenges of a national scale implementation of private apartment end-consumer DR and the SRS price model. The second part investigates what the impact would be if the entire Swedish private apartment end-consumer sector where to act in accordance with the Active customer scenario. The third part consists of a sensitivity analysis. Four challenges for a national private apartment end-consumer load-shift implementation have been elicited. They are; the lack of easily moveable loads in a foreseeable future, the heterogeneous cost of distribution, the suggested price models low peak to off-peak price ratio and the comparatively small cost of electricity of the private apartment end-consumers. The SRS price model is deemed to give a clear economic incentive for load-shift of private apartment end-consumer without electric heating. However, the incentive might be considered too weak with yearly savings of 48-165 SEK for a 15 % load-shift, depending on apartment consumption. This corresponds to yearly savings of 124 to 429 million SEK for the entire customer segment. These challenges are deemed to be of a non-technical character, but rather of a marketing and communication nature. The impact of a fully implemented national private apartment end-consumer load-shift in accordance with the Active customer scenario and the SRS price model is deemed to be beneficial from an overall power system point of view. However, the impact on the private apartment end-consumer national demand is small in comparison with other plausible system developments, such as energy demand reductions due to more efficient lighting solutions. The sensitivity analysis of private apartment end-consumer cost savings when acting in accordance with the Active customer scenario indicates that the percentage savings may increase in the future when considering more volatile prices for electric energy or the implementation of a time differentiated energy tax.

Demand for cooling has been increasing around the world for the last couple of decades due to various reasons, and it will continue to increase in the future particularly in developing countries. Traditionally, cooling demand is met by decentralised electrically driven appliances which affect energy, economy and environment as well. District Cooling Plant (DCP) is an innovative alternative means of providing comfort cooling. DCP is becoming an essential infrastructure in modern city development owning to many benefits compared to decentralized cooling technology. Demand Response Management (DRM) is largely applied for Demand Side management of electrical grid. Demand of electrical energy is closely connected with the demand of alternative form of energy such as heating, cooling and mechanical energy. Therefore, application of DR concept should be applied beyond the electrical grid; in particular, it could be applied to any interconnected district energy systems. District Cooling Plant is one of a potential candidate and Demand Response management solutions can be applied to DCP for sustainable operation. The study of demand response and its applicability has not been attempted previously for district cooling systems. To our knowledge, this is the first attempt to evaluate its applicability and economical feasibility. This thesis focused on some of the DR objectives which have the potential to implement for DCP of a mixed-use city. General published data on mixed use city developments and a specific city in Dubai was taken as a case study to show the usefulness on DRM objectives. This study primarily addressed the issues related to load management. The findings are: DRM creates greater flexibility in demand management without compromising service levels. Also it reduces the operation cost and impact to environment. However implementation is a big challenge. Therefore implementation strategies are also proposed as a part of recommendation which includes a generic model for demand response management. Moreover, a review is provided on key enabling technologies that are needed for effective demand response management. Finally this thesis concludes with recommendations for prospective applications and potential future works.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第21385号 / エネ博第373号 / 新制||エネ||73(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 手塚 哲央, 教授 下田 宏, 准教授 MCLELLAN,Benjamin / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

No description available.

This thesis stems from the interest of Holmen group to investigate the opportunitiesavailable for large electricity consumers in the Swedish primary reserve markets.The study performed focuses on one of Holmen's paper mill and it aims at identifyinga load inside the production process that is suitable for providing frequency containmentservices for the grid. The evaluation of the mill's consumption prole and the technicalrequirements of the reserve market led to the identication of the electric boiler coupledwith a steam accumulator as the most appropriate load.Five case study simulating the participation of the mill to dierent energy and reservemarkets have been evaluated. For each case a linear optimization problem has beenformulated. The rst simulation represents the current practice of the mill in relation tothe energy purchased on the spot market (following it will be also referred as referencecase). The second case study (II c.s.) integrates the use of the steam accumulator asa tool to perform thermal load shifting. In the third case study (III c.s.) the mill ismodelled to bid on the spot and primary reserve market by oering some capacity ofthe electric boiler. The last two case studies (IV and V c.s.) recalls the rst and lastpreviously mentioned, but also include the possibility of having energy imbalance. Thismeans that the imbalance settlement operated by eSett will produce an additional costor prot for the mill.The last three problem formulations fall under the denition of stochastic problems,since two random variable are present, namely: average hourly frequency value andimbalance settlement price. The uncertainty of the variables is represented throughscenarios.The outcome derived from the combination of the results for the winter and summercases shows that each strategy brings an economic saving when compared to the referencecase (I c.s.). The less interesting strategies are the ones that do not involve the reservemarket, leading to about 0.03% (II c.s.) and 0.06% (IV c.s.) of saving on the overallyearly energy cost. Contrariwise, by oering FCR-N capacity, the cost of electricitycan be cut by 5.15% (III c.s.) and 6.69% (V c.s.), respectively considering and notconsidering the imbalance settlement. / Avhandlingen har sitt ursprung i skogsindustrikoncernen Holmens intresse att undersökamöjligheten för stora elförbrukare att delta på den svenska primär-reservmarknaden. Studien som utförts fokuserar på ett av Holmens pappersbruk och syftar till att identifiera en elektrisk process som, inom bruksgränserna, är lämplig för att tillhandahålla frekvensregleringstjänster till det nationella nätet. En utvärdering av brukets elförbrukning samt de tekniska krav som ställs på reservmarknaden ledde till att en elektrisk panna med tillkopplad ångackumulator identifierades som mest lämplig.Fem budstrategier som simulerar brukets deltagande till olika energioch reservmarknader har presenterats. För varje strategi är ett linjärt optimeringsproblem formulerat. Den första strategin visar på nuvarande sätt bruket köper elektricitet på spotmarknaden. Den andra strategin integrerar användning av ångackumulatorn som ett verktyg för att utföra termisk lastskiftning. I den tredje modelleras deltagande också på primärreservmarknaden genom att erbjuda en viss kapacitet hos elpannan. De två sista strategierna baseras på den första och tredje, men tillåter i tillägg obalanser vilket innebär en extra kostnad eller möjlig intjäning för bruket.De tre sista problemformuleringarna faller under definitionen stokastiska problem, eftersom två slumpmässiga variabler är närvarande, nämligen: genomsnittligt timfrekvensvärde och priset för obalans. Osäkerheten för variablerna representeras genom scenarier.Resultatet visar att varje strategi ger en ekonomisk besparing jämfört med refer-ensfallet (strategi ett). De mindre intressanta strategierna är de som inte involverarreservmarknaden, vilka endast leder till ca 0,03% och 0,06% minskning av den totalaårliga energikostnaden. Däremot, genom att erbjuda FCR-N-kapacitet kan kostnaden för el minskas med 6,69% och 5,15% beroende s eller ej.

Electric power systems are undergoing a paradigm shift where an increasing number of variable renewable energy resources such as wind and solar power are being introduced to all levels of existing power grids. At the same time consumers are gaining a more active role where self energy production and home automation solutions are no longer uncommon. This challenges traditional power systems which were designed to serve as a centralized top-down solution for providing electricity to consumers. Demand response has risen as a promising solution to cope with some of the challenges that this shift is creating. In this thesis, control and scheduling studies using demand response, and consumer load models adapted to environments similar to Sweden are proposed and evaluated. The studies use model predictive control approaches for the purpose of providing ancillary and financial services to electricity market actors using thermal flexibility from detached houses. The approaches are evaluated on use-cases using data from Sweden for the purpose of reducing power imbalances of a balance responsible player and congestion management for a system operator. Simulations show promising results for reducing power imbalances by up to 30% and managing daily congestion of 5-19 MW using demand response. Moreover, a consumer load model of an office building is proposed using a gray-box modeling approach combining physical understanding of buildings with empirical data. Furthermore, the proposed consumer load model along with a similar model for detached houses are packaged and made freely available as MATLAB applications for other researchers and stakeholders working with demand response. The applications allow the user to generate synthetic electricity load profiles for heterogeneous populations of detached houses and office buildings down to 1-min resolution. The aim of this thesis has been to summarize and discuss the main highlights of the included articles. The interested reader is encouraged to investigate further details in the second part of the thesis as they provide a more comprehensive account of the studies and models proposed. / <p>QC 20171011</p>