Cyclic blackout mitigation and prevention

Severe and long-lasting power shortages plague many countries, resulting in cyclic blackouts affecting the life of millions of people. This research focuses on the design, development and evolution of a computer-controlled system for chronic cyclic blackouts mitigation based on the use of an agent-based distributed power management system integrating Supply Demand Matching (SDM) with the dynamic management of Heat, Ventilation, and Air Conditioning (HVAC) appliances. The principle is supported through interlocking different types of HVAC appliances within an adaptive cluster, the composition of which is dynamically updated according to the level of power secured from aggregating the surplus power from underutilised standby generation which is assumed to be changing throughout the day. The surplus power aggregation provides a dynamically changing flow, used to power a basic set of appliances and one HVAC per household. The proposed solution has two modes, cyclic blackout mitigation and prevention modes, selecting either one depends on the size of the power shortage. If the power shortage is severe, the system works in its cyclic blackout mitigation mode during the power OFF periods of a cyclic blackout. The system changes the composition of the HVAC cluster so that its demand added to the demand of basic household appliances matches the amount of secured supply. The system provides the best possible air conditioning/cooling service and distributes the usage right and duration of each type of HVAC appliance either equally among all houses or according to house temperature. However if the power shortage is limited and centred around the peak, the system works in its prevention mode, in such case, the system trades a minimum number of operational air conditioners (ACs) with air cooling counterparts in so doing reducing the overall demand. The solution assumes the use of a new breed of smart meters, suggested in this research, capable of dynamically rationing power provided to each household through a centrally specified power allocation for each family. This smart meter dynamically monitors each customer’s demand and ensures their allocation is never exceeded. The system implementation is evaluated utilising input power usage patterns collected through a field survey conducted in a residential quarter in Basra City, Iraq. The results of the mapping formed the foundation for a residential demand generator integrated in a custom platform (DDSM-IDEA) built as the development environment dedicated for implementing and evaluating the power management strategies. Simulation results show that the proposed solution provides an equitably distributed, comfortable quality of life level during cyclic blackout periods.Severe and long-lasting power shortages plague many countries, resulting in cyclic blackouts affecting the life of millions of people. This research focuses on the design, development and evolution of a computer-controlled system for chronic cyclic blackouts mitigation based on the use of an agent-based distributed power management system integrating Supply Demand Matching (SDM) with the dynamic management of Heat, Ventilation, and Air Conditioning (HVAC) appliances. The principle is supported through interlocking different types of HVAC appliances within an adaptive cluster, the composition of which is dynamically updated according to the level of power secured from aggregating the surplus power from underutilised standby generation which is assumed to be changing throughout the day. The surplus power aggregation provides a dynamically changing flow, used to power a basic set of appliances and one HVAC per household. The proposed solution has two modes, cyclic blackout mitigation and prevention modes, selecting either one depends on the size of the power shortage. If the power shortage is severe, the system works in its cyclic blackout mitigation mode during the power OFF periods of a cyclic blackout. The system changes the composition of the HVAC cluster so that its demand added to the demand of basic household appliances matches the amount of secured supply. The system provides the best possible air conditioning/cooling service and distributes the usage right and duration of each type of HVAC appliance either equally among all houses or according to house temperature. However if the power shortage is limited and centred around the peak, the system works in its prevention mode, in such case, the system trades a minimum number of operational air conditioners (ACs) with air cooling counterparts in so doing reducing the overall demand. The solution assumes the use of a new breed of smart meters, suggested in this research, capable of dynamically rationing power provided to each household through a centrally specified power allocation for each family. This smart meter dynamically monitors each customer’s demand and ensures their allocation is never exceeded. The system implementation is evaluated utilising input power usage patterns collected through a field survey conducted in a residential quarter in Basra City, Iraq. The results of the mapping formed the foundation for a residential demand generator integrated in a custom platform (DDSM-IDEA) built as the development environment dedicated for implementing and evaluating the power management strategies. Simulation results show that the proposed solution provides an equitably distributed, comfortable quality of life level during cyclic blackout periods

The Human Factor in Transmission Network Expansion Planning: The Grid That a Sustainable Energy System Needs

The decarbonization of the energy sector puts additional pressure on the transmission network. The main cause for this is that renewable sources are often more abundant in geographical areas far away from the main demand centers, so new transmission lines are required to connect the new renewable energy capacity. In addition, by connecting different geographical zones, the transmission network could smooth the intermittency and the variability of renewable energy production. Thus, the changing energy landscape leads to a need to reinforce the transmission network through the Network Transmission Expansion Planning. Ideally, all the idiosyncrasies of the electricity system are considered in the operation and expansion planning process. However, several critical dimensions of the planning process are routinely ignored since they may introduce parameters that are difficult to quantify and complexity that state-of-the-art planning methods cannot handle. This paper identifies the most relevant elements related to the human factor, which have been grouped around the main topics: the human behind the technical, the human at the institutional level, and the human at the individual level. This paper also provides an additional formulation that can be used to upgrade existing models to include the human element and discusses the implications of these upgrades. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Funding: This research has been carried out thanks to the Spanish Ministry of Economy and Competitiveness MINECO through BC3 María de Maeztu excellence accreditation MDM-2017-0714 Maria de Maeztu Grant, and through the funding of openENTRANCE project (Open ENergy TRansition ANalyses for a low-carbon Economy) that belongs to LC-SC3-CC-2-2018—Modelling in support to the transition to a Low-Carbon Energy System in Europe

Modelling and analysis of demand response implementation in the residential sector

Demand Response (DR) eliminates the need for expensive capital expenditure on the electricity distribution, transmission and the generation systems by encouraging consumers to alter their power usage through electricity pricing or incentive programs. However, modelling of DR programs for residential consumers is complicated due to the uncertain consumption behavious of consumers and the complexity of schedulling a large number of household appliances. This thesis has investigated the design and the implementation challenges of the two most commonly used DR components in the residential sector, i.e., time of use (TOU) and direct load control (DLC) programs for improving their effectiveness and implementation with innovative strategies to facilitate their acceptance by both consumers and utilities. In price-based DR programs, the TOU pricing scheme is one of the most attractive and simplest approaches for reducing peak electricity demand in the residential sector. This scheme has been adopted in many developed countries because it requires less communication infrastructure for its implementation. However, the implementation of TOU pricing in low and lower-middle income economies is less appealing, mainly due to a large number of low-income consumers, as traditional TOU pricing schemes may increase the cost of electricity for low income residential consumers and adversely affect their comfort levels. The research in this thesis proposes an alternative TOU pricing strategy for the residential sector in developing countries in order to manage peak demand problems while ensuring a low impact on consumers’ monthly energy bills and comfort levels. In this study, Bangladesh is used as an example of a lower-to-middle income developing country. The DLC program is becoming an increasingly attractive solution for utilities in developed countries due to advances in the construction of communication infrastructures as part of the smart grid concept deployment. One of the main challenges of the DLC program implementation is ensuring optimal control over a large number of different household appliances for managing both short and long intervals of voltage variation problems in distribution networks at both medium voltage (MV) and low voltage (LV) networks, while simultaneously enabling consumers to maintain their comfort levels. Another important challenge for DLC implementation is achieving a fair distribution of incentives among a large number of participating consumers. This thesis addresses these challenges by proposing a multi-layer load control algorithm which groups the household appliances based on the intervals of the voltage problems and coordinates with the reactive power from distributed generators (DGs) for the effective voltage management in MV networks. The proposed load controller takes into consideration the consumption preference of individual appliance, ensuring that the consumer’s comfort level is satisfied as well as fairly incentivising consumers based on their contributions in network voltage and power loss improvement. Another significant challenge with the existing DLC strategy as it applies to managing voltage in LV networks is that it does not take into account the network’s unbalance constraints in the load control algorithm. In LV distribution networks, voltage unbalance is prevalent and is one of the main power quality problems of concern. Unequal DR activation among the phases may cause excessive voltage unbalance in the network. In this thesis, a new load control algorithm is developed with the coordination of secondary on-load tap changer (OLTC) transformer for effective management of both voltage magnitude and unbalance in the LV networks. The proposed load control algorithm minimises the disturbance to consumers’ comfort levels by prioritising their consumption preferences. It motivates consumers to participate in DR program by providing flexibility to bid their participation prices dynamically in each DR event. The proposed DR programs are applicable for both developed and developing countries based on their available communication infrastructure for DR implementation. The main benefits of the proposed DR programs can be shared between consumers and their utilities. Consumers have flexibility in being able to prioritise their comfort levels and bid for their participation prices or receive fair incentives, while utilities effectively manage their network peak demand and power quality problems with minimum compensation costs. As a whole, consumers get the opportunity to minimise their electricity bills while utilities are able to defer or avoid the high cost of their investment in network reinforcements

A review of World Bank lending for electric power

This paper presents the result of an evaluation of about 300 power projects financed by the World Bank and IDA between 1965 and 1983. The study shows a declining trend in power sector performance in spite of Bank involvement in the sector. It recommends greater emphasis on : improving productive and allocative efficiency; increasing incentives for enhanced utility efficiency; strengthening of power-energy-macroeconomic linkages; improving investment planning to achieve a better balance between generation and distribution, and giving greater emphasis to rehabilitation and maintenance. Sector restructuring and institutional reform is also recommended to improve the social compact between government, consumers and the electric utility.Banks&Banking Reform,Environmental Economics&Policies,Economic Theory&Research,Health Monitoring&Evaluation,Business Environment

Dispa-SET 2.0: unit commitment and power dispatch model

Most analyses of the future European energy system conclude that in order to achieve energy and climate change policy goals it will be necessary to ramp up the use of renewable energy sources. The stochastic nature of those energies, together with other sources of short- and long-term uncertainty, already have significant impacts in current energy systems operation and planning, and it is expected that future energy systems will be forced to become increasingly flexible in order to cope with these challenges. Therefore, policy makers need to consider issues such as the effects of intermittent energy sources on the reliability and adequacy of the energy system, the impacts of rules governing the curtailment or storage of energy, or how much backup dispatchable capacity may be required to guarantee that energy demand is safely met. Many of these questions are typically addressed by detailed models of the electric power sector with a high level of technological and temporal resolution. This report describes one of such models developed by the JRC's Institute for Energy and Transport: Dispa-SET 2.0, a unit commitment and dispatch model of the European power system aimed at representing with a high level of detail the short-term operation of large-scale power systems. The new model is an updated version of Dispa-SET 1.0, in use at the JRC since 2009.JRC.F.6-Energy Technology Policy Outloo

Coordinated and optimized voltage management of distribution networks with multi-microgrids

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

Quantifying energy transition pathways: an integrated framework approach

This thesis provides quantitative insights into energy transition pathways using a framework approach (i.e., IESA), which links bottom-up and top-down energy and economy models, covers the whole demand, supply, infrastructure and trade of energy, has a low entry-barrier, and features advanced capabilities, such as, wide range of flexibility options and hourly temporal resolution, tailored to answer future policy questions. Moreover, the current study shows the implications of model improvements on required data at specific resolutions and how data availability restrains such improvements. Finally, the thesis demonstrates how the higher modeling capabilities and resolutions inform Dutch energy transition scenarios with respect to environmental policies, direction and timing of investments, and its impact on the economy

Advances in Energy System Optimization

The papers presented in this open access book address diverse challenges in decarbonizing energy systems, ranging from operational to investment planning problems, from market economics to technical and environmental considerations, from distribution grids to transmission grids, and from theoretical considerations to data provision concerns and applied case studies. While most papers have a clear methodological focus, they address policy-relevant questions at the same time. The target audience therefore includes academics and experts in industry as well as policy makers, who are interested in state-of-the-art quantitative modelling of policy relevant problems in energy systems. The 2nd International Symposium on Energy System Optimization (ISESO 2018) was held at the Karlsruhe Institute of Technology (KIT) under the symposium theme “Bridging the Gap Between Mathematical Modelling and Policy Support” on October 10th and 11th 2018. ISESO 2018 was organized by the KIT, the Heidelberg Institute for Theoretical Studies (HITS), the Heidelberg University, the German Aerospace Center and the University of Stuttgart