Development of an intelligent decision supporting home energy management system

One of the main goals of Smart grid is to achieve Demand Response by increasing the end users’ participation in decision-making and increasing the awareness that will help consumers to efficiently manage their energy consumption. However the existing demand response (DR) mechanism reduces power consumption based on predetermined policies of load priority (direct load control and pricing techniques) during the peak times without considering consumer comfort and environmental issues. Demand response has been achieved by forcefully shutdown the consumers’ loads during peak hours which violate users’ comfort life style. This is due to lacking of intelligent energy management system and smart automation tools at home level. The main objective of this thesis paper is to develop a model based intelligent decision supporting Energy Management system which will understand the customer consumption behaviours while simultaneously reduce the energy consumptions. To achieve these, a Fuzzy Multi Criteria Decision Making (MCDM) based load controller has been developed to prioritize the consumers’ preferences and to take decision on behalf of the consumers in order to best manage the use of their appliances. The Fuzzy Multi Criteria Decision Making (MCDM) methodology has been used because it can solve decision and planning problems involving multiple criteria. Furthermore a comparative analysis for the power consumption and cost saving performance is carried out to show the benefit of using renewable energy sources along with the proposed fuzzy MCDM based load controller. Simulation results show that the proposed load controller successfully limits the power consumption during the peak hours and concurrently maximizes the savings of energy consumption cost without violating consumer comfort level

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 new approach to voltage management in unbalanced low voltage networks using demand response and OLTC considering consumer preference

Voltage unbalance and magnitude violations under normal operating conditions have become main power quality problems in many low voltage (LV) distribution networks. Maintaining the voltage level in an LV network within the standard limits is the main constraining factor in increasing the network hosting ability for rooftop photovoltaic (PV). This study presents a new effective method for voltage management in unbalanced distribution networks through the implementation of optimal residential demand response (DR) and on-load tap changers (OLTCs). The proposed method minimises the compensation costs of voltage management (cost of DR and network loss), while prioritises the consumer consumption preferences for minimising their comfort level violations. A modified particle swarm optimisation algorithm (MPSO) is utilised to identify the optimal switching combination of household appliances and OLTC tap positions for the network voltage management. The proposed method is comprehensively examined on a real three-phase four-wire Australian LV network with considerable unbalanced and distributed generations. Several scenarios are investigated for improving the network voltage magnitude and unbalance considering individual and coordinated operations of DR and OLTCs (three phase tap control and independent phase tap control). Simulation results show that the coordinated approach of DR and OLTC, especially, DR integrated with OLTC independent phase tap control effectively improves the network voltage and increases the PV hosting capacity

An analysis of the time of use electricity price in the residential sector of Bangladesh

Time of Use (TOU) pricing is a cost-reflective electricity pricing scheme; it has proven to be an effective approach for reducing peak electricity demand in the residential sector around the world, especially in developed countries. The implementation of TOU pricing in low and lower-middle income economies is less appealing than in other settings. This is mainly because a traditional TOU pricing scheme may increase the cost of electricity for low income consumers. The lack of a suitable TOU pricing strategy for these countries results in high peak demand, poor utilization of network infrastructure and, consequently, higher electricity prices than necessary. The purpose of this study is to analyse and propose a TOU pricing scheme for the residential sector that will be suitable for countries with a high percentage of low income household consumers. In this study, Bangladesh will be used as an exemplar of a lower-to-middle income developing country. In Bangladesh, the residential sector is responsible for half the country's total electricity consumption, and constitutes an even greater proportion of the peak demand. Residential consumers currently pay inclining block usage rates that provide no financial incentive for them to shift their electricity usage from peak to non-peak periods. The proposed TOU pricing scheme is a combination of the traditional TOU and inclining block usage pricing schemes, based on a realistic load shifting capacity that is applicable to Bangladesh, and to other similar developing countries. Analysis of this pricing system for different income levels of residential consumers shows that the proposed scheme effectively reduces the peak demand, while ensuring minimum impact on consumer monthly energy bills and comfort levels. Keywords: Time of use pricing, Peak demand, Inclining block pricing, Low income economies, Banglades

Implementation of Advanced Demand Side Management for Microgrid Incorporating Demand Response and Home Energy Management System

To facilitate the possible technology and demand changes in a renewable-energy dominated future energy system, an integrated approach that involves Renewable Energy Sources (RES)-based generation, cutting-edge communication strategies, and advanced Demand Side Management (DSM) is essential. A Home Energy Management System (HEMS) with integrated Demand Response (DR) programs is able to perform optimal coordination and scheduling of various smart appliances. This paper develops an advanced DSM framework for microgrids, which encompasses modeling of a microgrid, inclusion of a smart HEMS comprising of smart load monitoring and an intelligent load controller, and finally, incorporation of a DR strategy to reduce peak demand and energy costs. Effectiveness of the proposed framework is assessed through a case study analysis, by investigation of DR opportunities and identification of energy savings for the developed model on a typical summer day in Western Australia. From the case study analysis, it is evident that a maximum amount of 2.95 kWh energy can be shifted to low demand periods, which provides a total daily energy savings of 3%. The total energy cost per day is AU$2.50 and AU$3.49 for a house with and without HEMS, respectively. Finally, maximum possible peak shaving, maximum shiftable energy, and maximum standby power losses and energy cost savings with or without HEMS have been calculated to identify the energy saving opportunities of the proposed strategy for a microgrid of 100 houses with solar, wind, and a back-up diesel generator in the generation side

State of the Art of the Techniques for Grid Forming Inverters to Solve the Challenges of Renewable Rich Power Grids

To mitigate the fast-growing demand of electrical energy, the use of renewable energy resources, e.g., solar and wind, can offer an environmentally friendly and sustainable solution. Due to their intermittent nature, the grid connected operation of renewable energy resources provides a better performance compared to the standalone operation. However, the massive penetration of power electronic inverter/converter-interfaced renewable resources in power systems introduces new issues, such as voltage and frequency instabilities, because of their inherent low inertia properties. As a consequence, these issues may lead to serious problems, such as system blackouts. Therefore, there is an immediate demand to solve these new issues and ensure the normal performance of the power system with the large penetration of renewable energy resources. To achieve this, grid connected inverters/converters are designed to address these problems and behave as synchronous generators, which is possible with grid forming (GFM) inverters/converters concepts. This paper reviews the recent advancement of GFM converters for solving emerging issues related to the renewable rich power grids. It also provides a comprehensive review on frequency deviations and power system stability issues in low-inertia systems and recent advancements in control methods for harmonic mitigation. It is expected that this paper will help the research community to enhance the technology further to solve the challenges in renewable rich power grids

Power Quality Enhancement of Smart Reconfigurable Grids by Integrating Renewable Energy Sources

Electronic-based loads such as computers, smart phones, etc. are fast expanding all around the world. On the other hand, the aging of distribution systems to deliver power to these users results in a low quality of power. To this aim, in this study, renewable energy sources (RESs) connected to networks by smart inverters, are allocated to support networks\u27 weakness related to harmonic distortion, resulting in delivering high-quality power to customers. In other words, solar and wind energy resources are optimally allocated in reconfigurable distribution networks with the aim of minimizing total harmonic distortion (THD). Due to the nonlinearity of the problem, the proposed methodology is then optimized by using the differential evolution algorithm (DEA). The simulation results from a typical 33-bus IEEE test network demonstrate that network reconfiguration in the presence of renewable energies with the interface of smart inverters has an active role in THD compensation, loss minimization, etc