Project Topics
Get Complete Project Material File(s) Now! »
Net metering and net billing
In the development of self-consumption, energy excess could not be separated from the PV system. Energy excess can be stored in a battery system and or injected in the public distribution grid. The regulator proposes compensation for this injection, typically net metering or net billing: State of the art of energy management for residential sector The household as prosumer is charged based on their net energy usage of kWh at the end of each billing cycle. However, the electricity sold to the energy supplier has not necessarily the same price as electricity bought to the supplier (because of costs that occur in the energy distribution, and/or taxes). This condition depends on national regulations. The energy excess generated could be credited to the user for future usage. When in next month, the house owner still produces energy excess, the credit will be accumulated with the previous one. However, when the consumption is greater than PV production, the surplus credit will cover the difference between production and demand. If the credit is not enough to cover consumption, user should pay the underpayment.
In Net Billing, both generation and consumption of electricity in the household are recorded and billed separately. As a result, customers get charged their full rate per kWh when they consume energy from the grid, but they are also compensated with the same rate for energy exported to the grid. The supplier calculate and inform the charges periodically related to net consumptions.
Self-consumption categories
There are several categories of self-consumption, namely:
1. Random self-consumption, the condition where the house owner could consume their PV production. The ideal situation is to match the production (P) perfectly to load consumption (L). In annual basis, house owner reach energy balance where total amount energy usage equal with total PV production. It condition commonly called by net Zero Energy Building (NZEB) [15]. This condition also means self-consumption ratio (𝜑𝑆𝐶) equal with self-sufficiency ratio (𝜑𝑆𝑆), where it is reflected in the eq. II.1. However, the production can be greater than load consumption occasionally. The energy excess is injected into the public distribution network. Conversely, the production is momentary smaller than load consumption. In result, the house owner will top up their electricity from provider.
2. Optimized self-consumption, the house owner reaches its self-consumption with optimizer method to reduce the instantaneous imbalance to increase energy efficiency and to be more profitable.
3. Stored self-consumption, when the house owner invests in storage system for storing electricity, and then use it later to meet load consumption.
In the connection context, self-consumption is commonly divided in two categories:
1. Isolated Self-consumption (off grid), the house owner that have PV system consume their production, and if they have excess energy, storage system should be improved and or energy management to maximize the self-consumption in order to prevent losing the electricity produced.
2. Self-consumption with grid (on-grid), PV system that installed in the house owner produce the electricity and then consumed by themselves. When the excess energy arise, they have option to store the energy and conduct energy management procedure. They are also able to distribute excess energy to public electricity network. Furthermore, on grid system could divide in two self-consumption categories in accordance utilization namely
Benefit and Challenges of Self-consumption
Welsch et al in their book[17] state that several benefits for the growth of self-consumption:
Enabling transition from RES support scheme (eg. Feed in Tariff, Quota) to market integration of Renewable Energy Source (RES). Self-consumption help to smoothen the transition from the previous policies-driven support scheme to the integration of RES through market forces.
Authorization of consumer and mobilizing new financial resources for RES (especially PV system). Self-consumption enable the household to take responsibility for their consumption.
Therefore, self-consumption bring awareness of household regarding behavior of energy usage. It drive the household to adjust their consumption habits for instance, to shift the demand to the high production. At the same time, by investing small-scale PV system to facilitate self-consumption, households can contribute to the high investment facilities in the energy transition and profit from the high of electricity bills.
Grid Relief and cost of electricity production. Self-consumption of RES support to lower the pressure on the electricity grid emerging the feed-in of electricity from RES in particular the RES production in the high production period. Self-consumption also bring the derivation of electricity production cost. According to book information, in studies, self-consumption with storage and demand response measure can reduce the additional integration cost at high penetration level around 18% of total electricity production by an average of around 20% over all countries. Whereas, the overall additional integration cost of grid extension on the transmission and distribution with self-consumption were estimated to lower than no self-consumption.
Demand Energy Strategies
Electricity become an important thing for household to operate their appliance, However, electricity usage could be enlarged dramatically when household pay attention with their consumption habits. In result, the electricity bills will be emerged sharply. This condition drive the burden in the supply power side. Energy management is one of strategy for helping electricity management, so that the effect from electricity usage could be diminished. There are energy paradigm of energy management namely supply management and demand management.
Energy management from supply side
In Supply management, energy management concentrates to handle conventional power system where it is built based on three assumptions: electricity generation is controllable, electricity demand is uncontrollable and the generated power is transferred from power plants to end-users. There are four methods for maintaining stability and reducing the cost; Unit commitment, economic dispatching, frequency restoration mechanism and contingency reserve. Unit Commitment and economic dispatching are scheduling methods for generator and control generator respectively[19]. Whereas frequency restoration method is used when a difference occurs between demand and generation. In addition, contingency reverses respond to a large loss of power supply.
Power consumption depends on consumer living activities which uncontrolled power consumption could lead to high peak demand. Demand management aims at reducing the high peak demand and the cost of power consumption, and avoiding the blackout in particular at time of a low generation. Demand management should fulfil the satisfaction of user (Quality of Life) and at least support minimum of satisfaction[19]. Control of power consumption also becomes a concern where it only reduces the total consumption. Demand management should consider the part of uncontrollable power consumption in consequence of human activity.
Table of contents :
Acknowledgement
Résume substantiel en Langue Française
List of Content
List of Figure
List of Table
General Introduction
Chapter 1 Introduction Energy Consumption
1.1 Background Energy Consumption and Renewable Energy
1.1.1 Global Energy demand
1.1.2 Renewable Energy Source Development
1.1.3 Building energy consumption
1.1.4 Building Integrated Photo Voltaic (BIPV)
1.2 Photovoltaic: Self-Consumption and Energy Management
1.2.1 Self-consumption in France
1.2.2 Electricity Market: Peer to Peer Trading Concept
1.3 Thesis Content and Organization
Chapter 2 State of the art of energy management for residential sector
2.1 Introduction
2.2 Participation of Smart Grid in Energy Management
2.3 Self-Consumption: Introduction and Application
2.3.1 Net metering and net billing
2.3.2 Self-consumption categories
2.3.3 Benefit and Challenges of Self-consumption
2.4 Demand Energy Strategies
2.4.1 Energy management from supply side
2.4.2 Demand side management
2.5 Home Energy Management System
2.5.1 Component of HEMS
2.5.2 Communication tool in HEMS
2.5.3 HEMS Scheduling
2.6 Prosumer in Coordination Energy Management System
2.7 Peer to Peer Energy Trading in the Communities
2.7.1 Peer to Peer Energy Market Concept
2.7.2 Type of Peer to Peer Energy Trading
2.7.3 Advantage and Drawback of Peer to Peer
2.8 Conclusion
2.9 The Challenge, Research Approach and Thesis Contribution
References
Chapter 3 Simulation platform for study case
3.1 Introduction
3.2 Load profile forecasting in the residential
3.2.1 Literature review
3.2.2 Top-down Approach
3.2.3 Bottom-up approach
3.3 PV Profile Generator
3.3.1 PV forecasting methods
3.3.2 Statistical method
3.3.3 Physical method
3.3.4 Ensemble method (hybrid)
3.4 Energy Storage
3.5 Electric Water Heater
3.5.1 Parameter of Electric Water Heater
3.5.2 User Comfort
3.5.3 Electric Water Heater for modeling
3.6 Thermal Building
3.6.1 Background
3.6.2 Literature review
3.7 Financial Scheme
3.8 Energy Management method
3.8.1 Coordination Energy Management via Bilateral Contract
3.8.2 Application the bilateral contract in Heuristic
3.9 Conclusion
References
Chapter 4 Development of Model Predictive Control in Household Communities
4.1 Introduction
4.2 Model Predictive Control for EMS
4.2.1 Literature review
4.2.2 Optimal Control
4.2.3 Mixed integer programming formulation for MPC
4.2.4 Objective
4.2.5 Application MPC for Energy Management
4.3 Energy Management method and Solving
4.3.1 Coordination of Energy Management in the household
4.3.2 Coordination Energy Management via Bilateral Contract
4.3.3 Centralized Coordination Energy Management
4.3.4 Multilateral Energy Management
4.4 Conclusion
Chapter 5 Case study for Coordinated Energy Management validation simulation based
5.1 Introduction
5.2 Case Study with MPC for Market Model
5.2.1 Bilateral contract Prosumer to Consumer
5.2.2 Prosumer to Prosumer Coordination Energy
5.2.3 Energy management using Centralized Coordination
5.2.4 Pool to Pool Energy Coordination via MPC
5.3 Case study of Energy Coordination integrated with Thermal Building
5.3.1 Background
5.3.2 Introduction of INCAS Building
5.3.3 Local coordination of district in Chambery
5.3.4 Local District in Jakarta
5.3.5 Return of Investment for PV system in District
5.4 Conclusion
Reference
