The Experts below are selected from a list of 7098 Experts worldwide ranked by ideXlab platform
Yonghua Song - One of the best experts on this subject based on the ideXlab platform.
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modeling and integration of flexible Demand in heat and electricity integrated energy system
Power and Energy Society General Meeting, 2018Co-Authors: Changzheng Shao, Yi Ding, Jianhui Wang, Yonghua SongAbstract:This paper is focused on utilizing customersi¯ flexible energy Demand, including both heat Demand and electricity Demand, to provide balancing resources and relieve the difficulties of integrating variable wind power with the combined heat and power (CHP). The integration of heat and electricity energy systems providing customers with multiple options for fulfilling their energy Demand is described. Customer aggregators are introduced to supply downstream Demand in the most economical way. Controlling customersi¯ energy consumption behaviors enables aggregators to adjust their energy Demand in response to supply conditions. Incorporating aggregatorsi¯ flexible energy Demand into the centralized energy dispatch model, a two-level optimization problem (TLOP) is firstly formed where the system operator maximizes social welfare subject to aggregatorsi¯ strategies which minimize the energy purchase cost. Furthermore, the sub-problems are linearized based on several reasonable assumptions. Optimal conditions of the sub-problems are then transformed as energy Demands to be described as explicit piecewise-linear functions of electricity prices corresponding to the Demand Bid curves. In this way, the TLOP is transformed to a standard optimization problem, which requires aggregators to only submit a Demand Bid to run the centralized energy dispatch program. All the parameters pertaining to the aggregatorsi¯ energy consumption models are internalized in the Bid curves. The proposed technique is illustrated in a modified testing system.
Aqueel Shah - One of the best experts on this subject based on the ideXlab platform.
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Consolidated Demand Bid model and strategy in constrained Direct Load Control program
2015 IEEE 8th GCC Conference & Exhibition, 2015Co-Authors: Muhammad Babar, T Imthias P Ahamed, Essam Al-ammar, Aqueel ShahAbstract:With the development of the Smart Grid, Direct Load Control (DLC) can be implemented in such a way that consumer can be motivated to participate in it while satisfying ON/OFF constraints of his/her devices. This paper introduces the concept of Consolidated Demand Reduction Bid (CDRB) and develops a dynamic algorithm to compute the same for a consumer having a set of devices with different ratings, importance and constraints. CDRB consist of various power levels at which consumer is willing to curtail it's load during a particular control interval Pl(k) and the corresponding Bid to curtail Pl(k) units of power for a specified duration is F(CPl(k)). The proposed algorithm can be implemented using two way communication between the consumer and the service provider. The applicability of the dynamic algorithm is illustrated using a cases study. The dynamic nature of the algorithm is also illustrated for different choices of the service provider.
Marija Ilic - One of the best experts on this subject based on the ideXlab platform.
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a multi layered adaptive load management alm system information exchange between market participants for efficient and reliable energy use
IEEE PES Transmission and Distribution Conference and Exposition, 2010Co-Authors: Marija IlicAbstract:In this paper, we propose a multi-layered adaptive load management (ALM) system capable of integrating large-scale Demand response efficiently and reliably. At the tertiary layer, the system/market operator utilizes Demand Bid curves provided by the load aggregators on behalf of the end-users they serve. This information is processed by the system/market operator together with the Bid curves provided by the generators. The information is further used to estimate electricity price and send it to load aggregators. Similarly, at the secondary layer, the load aggregators utilize the Demand curves provided to them by the individual end-users. Based on the end-users' requests and the estimated electricity price given by the system/market operator, load aggregators create aggregate Demand curves on behalf of all their users, and share them with both the system operator and their own customers. Finally, at the primary layer, individual end-users create their own Demand functions while taking into consideration their own needs and preferences. They provide this information to their load aggregator. The proposed ALM system is best implemented online. In this paper, we provide a basic formulation of the multi-layered multi-directional decision making and information exchange in support of the ALM system. We illustrate this process using simple simulations. The proposed ALM can be used to implement Demand response for different industry rules, such as fixed rate, time-of-use, and real-time pricing.
Changzheng Shao - One of the best experts on this subject based on the ideXlab platform.
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modeling and integration of flexible Demand in heat and electricity integrated energy system
Power and Energy Society General Meeting, 2018Co-Authors: Changzheng Shao, Yi Ding, Jianhui Wang, Yonghua SongAbstract:This paper is focused on utilizing customersi¯ flexible energy Demand, including both heat Demand and electricity Demand, to provide balancing resources and relieve the difficulties of integrating variable wind power with the combined heat and power (CHP). The integration of heat and electricity energy systems providing customers with multiple options for fulfilling their energy Demand is described. Customer aggregators are introduced to supply downstream Demand in the most economical way. Controlling customersi¯ energy consumption behaviors enables aggregators to adjust their energy Demand in response to supply conditions. Incorporating aggregatorsi¯ flexible energy Demand into the centralized energy dispatch model, a two-level optimization problem (TLOP) is firstly formed where the system operator maximizes social welfare subject to aggregatorsi¯ strategies which minimize the energy purchase cost. Furthermore, the sub-problems are linearized based on several reasonable assumptions. Optimal conditions of the sub-problems are then transformed as energy Demands to be described as explicit piecewise-linear functions of electricity prices corresponding to the Demand Bid curves. In this way, the TLOP is transformed to a standard optimization problem, which requires aggregators to only submit a Demand Bid to run the centralized energy dispatch program. All the parameters pertaining to the aggregatorsi¯ energy consumption models are internalized in the Bid curves. The proposed technique is illustrated in a modified testing system.
Kasimir Egli - One of the best experts on this subject based on the ideXlab platform.
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Analysis of Strategic Behaviour in Combined Electricity and Gas Markets Using Agent-based Computational Economics
2007Co-Authors: Kasimir EgliAbstract:In many European countries, natural gas-fired power plants are considered a possibility to quickly compensate the expected shortfall in electric energy supply. Increasing gasfired generation capacity would also increase the couplings and interactions between gas and electricity systems. So far, gas power plants participate in two different markets gas and electricity. Coupling these markets by establishing a single integrated gas-electricity market clearing could result in better overall market performance. This thesis proposes two integrated natural gas and electricity market models and outlines some of their basic characteristics. Specific emphasis is put on the issue of market power, wich is investigated by using agent-based computational economics. Two different models for integrated gas and electricity markets are compared. In the first model, gas-fired power plants submit two separate Bids an offer Bid for the electricity market and a Demand Bid for the gas market. The plants, which are modelled as learning agents, can vary the intercept of their marginal cost functions when Bidding electricity. On the other hand, they can also change their Demand function for gas. In the second model, power producers submit only one aggregated Bid for their gas-electric conversion capacity, and the agents can vary the intercept of their marginal cost of converting gas into electricity. Further a third model with separated electricity and gas market clearings is introduced to compare separated with combined electricity and natural gas markets. The simulation results show the basic differences between the two market models. Besides overall social welfare, the differences in strategic behaviour and market power are significant. When comparing the two integrated models between each other, the second model with only one aggregated Bid for the gas-electric conversion capacity gives less potential for strategic behaviour to gas power plant operators. The difference between the separated model and the combined model where gas-fired power plant operators offer electricity and Demand gas is small.